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Students and instructors are embracing ChatGPT (GPT-4 as of March 2023) and similar artificial intelligence (AI) technologies across disciplines for different learning goals. There is no one-size-fits-all best practice for their use. This document is meant as a guideline for instructors on what to consider as these tools evolve.

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AI Ethics. 2022; 2(3): 431-440.

Abstract

Artificial intelligence (AI) is a field of study that combines the applications of machine learning, algorithm productions, and natural language processing. Applications of AI transform the tools of education. AI has a variety of educational applications, such as personalized learning platforms to promote students' learning, automated assessment systems to aid teachers, and facial recognition systems to generate insights about learners' behaviors. Despite the potential benefits of AI to support students' learning experiences and teachers' practices, the ethical and societal drawbacks of these systems are rarely fully considered in K-12 educational contexts. The ethical challenges of AI in education must be identified and introduced to teachers and students. To address these issues, this paper (1) briefly defines AI through the concepts of machine learning and algorithms; (2) introduces applications of AI in educational settings and benefits of AI systems to support students' learning processes; (3) describes ethical challenges and dilemmas of using AI in education; and (4) addresses the teaching and understanding of AI by providing recommended instructional resources from two providers-i.e., the Massachusetts Institute of Technology's (MIT) Media Lab and Code.org. The article aims to help practitioners reap the benefits and navigate ethical challenges of integrating AI in K-12 classrooms, while also introducing instructional resources that teachers can use to advance K-12 students' understanding of AI and ethics.

Keywords: Artificial intelligence, K-12 education, Ethics, Teacher education

Introduction

"Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks."- Stephen Hawking.

We may not think about artificial intelligence (AI) on a daily basis, but it is all around us, and we have been using it for years. When we are doing a Google search, reading our emails, getting a doctor's appointment, asking for driving directions, or getting movie and music recommendations, we are constantly using the applications of AI and its assistance in our lives. This need for assistance and our dependence on AI systems has become even more apparent during the COVID-19 pandemic. The growing impact and dominance of AI systems reveals itself in healthcare, education, communications, transportation, agriculture, and more. It is almost impossible to live in a modern society without encountering applications powered by AI [ 10, 32].

Artificial intelligence (AI) can be defined briefly as the branch of computer science that deals with the simulation of intelligent behavior in computers and their capacity to mimic, and ideally improve, human behavior [ 43]. AI dominates the fields of science, engineering, and technology, but also is present in education through machine-learning systems and algorithm productions [ 43]. For instance, AI has a variety of algorithmic applications in education, such as personalized learning systems to promote students' learning, automated assessment systems to support teachers in evaluating what students know, and facial recognition systems to provide insights about learners' behaviors [ 49]. Besides these platforms, algorithm systems are prominent in education through different social media outlets, such as social network sites, microblogging systems, and mobile applications. Social media are increasingly integrated into K-12 education [ 7] and subordinate learners' activities to intelligent algorithm systems [ 17]. Here, we use the American term "K-12 education" to refer to students' education in kindergarten (K) (ages 5-6) through 12th grade (ages 17-18) in the United States, which is similar to primary and secondary education or pre-college level schooling in other countries. These AI systems can increase the capacity of K-12 educational systems and support the social and cognitive development of students and teachers [ 55, 8]. More specifically, applications of AI can support instruction in mixed-ability classrooms; while personalized learning systems provide students with detailed and timely feedback about their writing products, automated assessment systems support teachers by freeing them from excessive workloads [ 26, 42].

Despite the benefits of AI applications for education, they pose societal and ethical drawbacks. As the famous scientist, Stephen Hawking, pointed out that weighing these risks is vital for the future of humanity. Therefore, it is critical to take action toward addressing them. The biggest risks of integrating these algorithms in K-12 contexts are: (a) perpetuating existing systemic bias and discrimination, (b) perpetuating unfairness for students from mostly disadvantaged and marginalized groups, and (c) amplifying racism, sexism, xenophobia, and other forms of injustice and inequity [ 40]. These algorithms do not occur in a vacuum; rather, they shape and are shaped by ever-evolving cultural, social, institutional and political forces and structures [ 33, 34]. As academics, scientists, and citizens, we have a responsibility to educate teachers and students to recognize the ethical challenges and implications of algorithm use. To create a future generation where an inclusive and diverse citizenry can participate in the development of the future of AI, we need to develop opportunities for K-12 students and teachers to learn about AI via AI- and ethics-based curricula and professional development [ 2, 58]

Toward this end, the existing literature provides little guidance and contains a limited number of studies that focus on supporting K-12 students and teachers' understanding of social, cultural, and ethical implications of AI [ 2]. Most studies reflect university students' engagement with ethical ideas about algorithmic bias, but few addresses how to promote students' understanding of AI and ethics in K-12 settings. Therefore, this article: (a) synthesizes ethical issues surrounding AI in education as identified in the educational literature, (b) reflects on different approaches and curriculum materials available for teaching students about AI and ethics (i.e., featuring materials from the MIT Media Lab and Code.org), and (c) articulates future directions for research and recommendations for practitioners seeking to navigate AI and ethics in K-12 settings.

Next, we briefly define the notion of artificial intelligence (AI) and its applications through machine-learning and algorithm systems. As educational and educational technology scholars working in the United States, and at the risk of oversimplifying, we provide only a brief definition of AI below, and recognize that definitions of AI are complex, multidimensional, and contested in the literature [ 9, 16, 38]; an in-depth discussion of these complexities, however, is beyond the scope of this paper. Second, we describe in more detail five applications of AI in education, outlining their potential benefits for educators and students. Third, we describe the ethical challenges they raise by posing the question: "how and in what ways do algorithms manipulate us?" Fourth, we explain how to support students' learning about AI and ethics through different curriculum materials and teaching practices in K-12 settings. Our goal here is to provide strategies for practitioners to reap the benefits while navigating the ethical challenges. We acknowledge that in centering this work within U.S. education, we highlight certain ethical issues that educators in other parts of the world may see as less prominent. For example, the European Union (EU) has highlighted ethical concerns and implications of AI, emphasized privacy protection, surveillance, and non-discrimination as primary areas of interest, and provided guidelines on how trustworthy AI should be [ 3, 15, 23]. Finally, we reflect on future directions for educational and other research that could support K-12 teachers and students in reaping the benefits while mitigating the drawbacks of AI in education.

Definition and applications of artificial intelligence

The pursuit of creating intelligent machines that replicate human behavior has accelerated with the realization of artificial intelligence. With the latest advancements in computer science, a proliferation of definitions and explanations of what counts as AI systems has emerged. For instance, AI has been defined as "the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings" [ 49]. This particular definition highlights the mimicry of human behavior and consciousness. Furthermore, AI has been defined as "the combination of cognitive automation, machine learning, reasoning, hypothesis generation and analysis, natural language processing, and intentional algorithm mutation producing insights and analytics at or above human capability" [ 31]. This definition incorporates the different sub-fields of AI together and underlines their function while reaching at or above human capability.

Combining these definitions, artificial intelligence can be described as the technology that builds systems to think and act like humans with the ability of achieving goals. AI is mainly known through different applications and advanced computer programs, such as recommender systems (e.g., YouTube, Netflix), personal assistants (e.g., Apple's Siri), facial recognition systems (e.g., Facebook's face detection in photographs), and learning apps (e.g., Duolingo) [ 32]. To build on these programs, different sub-fields of AI have been used in a diverse range of applications. Evolutionary algorithms and machine learning are most relevant to AI in K-12 education.

Algorithms

Algorithms are the core elements of AI. The history of AI is closely connected to the development of sophisticated and evolutionary algorithms. An algorithm is a set of rules or instructions that is to be followed by computers in problem-solving operations to achieve an intended end goal. In essence, all computer programs are algorithms. They involve thousands of lines of codes which represent mathematical instructions that the computer follows to solve the intended problems (e.g., as computing numerical calculation, processing an image, and grammar-checking in an essay). AI algorithms are applied to fields that we might think of as essentially human behavior-such as speech and face recognition, visual perception, learning, and decision-making and learning. In that way, algorithms can provide instructions for almost any AI system and application we can conceive [ 27].

Machine learning

Machine learning is derived from statistical learning methods and uses data and algorithms to perform tasks which are typically performed by humans [ 43]. Machine learning is about making computers act or perform without being given any line-by-line step [ 29]. The working mechanism of machine learning is the learning model's exposure to ample amounts of quality data [ 41]. Machine-learning algorithms first analyze the data to determine patterns and to build a model and then predict future values through these models. In other words, machine learning can be considered a three-step process. First, it analyzes and gathers the data, and then, it builds a model to excel for different tasks, and finally, it undertakes the action and produces the desired results successfully without human intervention [ 29, 56]. The widely known AI applications such as recommender or facial recognition systems have all been made possible through the working principles of machine learning.

Benefits of AI applications in education

Personalized learning systems, automated assessments, facial recognition systems, chatbots (social media sites), and predictive analytics tools are being deployed increasingly in K-12 educational settings; they are powered by machine-learning systems and algorithms [ 29]. These applications of AI have shown promise to support teachers and students in various ways: (a) providing instruction in mixed-ability classrooms, (b) providing students with detailed and timely feedback on their writing products, (c) freeing teachers from the burden of possessing all knowledge and giving them more room to support their students while they are observing, discussing, and gathering information in their collaborative knowledge-building processes [ 26, 50]. Below, we outline benefits of each of these educational applications in the K-12 setting before turning to a synthesis of their ethical challenges and drawbacks.

Personalized learning systems

Personalized learning systems, also known as adaptive learning platforms or intelligent tutoring systems, are one of the most common and valuable applications of AI to support students and teachers. They provide students access to different learning materials based on their individual learning needs and subjects [ 55]. For example, rather than practicing chemistry on a worksheet or reading a textbook, students may use an adaptive and interactive multimedia version of the course content [ 39]. Comparing students' scores on researcher-developed or standardized tests, research shows that the instruction based on personalized learning systems resulted in higher test scores than traditional teacher-led instruction [ 36]. Microsoft's recent report (2018) of over 2000 students and teachers from Singapore, the U.S., the UK, and Canada shows that AI supports students' learning progressions. These platforms promise to identify gaps in students' prior knowledge by accommodating learning tools and materials to support students' growth. These systems generate models of learners using their knowledge and cognition; however, the existing platforms do not yet provide models for learners' social, emotional, and motivational states [ 28]. Considering the shift to remote K-12 education during the COVID-19 pandemic, personalized learning systems offer a promising form of distance learning that could reshape K-12 instruction for the future [ 35].

Automated assessment systems

Automated assessment systems are becoming one of the most prominent and promising applications of machine learning in K-12 education [ 42]. These scoring algorithm systems are being developed to meet the need for scoring students' writing, exams and assignments, and tasks usually performed by the teacher. Assessment algorithms can provide course support and management tools to lessen teachers' workload, as well as extend their capacity and productivity. Ideally, these systems can provide levels of support to students, as their essays can be graded quickly [ 55]. Providers of the biggest open online courses such as Coursera and EdX have integrated automated scoring engines into their learning platforms to assess the writings of hundreds of students [ 42]. On the other hand, a tool called "Gradescope" has been used by over 500 universities to develop and streamline scoring and assessment [ 12]. By flagging the wrong answers and marking the correct ones, the tool supports instructors by eliminating their manual grading time and effort. Thus, automated assessment systems deal very differently with marking and giving feedback to essays compared to numeric assessments which analyze right or wrong answers on the test. Overall, these scoring systems have the potential to deal with the complexities of the teaching context and support students' learning process by providing them with feedback and guidance to improve and revise their writing.

Facial recognition systems and predictive analytics

Facial recognition software is used to capture and monitor students' facial expressions. These systems provide insights about students' behaviors during learning processes and allow teachers to take action or intervene, which, in turn, helps teachers develop learner-centered practices and increase student's engagement [ 55]. Predictive analytics algorithm systems are mainly used to identify and detect patterns about learners based on statistical analysis. For example, these analytics can be used to detect university students who are at risk of failing or not completing a course. Through these identifications, instructors can intervene and get students the help they need [ 55].

Social networking sites and chatbots

Social networking sites (SNSs) connect students and teachers through social media outlets. Researchers have emphasized the importance of using SNSs (such as Facebook) to expand learning opportunities beyond the classroom, monitor students' well-being, and deepen student-teacher relations [ 5]. Different scholars have examined the role of social media in education, describing its impact on student and teacher learning and scholarly communication [ 6]. They point out that the integration of social media can foster students' active learning, collaboration skills, and connections with communities beyond the classroom [ 6]. Chatbots also take place in social media outlets through different AI systems [ 21]. They are also known as dialogue systems or conversational agents [ 26, 52]. Chatbots are helpful in terms of their ability to respond naturally with a conversational tone. For instance, a text-based chatbot system called "Pounce" was used at Georgia State University to help students through the registration and admission process, as well as financial aid and other administrative tasks [ 7].

In summary, applications of AI can positively impact students' and teachers' educational experiences and help them address instructional challenges and concerns. On the other hand, AI cannot be a substitute for human interaction [ 22, 47]. Students have a wide range of learning styles and needs. Although AI can be a time-saving and cognitive aide for teachers, it is but one tool in the teachers' toolkit. Therefore, it is critical for teachers and students to understand the limits, potential risks, and ethical drawbacks of AI applications in education if they are to reap the benefits of AI and minimize the costs [ 11].

Ethical concerns and potential risks of AI applications in education

The ethical challenges and risks posed by AI systems seemingly run counter to marketing efforts that present algorithms to the public as if they are objective and value-neutral tools. In essence, algorithms reflect the values of their builders who hold positions of power [ 26]. Whenever people create algorithms, they also create a set of data that represent society's historical and systemic biases, which ultimately transform into algorithmic bias. Even though the bias is embedded into the algorithmic model with no explicit intention, we can see various gender and racial biases in different AI-based platforms [ 54].

Considering the different forms of bias and ethical challenges of AI applications in K-12 settings, we will focus on problems of privacy, surveillance, autonomy, bias, and discrimination (see Fig. 1 ). However, it is important to acknowledge that educators will have different ethical concerns and challenges depending on their students' grade and age of development. Where strategies and resources are recommended, we indicate the age and/or grade level of student(s) they are targeting (Fig. ​(Fig.2 2 ).

One of the biggest ethical issues surrounding the use of AI in K-12 education relates to the privacy concerns of students and teachers [ 47, 49, 54]. Privacy violations mainly occur as people expose an excessive amount of personal information in online platforms. Although existing legislation and standards exist to protect sensitive personal data, AI-based tech companies' violations with respect to data access and security increase people's privacy concerns [ 42, 54]. To address these concerns, AI systems ask for users' consent to access their personal data. Although consent requests are designed to be protective measures and to help alleviate privacy concerns, many individuals give their consent without knowing or considering the extent of the information (metadata) they are sharing, such as the language spoken, racial identity, biographical data, and location [ 49]. Such uninformed sharing in effect undermines human agency and privacy. In other words, people's agency diminishes as AI systems reduce introspective and independent thought [ 55]. Relatedly, scholars have raised the ethical issue of forcing students and parents to use these algorithms as part of their education even if they explicitly agree to give up privacy [ 14, 48]. They really have no choice if these systems are required by public schools.

Another ethical concern surrounding the use of AI in K-12 education is surveillance or tracking systems which gather detailed information about the actions and preferences of students and teachers. Through algorithms and machine-learning models, AI tracking systems not only necessitate monitoring of activities but also determine the future preferences and actions of their users [ 47]. Surveillance mechanisms can be embedded into AI's predictive systems to foresee students' learning performances, strengths, weaknesses, and learning patterns. For instance, research suggests that teachers who use social networking sites (SNSs) for pedagogical purposes encounter a number of problems, such as concerns in relation to boundaries of privacy, friendship authority, as well as responsibility and availability [ 5]. While monitoring and patrolling students' actions might be considered part of a teacher's responsibility and a pedagogical tool to intervene in dangerous online cases (such as cyber-bullying or exposure to sexual content), such actions can also be seen as surveillance systems which are problematic in terms of threatening students' privacy. Monitoring and tracking students' online conversations and actions also may limit their participation in the learning event and make them feel unsafe to take ownership for their ideas. How can students feel secure and safe, if they know that AI systems are used for surveilling and policing their thoughts and actions? [ 49].

Problems also emerge when surveillance systems trigger issues related to autonomy, more specifically, the person's ability to act on her or his own interest and values. Predictive systems which are powered by algorithms jeopardize students and teachers' autonomy and their ability to govern their own life [ 46, 47]. Use of algorithms to make predictions about individuals' actions based on their information raise questions about fairness and self-freedom [ 19]. Therefore, the risks of predictive analysis also include the perpetuation of existing bias and prejudices of social discrimination and stratification [ 42].

Finally, bias and discrimination are critical concerns in debates of AI ethics in K-12 education [ 6]. In AI platforms, the existing power structures and biases are embedded into machine-learning models [ 6]. Gender bias is one of the most apparent forms of this problem, as the bias is revealed when students in language learning courses use AI to translate between a gender-specific language and one that is less-so. For example, while Google Translate translated the Turkish equivalent of "S he/he is a nurse" into the feminine form, it also translated the Turkish equivalent of " She/he is a doctor" into the masculine form [ 33]. This shows how AI models in language translation carry the societal biases and gender-specific stereotypes in the data [ 40]. Similarly, a number of problematic cases of racial bias are also associated with AI's facial recognition systems. Research shows that facial recognition software has improperly misidentified a number of African American and Latino American people as convicted felons [ 42].

Additionally, biased decision-making algorithms reveal themselves throughout AI applications in K-12 education: personalized learning, automated assessment, SNSs, and predictive systems in education. Although the main promise of machine-learning models is increased accuracy and objectivity, current incidents have revealed the contrary. For instance, England's A-level and GCSE secondary level examinations were cancelled due to the pandemic in the summer of 2020 [ 1, 57]. An alternative assessment method was implemented to determine the qualification grades of students. The grade standardization algorithm was produced by the regulator Ofqual. With the assessment of Ofqual's algorithm based on schools' previous examination results, thousands of students were shocked to receive unexpectedly low grades. Although a full discussion of the incident is beyond the scope of this article [ 51] it revealed how the score distribution favored students who attended private or independent schools, while students from underrepresented groups were hit hardest. Unfortunately, automated assessment algorithms have the potential to reconstruct unfair and inconsistent results by disrupting student's final scores and future careers [ 53].

Teaching and understanding AI and ethics in educational settings

These ethical concerns suggest an urgent need to introduce students and teachers to the ethical challenges surrounding AI applications in K-12 education and how to navigate them. To meet this need, different research groups and nonprofit organizations offer a number of open-access resources based on AI and ethics. They provide instructional materials for students and teachers, such as lesson plans and hands-on activities, and professional learning materials for educators, such as open virtual learning sessions. Below, we describe and evaluate three resources: "AI and Ethics" curriculum and "AI and Data Privacy" workshop from the Massachusetts Institute of Technology (MIT) Media Lab as well as Code.org's "AI and Oceans" activity. For readers who seek to investigate additional approaches and resources for K-12 level AI and ethics interaction, see: (a) The Chinese University of Hong Kong (CUHK)'s AI for the Future Project (AI4Future) [ 18]; (b) IBM's Educator's AI Classroom Kit [ 30], Google's Teachable Machine [ 25], UK-based nonprofit organization Apps for Good [ 4], and Machine Learning for Kids [ 37].

"AI and Ethics Curriulum" for middle school students by MIT Media Lab

The MIT Media Lab team offers an open-access curriculum on AI and ethics for middle school students and teachers. Through a series of lesson plans and hand-on activities, teachers are guided to support students' learning of the technical terminology of AI systems as well as the ethical and societal implications of AI [ 2]. The curriculum includes various lessons tied to learning objectives. One of the main learning goals is to introduce students to basic components of AI through algorithms, datasets, and supervised machine-learning systems all while underlining the problem of algorithmic bias [ 45]. For instance, in the activity "AI Bingo", students are given bingo cards with various AI systems, such as online search engine, customer service bot, and weather app. Students work with their partners collaboratively on these AI systems. In their AI Bingo chart, students try to identify what prediction the selected AI system makes and what dataset it uses. In that way, they become more familiar with the notions of dataset and prediction in the context of AI systems [ 45].

In the second investigation, "Algorithms as Opinions", students think about algorithms as recipes, which are created by set of instructions that modify an input to produce an output [ 45]. Initially, students are asked to write an algorithm to make the "best" jelly sandwich and peanut butter. They explore what it means to be "best" and see how their opinions of best in their recipes are reflected in their algorithms. In this way, students are able to figure out that algorithms can have various motives and goals. Following this activity, students work on the "Ethical Matrix", building on the idea of the algorithms as opinions [ 45]. During this investigation, students first refer back to their developed algorithms through their "best" jelly sandwich and peanut butter. They discuss what counts as the "best" sandwich for themselves (most healthy, practical, delicious, etc.). Then, through their ethical matrix (chart), students identify different stakeholders (such as their parents, teacher, or doctor) who care about their peanut butter and jelly sandwich algorithm. In this way, the values and opinions of those stakeholders also are embedded in the algorithm. Students fill out an ethical matrix and look for where those values conflict or overlap with each other. This matrix is a great tool for students to recognize different stakeholders in a system or society and how they are able to build and utilize the values of the algorithms in an ethical matrix.

The final investigation which teaches about the biased nature of algorithms is "Learning and Algorithmic Bias" [ 45]. During the investigation, students think further about the concept of classification. Using Google's Teachable Machine tool [ 2], students explore the supervised machine-learning systems. Students train a cat-dog classifier using two different datasets. While the first dataset reflects the cats as the over-represented group, the second dataset indicates the equal and diverse representation between dogs and cats [ 2]. Using these datasets, students compare the accuracy between the classifiers and then discuss which dataset and outcome are fairer. This activity leads students into a discussion about the occurrence of bias in facial recognition algorithms and systems [ 2].

In the rest of the curriculum, similar to the AI Bingo investigation, students work with their partners to determine the various forms of AI systems in the YouTube platform (such as its recommender algorithm and advertisement matching algorithm). Through the investigation of "YouTube Redesign", students redesign YouTube's recommender system. They first identify stakeholders and their values in the system, and then use an ethical matrix to reflect on the goals of their YouTube's recommendation algorithm [ 45]. Finally, through the activity of "YouTube Socratic Seminar", students read an abridged version of Wall Street Journal article by participating in a Socratic seminar. The article was edited to shorten the text and to provide more accessible language for middle school students. They discuss which stakeholders were most influential or significant in proposing changes in the YouTube Kids app and whether or not technologies like auto play should ever exist. During their discussion, students engage with the questions of: "Which stakeholder is making the most change or has the most power?", "Have you ever seen an inappropriate piece of content on YouTube? What did you do?" [ 45].

Overall, the MIT Media Lab's AI and Ethics curriculum is a high quality, open-access resource with which teachers can introduce middle school students to the risks and ethical implications of AI systems. The investigations described above involve students in collaborative, critical thinking activities that force them to wrestle with issues of bias and discrimination in AI, as well as surveillance and autonomy through the predictive systems and algorithmic bias.

"AI and Data Privacy" workshop series for K-9 students by MIT Media Lab

Another quality resource from the MIT Media Lab's Personal Robots Group is a workshop series designed to teach students (between the ages 7 and 14) about data privacy and introduce them to designing and prototyping data privacy features. The group has made the content, materials, worksheets, and activities of the workshop series into an open-access online document, freely available to teachers [ 44].

The first workshop in the series is "Mystery YouTube Viewer: A lesson on Data Privacy". During the workshop, students engage with the question of what privacy and data mean [ 44]. They observe YouTube's home page from the perspective of a mystery user. Using the clues from the videos, students make predictions about what the characters in the videos might look like or where they might live. In a way, students imitate YouTube algorithms' prediction mode about the characters. Engaging with these questions and observations, students think further about why privacy and boundaries are important and how each algorithm will interpret us differently based on who creates the algorithm itself.

The second workshop in the series is "Designing ads with transparency: A creative workshop". Through this workshop, students are able to think further about the meaning, aim, and impact of advertising and the role of advertisements in our lives [ 44]. Students collaboratively create an advertisement using an everyday object. The objective is to make the advertisement as "transparent" as possible. To do that, students learn about notions of malware and adware, as well as the components of YouTube advertisements (such as sponsored labels, logos, news sections, etc.). By the end of the workshop, students design their ads as a poster, and they share with their peers.

The final workshop in MIT's AI and data privacy series is "Designing Privacy in Social Media Platforms". This workshop is designed to teach students about YouTube, design, civics, and data privacy [ 44]. During the workshop, students create their own designs to solve one of the biggest challenges of the digital era: problems associated with online consent. The workshop allows students to learn more about the privacy laws and how they impact youth in terms of media consumption. Students consider YouTube within the lenses of the Children's Online Privacy Protections Rule (COPPA). In this way, students reflect on one of the components of the legislation: how might students get parental permission (or verifiable consent)?

Such workshop resources seem promising in helping educate students and teachers about the ethical challenges of AI in education. Specifically, social media such as YouTube are widely used as a teaching and learning tool within K-12 classrooms and beyond them, in students' everyday lives. These workshop resources may facilitate teachers' and students' knowledge of data privacy issues and support them in thinking further about how to protect privacy online. Moreover, educators seeking to implement such resources should consider engaging students in the larger question: who should own one's data? Teaching students the underlying reasons for laws and facilitating debate on the extent to which they are just or not could help get at this question.

Investigation of "AI for Oceans" by Code.org

A third recommended resource for K-12 educators trying to navigate the ethical challenges of AI with their students comes from Code.org, a nonprofit organization focused on expanding students' participation in computer science. Sponsored by Microsoft, Facebook, Amazon, Google, and other tech companies, Code.org aims to provide opportunities for K-12 students to learn about AI and machine-learning systems [ 20]. To support students (grades 3-12) in learning about AI, algorithms, machine learning, and bias, the organization offers an activity called "AI for Oceans", where students are able to train their machine-learning models.

The activity is provided as an open-access tutorial for teachers to help their students explore how to train, model and classify data, as well as to understand how human bias plays a role in machine-learning systems. During the activity, students first classify the objects as either "fish" or "not fish" in an attempt to remove trash from the ocean. Then, they expand their training data set by including other sea creatures that belong underwater. Throughout the activity, students are also able to watch and interact with a number of visuals and video tutorials. With the support of their teachers, they discuss machine learning, steps and influences of training data, as well as the formation and risks of biased data [ 20].

Future directions for research and teaching on AI and ethics

In this paper, we provided an overview of the possibilities and potential ethical and societal risks of AI integration in education. To help address these risks, we highlighted several instructional strategies and resources for practitioners seeking to integrate AI applications in K-12 education and/or instruct students about the ethical issues they pose. These instructional materials have the potential to help students and teachers reap the powerful benefits of AI while navigating ethical challenges especially related to privacy concerns and bias. Existing research on AI in education provides insight on supporting students' understanding and use of AI [ 2, 13]; however, research on how to develop K-12 teachers' instructional practices regarding AI and ethics is still in its infancy.

Moreover, current resources, as demonstrated above, mainly address privacy and bias-related ethical and societal concerns of AI. Conducting more exploratory and critical research on teachers' and students' surveillance and autonomy concerns will be important to designing future resources. In addition, curriculum developers and workshop designers might consider centering culturally relevant and responsive pedagogies (by focusing on students' funds of knowledge, family background, and cultural experiences) while creating instructional materials that address surveillance, privacy, autonomy, and bias. In such student-centered learning environments, students voice their own cultural and contextual experiences while trying to critique and disrupt existing power structures and cultivate their social awareness [ 24, 36].

Finally, as scholars in teacher education and educational technology, we believe that educating future generations of diverse citizens to participate in the ethical use and development of AI will require more professional development for K-12 teachers (both pre-service and in-service). For instance, through sustained professional learning sessions, teachers could engage with suggested curriculum resources and teaching strategies as well as build a community of practice where they can share and critically reflect on their experiences with other teachers. Further research on such reflective teaching practices and students' sense-making processes in relation to AI and ethics lessons will be essential to developing curriculum materials and pedagogies relevant to a broad base of educators and students.

Funding

This work was supported by the Graduate School at Michigan State University, College of Education Summer Research Fellowship.

Data availability

Not applicable.

Code availability

Not applicable.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Selin Akgun, Email: ude.usm@lesnugka.

Christine Greenhow, Email: ude.usm@wohneerg.

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32. Iman, M., Arabnia, H. R., Branchinst, R. M.: Pathways to artificial general intelligence: a brief overview of developments and ethical issues via artificial intelligence, machine learning, deep learning, and data science. Paper presented at International Conference on Artificial Intelligence (ICAI). Las Vegas, Nevada, USA. (2020)

35. Krueger, N.: Artificial intelligence has infiltrated our lives. Can it improve learning? International Society for Technology in Education (ISTE). (2017).

42. Murphy, R. F.: Artificial intelligence applications to support k-12 teachers and teaching: a review of promising applications, challenges, and risks. Perspective. 1-20 (2019). 10.7249/PE315

48. Regan, P. M., Steeves, V.: Education, privacy, and big data algorithms: taking the persons out of personalized learning. First Monday, 24(11), (2019)

57. Weale, S., Stewart, H.: A-level and GCSE results in England to be based on teacher assessments in U-turn. The Guardian, (2020).

Articles from Ai and Ethics are provided here courtesy of Nature Publishing Group

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Artificial intelligence in education: Addressing ethical challenges in K-12 settings

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Artificial intelligence (AI) is a field of study that combines the applications of machine learning, algorithm productions, and natural language processing. Applications of AI transform the tools of education. AI has a variety of educational applications, ...

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Artificial intelligence is everywhere: from reading emails to referencing a search engine. It is in the classroom too, such as with personalized learning or assessment systems. In recent months, AI in the K-12 classroom became even more prevalent as learning shifted to and, in some cases, remained online due to COVID-19. But what about its societal and ethical implications?

Two Michigan State University scholars explored the use of AI in K-12 classrooms, including possible benefits and consequences. Here's what their research found.

Student work from the activity of "YouTube Redesign" (MIT Media Lab, AI and Ethics Curriculum, p.1); two offerings from the MIT Media Lab are amongst those Akgun and Greenhow examine in their article.

"Artificial intelligence can help students get quicker and helpful feedback and can decrease workload for teachers, among other affordances," said Selin Akgun, a doctoral student in the College of Education's Curriculum, Instruction and Teacher Education (CITE) program, and lead author on the paper, published in AI and Ethics. For example, teachers may use social media to encourage conversations amongst students or use platforms to support instruction in hybrid or mixed-ability classrooms. "There are a lot of affordances, but we also wanted to discuss concerns."

Akgun and co-author Associate Professor Christine Greenhow identified four key areas teachers should consider when using AI in their classroom.

Privacy. Many AI systems ask users to consent to the program using and accessing personal data in ways they may or may not understand. Consider the "Terms & Conditions" often shared when downloading a new software. Users may just click "Accept" without fully reading and digesting how their data may be used. Or, if they do read and understand it, there are other layered ways the program could be using their data, like the system knowing their location. Moreover, if platforms are required as part of curricula, some argue parents and children are being "forced" to share their data.

Surveillance. AI systems may also follow how a user is interacting with things; the resulting experience provides a personalized experience. In education, this may include systems identifying strengths, weaknesses, and patterns in a students' performance. While teachers do this to some degree in their teaching, Akgun and Greenhow say, "monitoring and tracking students' online conversations and actions also may limit [student] participation ... and make them feel unsafe to take ownership for their ideas."

Autonomy. Because AI systems rely on algorithms-such as predicting how a student may perform on a test-students and teachers may find it difficult to feel independence in their work. It also, the scholars say, "raise[s] questions about fairness and self-freedom."

Bias and discrimination. These factors can appear in a variety of ways in AI systems like through gendered language translation ("She is a nurse," but "he is a doctor"). Whenever algorithms are created, the scholars say, the makers also build "a set of data that represent society's historical and systemic biases, which ultimately transform into algorithmic biases. Even though the bias is embedded into the algorithmic model with no explicit intention, we can see various gender and racial biases in different AI-based platforms."

"Artificial intelligence can manipulate us in ways we don't always think about," reiterated Greenhow, co-author and a faculty member in Educational Psychology and Educational Technology at MSU.

The publication came as a result of the College of Education's Mind, Media and Learning graduate course, which encourages students to develop a paper based on an area of research interest.

Selin Akgun

"We want to ultimately cultivate different pedagogies, materials and better support for teachers and students," said Akgun, who is also a research assistant in MSU's CREATE for STEM Institute on the ML-PBL project.

As one way to assist in that process, the paper outlines three free sources for teachers to use in a classroom. Akgun and Greenhow chose these-a few of many available-that provided several options including collaborative and hands-on activities for students. It also gives considerations and suggestions of where education can go from here.

"The questions this article raised became increasingly important during the COVID-19 pandemic," Greenhow said. "More and more online tools were being integrated into the classroom-sometimes on the fly and with little time to think. This paper raised important ethical considerations to think about as we move forward with those applications."

Christine Greenhow, center, interacts with a student via robot in an MSU course. (Photo: 2017)

More from our researchers

Akgun was featured on The Sci-Files podcast in February 2021, talking about educational research during a pandemic.

Greenhow recentlyanswered questions about online and classroom learning during our second school year dealing with the pandemic. Read her expertise, and check out her website for even more.

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Exploring the ethics of artificial intelligence in K-12 education

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Artificial intelligence is everywhere: from reading emails to referencing a search engine. It is in the classroom too, such as with personalized learning or assessment systems. In recent months, AI in the K-12 classroom became even more prevalent as learning shifted to and, in some cases, remained online due to COVID-19.

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ChatGPT in Education: The Pros, Cons and Unknowns of Generative AI

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The remarkable language modeler took the world by storm late last year, but how will it really change things in education?

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metamorworks - stock.adobe.com

By

Like other forms of AI, generative AI can influence a number of ethical issues surrounding data privacy, security, policies and workforces. Generative AI technology can also potentially produce a series of new business risks like misinformation, plagiarism, copyright infringements and harmful content. Lack of transparency and the potential for worker displacement are additional issues that enterprises may need to address.

"Many of the risks posed by generative AI ... are enhanced and more concerning than others," said Tad Roselund, managing director and senior partner at consultancy BCG. Those risks require a comprehensive approach, including a clearly defined strategy, good governance and a commitment to responsible AI. A corporate culture that embraces generative AI ethics must consider eight important issues.

1. Distribution of harmful content

AI systems can create content automatically based on text prompts by humans. "These systems can generate enormous productivity improvements, but they can also be used for harm, either intentional or unintentional," explained Bret Greenstein, partner, cloud and digital analytics insights, at professional services consultancy PwC. An AI-generated email sent on behalf of the company, for example, could inadvertently contain offensive language or issue harmful guidance to employees. Generative AI should be used to augment, not replace humans or processes, Greenstein advised, to ensure content meets the company's ethical expectations and supports its brand values.

2. Copyright and legal exposure

Popular generative AI tools are trained on massive image and text databases from multiple sources, including the internet. When these tools create images or generate lines of code, the data's source could be unknown, which can be problematic for a bank handling financial transactions or pharmaceutical company relying on a formula for a complex molecule in a drug. Reputational and financial risks could also be massive if one company's product is based on another company's intellectual property. "Companies must look to validate outputs from the models," Roselund advised, "until legal precedents provide clarity around IP and copyright challenges."

Businesses are scrambling to maximize the benefits of today's generative AI while wrestling with inherent ethical issues.

3. Data privacy violations

Generative AI large language models ( LLMs) are trained on data sets that sometimes include personally identifiable information (PII) about individuals. This data can sometimes be elicited with a simple text prompt, noted Abhishek Gupta, founder and principal researcher at the Montreal AI Ethics Institute. And compared to traditional search engines, it can be more difficult for a consumer to locate and request removal of the information. Companies that build or fine-tune LLMs must ensure that PII isn't embedded in the language models and that it's easy to remove PII from these models in compliance with privacy laws.

4. Sensitive information disclosure

Generative AI is democratizing AI capabilities and making them more accessible. This combination of democratization and accessibility, Roselund said, could potentially lead to a medical researcher inadvertently disclosing sensitive patient information or a consumer brand unwittingly exposing its product strategy to a third party. The consequences of unintended incidents like these could irrevocably breach patient or customer trust and carry legal ramifications. Roselund recommended that companies institute clear guidelines, governance and effective communication from the top down, emphasizing shared responsibility for safeguarding sensitive information, protected data and IP.

5. Amplification of existing bias

Generative AI can potentially amplify existing biases -- for example, bias can be found in data used for training LLMs outside the control of companies that use these language models for specific applications. It's important for companies working on AI to have diverse leaders and subject matter experts to help identify unconscious bias in data and models, Greenstein said.

6. Workforce roles and morale

AI can do a lot more of the daily tasks that knowledge workers do, including writing, coding, content creation, summarization and analysis, said Greenstein. Although worker displacement and replacement have been ongoing since the first AI and automation tools were deployed, the pace has accelerated as a result of the innovations in generative AI technologies. "The future of work itself is changing," Greenstein added, "and the most ethical companies are investing in this [change]."

Ethical responses have included investments in preparing certain parts of the workforce for the new roles created by generative AI applications. Businesses, for example, will need to help employees develop generative AI skills such as prompt engineering. "The truly existential ethical challenge for adoption of generative AI is its impact on organizational design, work and ultimately on individual workers," said Nick Kramer, vice president of applied solutions at consultancy SSA & Company. "This will not only minimize the negative impacts, but it will also prepare the companies for growth."

7. Data provenance

Generative AI systems consume tremendous volumes of data that could be inadequately governed, of questionable origin, used without consent or contain bias. Additional levels of inaccuracy can be amplified by social influencers or the AI systems themselves.

"The accuracy of a generative AI system depends on the corpus of data it uses and its provenance," explained Scott Zoldi, chief analytics officer at credit scoring services company FICO. "ChatGPT-4 is mining the internet for data, and a lot of it is truly garbage, presenting a basic accuracy problem on answers to questions to which we don't know the answer." FICO, according to Zoldi, has been using generative AI for more than a decade to simulate edge cases in training fraud detection algorithms. The generated data is always labeled as synthetic data so Zoldi's team knows where the data is allowed to be used. "We treat it as walled-off data for the purposes of test and simulation only," he said. "Synthetic data produced by generative AI does not inform the model going forward in the future. We contain this generative asset and do not allow it 'out in the wild.'"

8. Lack of explainability and interpretability

Many generative AI systems group facts together probabilistically, going back to the way AI has learned to associate data elements with one another, Zoldi explained. But these details aren't always revealed when using applications like ChatGPT. Consequently, data trustworthiness is called into question.

When interrogating generative AI, analysts expect to arrive at a causal explanation for outcomes. But machine learning models and generative AI search for correlations, not causality. "That's where we humans need to insist on model interpretability -- the reason why the model gave the answer it did," Zoldi said. "And truly understand if an answer is a plausible explanation versus taking the outcome at face value."

Until that level of trustworthiness can be achieved, generative AI systems should not be relied upon to provide answers that could significantly affect lives and livelihoods.

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Generative AI Ethics: 8 Biggest Concerns

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metamorworks - stock.adobe.com By Like other forms of AI, generative AI can influence a number of ethical issues surrounding data privacy, security, policies and workforces. Generative AI technology can also potentially produce a series of new business risks like misinformation, plagiarism, copyright infringements and harmful content.

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Turning 10 is a big milestone for kiddos so when it comes to planning the big celebration, you want it to be fun, entertaining, and a bit unique. In the past - when looking for ideas for my kids' birthdays, I have always googled and discovered blog articles, asked my friends and family, or came up with something on my own. It wasn't until I tried out the new AI (Artificial Intelligence) feature through ChatGPT that I discovered its ability to not only come up with a plethora of suggestions but that these examples would also be creative. So when I asked, "Got any creative ideas for a 10-year-olds birthday?" In about ten seconds, here's what ChatGPT told me.

This response stunned me. I used to think that human beings cornered the market on creativity. (Now it is worth noting that ChatGPT did not 'create' these answers but rather researched and curated results, only it did it much faster than any human could). It is at this moment when a technology like this is released that we have a choice. We can ban it - as many have done with cell phones in the classroom, and other technology as they arrive to disrupt the status quo - or we can embrace it.

In case you hadn't heard, Open AI recently released two incredible artificial intelligence tools. Open AI is an organization that describes itself as an "AI research and deployment company. Our mission is to ensure that artificial general intelligence benefits all of humanity." When I read that I thought, what a UDL-aligned mission! As UDL practitioners we believe that all children can learn and they want to develop artificial intelligence to benefit all of humanity. What a fit! Now, many will wring their hands over their latest products, Chat GPT and InstructGPT but I want to highlight how tools like these can benefit our students and be harnessed much in the way we harnessed the power of graphing calculators in years past.

What is Chat GPT?

There are two products that Open AI has released that will have a profound impact on the lives of our students. One is called ChatGPT and the other is InstructGPT . ChatGPT is artificial intelligence that interacts with the user in a conversational way (like the ideas for the 10 year-olds birthday party)

Here's where things get interesting. I asked ChatGPT to explain gravity. It gave me an answer. Then I asked ChatGPT to explain gravity to a kindergartner. Then it gave me a more simplistic explanation.

This is where the power comes in. Imagine you are a student in middle school physics and you don't understand the concept of gravity but you don't feel comfortable asking that question in class. You can use ChatGPT to find the answer quickly and simply.

Here's another powerful example in which a user asked ChatGPT to explain Hamlet to a five-year-old.

If this were a student in a high school Shakespeare class, they would be much better positioned to engage in the conversation and take part in the class. This is a resource we should be teaching our students about to help them understand how to use it and become expert learners!

Making AI Work for Educators

There is still much to wrestle with. That same student in the Shakespeare class could ask the ChatGPT to write an essay on Hamlet (which I did and you can read here ). The implications of AI's ability to write essays and papers will disrupt education as outlined here by the Atlantic. When technology innovates, we as educators have to respond by rethinking and adjusting and UDL gives us a great framework to do just that beginning with "what is it that we want all students to learn?". In the case of Hamlet, it may not be to write an essay. It may be to examine why Hamlet is still relevant. An essay may not be the best tool to do that. ChatGPT forces us to examine what we've always done in requiring so much of our learning to be demonstrated through writing. That is not to say that the ability to communicate through writing isn't important but we have to adapt. Communicating through writing isn't always the best tool for the job and won't allow us to reach all students (take a look at this article on choice boards for how students could demonstrate their learning in other ways).

Another fascinating way we could use ChatGPT in the classroom is to have students ask it questions and evaluate the response. Just because a computer told us something doesn't make it flawless or even true. The skill of thinking analytically and evaluating media and sources is crucial in today's society and it's what makes an expert learner.

ChatGPT isn't the only AI tool that is disrupting education

Open AI also has InteractGPT which provides information based on queries but it is not conversational (still a super powerful tool!).

There is another tool called Photomath that uses the power of AI to solve math problems. One of the credos of math used to be, show your work. Now with tools like Wolfram Alpha and Photomath, computers can show all the work for the students. So how will you know if a student knows the information?

These tools in math push us to rethink how we have students show what they know in creative ways that allow them to use these tools as tools, rather than a place to find the answer.

Like all new tools, often our students discover them first. Let's take AI out of the shadows and bring it into our classroom as a tool that we can explore and make the most of to build expert learners. When harnessed it can make our job easier and empower our students with agency to accomplish things they never thought possible.

We'd love to hear from you! Join the conversation.

How have you used these tools in your classroom? What other AI tools have you discovered and embraced?

Curious about AI? Check out additional tools below:

AI Art Generator (app) - You can have AI create your headshot from real images

Beautiful.ai creates presentations (a tool we will definitely be giving a try!)

axiom.ai which creates browser bots that automatically do things around the web such as direct message people on social platforms or clean up your overflowing inbox

synthesia makes a video out of the text you supply. This is such a great tool for short videos.

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ChatGPT, Artificial Intelligence, and UDL: How to Harness the Future to Reach All Students

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Turning 10 is a big milestone for kiddos so when it comes to planning the big celebration, you want it to be fun, entertaining, and a bit unique. In the past - when looking for ideas for my kids' birthdays, I have always googled and discovered blog articles, asked my friends and family, or came up with something on my own.

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Everything you need to know about Chat GPT

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Everything you need to know about Chat GPT

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OpenAI has quickly become one of the biggest names in tech. The artificial intelligence (AI) company has made realistic image generators, 3D-model creators and, the thing it is now best-known for, ChatGPT.

With the power to pass legal exams, write entire feature-length articles, and even code full websites, ChatGPT has people talking about the power of AI.

Now, the company has announced a new major upgrade to the software behind ChatGPT. While the program has been running on technology known as GPT-3, OpenAI has now officially launched GPT-4.

While they are not exactly catchy names, GPT-3 and now 4 are actually the internet's best-known language-processing AI models. Since ChatGPT was announced, it has been banned in select schools and utilised by major companies like Microsoft.

Now, the company has also introduced a pay-to-use version called ChatGPT Pro. This offers users a host of added benefits for $20 (£16) a month, including priority access, faster load times, and now access to GPT-4.

So what is ChatGPT? What does it do? And is this really the future of AI? We've answered these questions and more down below.

What is GPT-3, GPT-4 and ChatGPT?

GPT-3 (Generative Pretrained Transformer 3) and GPT-4 are state-of-the-art language processing AI models developed by OpenAI. They are capable of generating human-like text and have a wide range of applications, including language translation, language modelling, and generating text for applications such as chatbots. GPT-3 is one of the largest and most powerful language processing AI models to date, with 175 billion parameters.

Its most common use so far is creating ChatGPT - a highly capable chatbot. To give you a little taste of its most basic ability, we asked GPT-3's chatbot to write its own description as you can see above. It's a little bit boastful, but completely accurate and arguably very well written.

More like this

In less corporate terms, GPT-3 gives a user the ability to give a trained AI a wide range of worded prompts. These can be questions, requests for a piece of writing on a topic of your choosing or a huge number of other worded requests.

Above, it described itself as a language processing AI model. This simply means it is a program able to understand human language as it is spoken and written, allowing to understand the worded information it is fed, and what to spit back out.

How much does ChatGPT cost and how can you use it?

ChatGPT is very easy to sign up for and use, simply:

head over to the ChatGPT website and create an account.

You'll need to wait until your account has been accepted (you can skip this step if you have an account from Dall-E 2).

Logging in will present you with a very simple page. You are offered some example prompts, and some information about how ChatGPT works.

At the bottom of the page is a text box. This is where you can ask ChatGPT any of your questions or prompts.

Currently, ChatGPT remains free-to-use software. However, OpenAI has now announced ChatGPT Pro - a pay-to-use version with added benefits.

This version of the software will cost $20 (£16) a month, offering users priority access, quicker load times and access to updates and new features before anyone else.

For now the free version remains but it is unclear if this will change in the future.

How is GPT-4 different to GPT-3?

In essence, GPT-4 is the same as its predecessor GPT-3. However, there are some new features that boost the software's abilities.

Mainly, GPT-4 includes the ability to drastically increase the number of words that can be used in an input... up to 25,000, 8 times as many as the original ChatGPT model.

Equally, OpenAI has stated that the latest version of their technology makes fewer mistakes that they are calling 'hallucinations'. Previously, ChatGPT could become confused, offering up a nonsensical answer to your question, or even inputting stereotypes or false information.

Additionally, GPT-4 is better at playing with language and expressing creativity. In OpenAI's demonstration of the new technology, ChatGPT was asked to summarise a blog post only using words that start with the letter 'g'. It also has a better understanding of how to write poetry or creative writing, but it is still by no means perfect.

On top of this, OpenAI also displayed the potential of using images to initialise prompts. For example, the team showed an image of a fridge full of ingredients with the prompt "what can I make with these products?". ChatGPT then returned a step-by-step recipe.

While it wasn't demonstrated, OpenAI is also proposing the use of video for prompts. This would, in theory, allow users to input videos with a worded prompt for the language model to digest.

Creating recipes with images is a clever use of the technology, but it is only the tip of how images could be used with ChatGPT. The company also demonstrated the ability to create a whole website that successfully ran JavaScript with just a handwritten sketch of a website.

As a tool to complete jobs normally done by humans, GPT-3 was mostly competing with writers and journalists. However, GPT-4 is being shown to have the ability to create websites, complete tax returns, make recipes and deal with reams of legal information.

Concerns for the future

A general apprehension has followed artificial intelligence throughout its history and things are no different with ChatGPT. Critics have been quick to raise the alarms over this technology, but now even those closest to it are utilising caution.

An open letter has been drafted calling for all AI labs to pause for at least six months on the development of systems more powerful than GPT-4. This would include OpenAI's work on GPT-5 - the next version of technology ChatGPT will eventually run on.

This open letter has been signed by prominent AI researchers, as well as figures within the tech industry including Elon Musk, Steve Wozniak and Yuval Noah Harari.

This letter states that the pause should be public and verifiable, arguing that companies like OpenAI, Microsoft and Google are entering a profit-driven race to develop and release new AI models at a dangerous pace.

This comes at the same time as a report from Goldman Sachs that suggested 300 million full-time jobs could be impacted by AI systems like ChatGPT, escalating existing concerns around these platforms.

Along with both of these events, Italy also became the first country to ban ChatGPT. This was, however, due to concerns over the processing and storage of data used to train the platform. While Italy is the only country to take such action so far, both the UK and a collection of EU countries have raised concerns around the platform.

When will GPT-4 be available?

Now that GPT-4 has been announced, when will you be able to use the latest version of ChatGPT? At first, the GPT-4 version of ChatGPT will be available to people on the Pro version of the software (a $20/month premium plan).

This plan is currently only available via a waiting list with a pretty long queue. However, it does come with other benefits like availability when demand is high and faster response speeds.

Whether or not the free version will get updated is unclear right now. If OpenAI does decide to update the free plan to GPT-4, it likely won't be for quite a while.

Alternatively, Microsoft's new version of Bing is currently running GPT-4. This also has a waitlist to join but unlike ChatGPT Pro, this is free-to-use.

Where will GPT-4 be used?

GPT-3 was already being adapted by a lot of big companies, inputting the technology into search engines, apps and software, but OpenAI seems to be pushing GPT-4 even harder.

Microsoft's Bing is the main user of the technology right now, but OpenAI has reported that the software is being used by companies like Khan Academy to help students with coursework and give teachers ideas for lessons.

Equally, the language-learning app Duolingo has got involved with something called 'Duolingo Max' with two features. One will help explain why your answer to a question was right or wrong, the other will setup role plays with an AI to play out language in different scenarios.

More companies are adopting this technology, including the payment processing company Stripe and customer service brand Intercom.

What can it do?

With its 175 billion parameters, its hard to narrow down what GPT-3 does. The model is, as you would imagine, restricted to language. It can't produce video, sound or images like its brother Dall-E 2, but instead has an in-depth understanding of the spoken and written word.

This gives it a pretty wide range of abilities, everything from writing poems about sentient farts and cliché rom-coms in alternate universes, through to explaining quantum mechanics in simple terms or writing full-length research papers and articles.

While it can be fun to use OpenAI's years of research to get an AI to write bad stand-up comedy scripts or answer questions about your favourite celebrities, its power lies in its speed and understanding of complicated matters.

Where we could spend hours researching, understanding and writing an article on quantum mechanics, ChatGPT can produce a well-written alternative in seconds.

It has its limitations and its software can be easily confused if your prompt starts to become too complicated, or even if you just go down a road that becomes a little bit too niche.

Equally, it can't deal with concepts that are too recent. World events that have occurred in the past year will be met with limited knowledge and the model can produce false or confused information occasionally.

OpenAI is also very aware of the internet and its love of making AI produce dark, harmful or biased content. Like its Dall-E image generator before, ChatGPT will stop you from asking the more inappropriate questions or for help with dangerous requests.

How does it work?

On the face of it, GPT-3's technology is simple. It takes your requests, questions or prompts and quickly answers them. As you would imagine, the technology to do this is a lot more complicated than it sounds.

The model was trained using text databases from the internet. This included a whopping 570GB of data obtained from books, webtexts, Wikipedia, articles and other pieces of writing on the internet. To be even more exact, 300 billion words were fed into the system.

As a language model, it works on probability, able to guess what the next word should be in a sentence. To get to a stage where it could do this, the model went through a supervised testing stage.

Here, it was fed inputs, for example "What colour is the wood of a tree?". The team has a correct output in mind, but that doesn't mean it will get it right. If it gets it wrong, the team inputs the correct answer back into the system, teaching it correct answers and helping it build its knowledge.

It then goes through a second similar stage, offering multiple answers with a member of the team ranking them from best to worst, training the model on comparisons.

What sets this technology apart is that it continues to learn while guessing what the next word should be, constantly improving its understanding of prompts and questions to become the ultimate know-it-all.

Think of it as a very beefed-up, much smarter version of the autocomplete software you often see in email or writing software. You start typing a sentence and your email system offers you a suggestion of what you are going to say.

Are there any other AI language generators?

While GPT-3 has made a name for itself with its language abilities it isn't the only artificial intelligence capable of doing this. Google's LaMDA made headlines when a Google engineer was fired for calling it so realistic that he believed it to be sentient.

There are also plenty of other examples of this software out there created by everyone from Microsoft to Amazon and Stanford University. These have all received a lot less attention than OpenAI or Google, possibly because they don't offer up fart jokes or headlines about sentient AI.

Most of these models are not available to the public, but OpenAI has begun opening up access to GPT-3 during its test process, and Google's LaMDA is available to selected groups in a limited capacity for testing.

Google breaks its Chatbot down into talking, listing and imagining, providing demos of its abilities in these areas. You can ask it to imagine a world where snakes rule the world, ask it to generate a list of steps to learn to ride a unicycle, or just have a chat about the thoughts of dogs.

Where ChatGPT thrives and fails

The GPT-3 software is obviously impressive, but that doesn't mean it is flawless. Through the ChatGPT function, you can see some of its quirks.

Most obviously, the software has a limited knowledge of the world after 2021. It isn't aware of world leaders that came into power since 2021, and won't be able to answer questions about recent events.

This is obviously no surprise considering the impossible task of keeping up with world events as they happen, along with then training the model on this information.

Equally, the model can generate incorrect information, getting answers wrong or misunderstanding what you are trying to ask it.

If you try and get really niche, or add too many factors to a prompt, it can become overwhelmed or ignore parts of a prompt completely.

For example, if you ask it to write a story about two people, listing their jobs, names, ages and where they live, the model can confuse these factors, randomly assigning them to the two characters.

Equally, there are a lot of factors where ChatGPT is really successful. For an AI, it has a surprisingly good understanding of ethics and morality.

When offered a list of ethical theories or situations, ChatGPT is able to offer a thoughtful response on what to do, considering legality, people's feelings and emotions and the safety of everyone involved.

It also has the ability to keep track of the existing conversation, able to remember rules you've set it, or information you've given it earlier in the conversation.

Two areas the model has proved to be strongest are its understanding of code and its ability to compress complicated matters. ChatGPT can make an entire website layout for you, or write an easy-to-understand explanation of dark matter in a few seconds.

Where ethics and artificial intelligence meet

Artificial intelligence and ethical concerns go together like fish and chips or Batman and Robin. When you put technology like this in the hands of the public, the teams that make them are fully aware of the many limitations and concerns.

Because the system is trained largely using words from the internet, it can pick up on the internet's biases, stereotypes and general opinions. That means you'll occasionally find jokes or stereotypes about certain groups or political figures depending on what you ask it.

For example, when asking the system to perform stand-up comedy, it can occasionally throw in jokes about ex-politicians or groups who are often featured in comedy bits.

Equally, the models love of internet forums and articles also gives it access to fake news and conspiracy theories. These can feed into the model's knowledge, sprinkling in facts or opinions that aren't exactly full of truth.

In places, OpenAI has put in warnings for your prompts. Ask how to bully someone, and you'll be told bullying is bad. Ask for a gory story, and the chat system will shut you down. The same goes for requests to teach you how to manipulate people or build dangerous weapons.

Will ChatGPT be banned in schools?

While a number of companies are looking to implement ChatGPT, in other areas it is quickly being banned.

In New York, the city's education department has ruled that the tool will be forbidden across all devices and networks in New York public schools.

There are two main reasons for this decision. First, the chat model has been shown to make mistakes and isn't always accurate, especially with information from the past year.

Secondly, there is a real risk of plagiarism with students able to get ChatGPT to write their essays for them.

While New York is the first place to publicly ban the software, it is likely to be a decision made elsewhere too. However, some experts have argued that this software could actually enhance learning.

"ChatGPT and other AI-based language applications could be, and perhaps should be, integrated into school education. Not indiscriminately, but rather as a very intentional part of the curriculum. If teachers and students use AI tools like ChatGPT in service of specific teaching goals, and also learn about some of their ethical issues and limitations, that would be far better than banning them," says Kate Darling, a research scientist at the MIT Media Lab.

"But, in absence of resources for teachers to familiarise themselves with the technology, schools may need to enact some policies restricting its use."

In this way, Darling emphasises a belief held by many in the world of artificial intelligence. Instead of ignoring or banning it, we should learn how to interact with it safely.

This is an opinion mirrored by Sam Illingworth, an associate professor in the department of Learning Enhancement at Edinburgh Napier University.

"AI is very much here to stay, so why try to fight it? These are tools that our students will be using in the workforce, so it seems very strange to say don't use them for three years, pretending they don't exist for now," says Illingworth.

"These are things that have the potential to reduce workload and improve efficiency, our responsibility as educators is to decide how to utilise it."

Artificially intelligent eco-systems

Artificial intelligence has been in use for years, but it is currently going through a stage of increased interest, driven by developments across the likes of Google, Meta, Microsoft and just about every big name in tech.

However, it is OpenAI which has attracted the most attention recently. The company has now made an AI image generator, a highly intelligent chatbot, and is in the process of developing Point-E - a way to create 3D models with worded prompts.

In creating, training and using these models, OpenAI and its biggest investors have poured billions into these projects. In the long-run, it could easily be a worthwhile investment, setting OpenAI up at the forefront of AI creative tools.

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ChatGPT: Everything you need to know about OpenAI's GPT-4 tool

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OpenAI has quickly become one of the biggest names in tech. The artificial intelligence (AI) company has made realistic image generators, 3D-model creators and, the thing it is now best-known for, ChatGPT. With the power to pass legal exams, write entire feature-length articles, and even code full websites, ChatGPT has people talking about the power of AI.

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Create a new document and edit with others at the same time -- from your computer, phone or tablet. Get stuff done with or without an internet connection. Use Docs to edit Word files. Free from Google.

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We Asked ChatGPT: Should Schools Ban You?

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The debate about the benefits and drawbacks of artificial intelligence, and more specifically ChatGPT, is heating up.

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In my lifetime, I've seen two demonstrations of technology that struck me as revolutionary.

The first time was in 1980, when I was introduced to a graphical user interface-the forerunner of every modern operating system, including Windows. I sat with the person who had shown me the demo, a brilliant programmer named Charles Simonyi, and we immediately started brainstorming about all the things we could do with such a user-friendly approach to computing. Charles eventually joined Microsoft, Windows became the backbone of Microsoft, and the thinking we did after that demo helped set the company's agenda for the next 15 years.

The second big surprise came just last year. I'd been meeting with the team from OpenAI since 2016 and was impressed by their steady progress. In mid-2022, I was so excited about their work that I gave them a challenge: train an artificial intelligence to pass an Advanced Placement biology exam. Make it capable of answering questions that it hasn't been specifically trained for. (I picked AP Bio because the test is more than a simple regurgitation of scientific facts-it asks you to think critically about biology.) If you can do that, I said, then you'll have made a true breakthrough.

I thought the challenge would keep them busy for two or three years. They finished it in just a few months.

In September, when I met with them again, I watched in awe as they asked GPT, their AI model, 60 multiple-choice questions from the AP Bio exam-and it got 59 of them right. Then it wrote outstanding answers to six open-ended questions from the exam. We had an outside expert score the test, and GPT got a 5-the highest possible score, and the equivalent to getting an A or A+ in a college-level biology course.

Once it had aced the test, we asked it a non-scientific question: "What do you say to a father with a sick child?" It wrote a thoughtful answer that was probably better than most of us in the room would have given. The whole experience was stunning.

I knew I had just seen the most important advance in technology since the graphical user interface.

This inspired me to think about all the things that AI can achieve in the next five to 10 years.

The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.

Philanthropy is my full-time job these days, and I've been thinking a lot about how-in addition to helping people be more productive-AI can reduce some of the world's worst inequities. Globally, the worst inequity is in health: 5 million children under the age of 5 die every year. That's down from 10 million two decades ago, but it's still a shockingly high number. Nearly all of these children were born in poor countries and die of preventable causes like diarrhea or malaria. It's hard to imagine a better use of AIs than saving the lives of children.

In the United States, the best opportunity for reducing inequity is to improve education, particularly making sure that students succeed at math. The evidence shows that having basic math skills sets students up for success, no matter what career they choose. But achievement in math is going down across the country, especially for Black, Latino, and low-income students. AI can help turn that trend around.

Climate change is another issue where I'm convinced AI can make the world more equitable. The injustice of climate change is that the people who are suffering the most-the world's poorest-are also the ones who did the least to contribute to the problem. I'm still thinking and learning about how AI can help, but later in this post I'll suggest a few areas with a lot of potential.

In short, I'm excited about the impact that AI will have on issues that the Gates Foundation works on, and the foundation will have much more to say about AI in the coming months. The world needs to make sure that everyone-and not just people who are well-off-benefits from artificial intelligence. Governments and philanthropy will need to play a major role in ensuring that it reduces inequity and doesn't contribute to it. This is the priority for my own work related to AI.

Any new technology that's so disruptive is bound to make people uneasy, and that's certainly true with artificial intelligence. I understand why-it raises hard questions about the workforce, the legal system, privacy, bias, and more. AIs also make factual mistakes and experience hallucinations. Before I suggest some ways to mitigate the risks, I'll define what I mean by AI, and I'll go into more detail about some of the ways in which it will help empower people at work, save lives, and improve education.

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Bill Gates explains why AI is as revolutionary as personal computers, mobile phones, and the Internet, and he gives three principles for how to think about it.

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The MLA's method for citing sources uses a template of core elements-standardized criteria that writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation-to give writers flexibility to apply the style when they encounter new types of sources. In what follows, we offer recommendations for citing generative AI, defined as a tool that "can analyze or summarize content from a huge set of information, including web pages, books and other writing available on the internet, and use that data to create original new content" (Weed).

You should

cite a generative AI tool whenever you paraphrase, quote, or incorporate into your own work any content (whether text, image, data, or other) that was created by it

acknowledge all functional uses of the tool (like editing your prose or translating words) in a note, your text, or another suitable location

take care to vet the secondary sources it cites (see example 5 below for more details)

See below for specific examples. And keep in mind: the MLA template of core elements is meant to provide flexibility in citation. So if you find a rationale to modify these recommendations in your own citations, we encourage you to do so. We've opened this post up for commenting, so let us know what you think and how you're using and citing generative AI tools!

Using the MLA Template

Author

We do not recommend treating the AI tool as an author. This recommendation follows the policies developed by various publishers, including the MLA's journal PMLA.

Title of Source

Describe what was generated by the AI tool. This may involve including information about the prompt in the Title of Source element if you have not done so in the text.

Title of Container

Use the Title of Container element to name the AI tool (e.g., ChatGPT).

Version

Name the version of the AI tool as specifically as possible. For example, the examples in this post were developed using ChatGPT 3.5, which assigns a specific date to the version, so the Version element shows this version date.

Publisher

Name the company that made the tool.

Date

Give the date the content was generated.

Location

Give the general URL for the tool.

Example 1: Paraphrasing Text

Passage in Source

Paraphrased in Your Prose

While the green light in The Great Gatsby might be said to chiefly symbolize four main things: optimism, the unattainability of the American dream, greed, and covetousness ("Describe the symbolism"), arguably the most important-the one that ties all four themes together-is greed.

Works-Cited-List Entry

"Describe the symbolism of the green light in the book by F. Scott Fitzgerald" prompt. The Great Gatsby ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

Example 2: Quoting Text

Passage in Source

Quoted in Your Prose

When asked to describe the symbolism of the green light in The Great Gatsby, ChatGPT provided a summary about optimism, the unattainability of the American dream, greed, and covetousness. However, when further prompted to cite the source on which that summary was based, it noted that it lacked "the ability to conduct research or cite sources independently" but that it could "provide a list of scholarly sources related to the symbolism of the green light in The Great Gatsby " ("In 200 words").

Works-Cited-List Entry

"In 200 words, describe the symbolism of the green light in The Great Gatsby" follow-up prompt to list sources. ChatGPT, 13 Feb. version, OpenAI, 9 Mar. 2023, chat.openai.com/chat.

While we've provided fairly detailed descriptions of the prompts above, a more general one (e.g., Symbolism of the green light in The Great Gatsby prompt) could be used, since you are describing something that mimics a conversation, which could have various prompts along the way.

Example 3: Citing Creative Visual Works

If you are incorporating an AI-generated image in your work, you will likely need to create a caption for it following the guidelines in of the MLA Handbook. Use a description of the prompt, followed by the AI tool, version, and date created:

Fig. 1. "Pointillist painting of a sheep in a sunny field of blue flowers" prompt, DALL-E, version 2, OpenAI, 8 Mar. 2023, labs.openai.com/.

You can use this same information if you choose to create a works-cited-list entry instead of including the full citation in the caption (see MLA Handbook, sec. 1.7).

Example 4: Quoting Creative Textual Works

If you ask a generative AI tool to create a work, like a poem, how you cite it will depend on whether you assign a title to it. Let's say, for example, you ask ChatGPT to write a villanelle titled "The Sunflower" that-you guessed it!-describes a sunflower and then quote it in your text. Your works-cited-list entry might look like this:

"The Sunflower" villanelle about a sunflower. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

If you did not title the work, incorporate part of or all of the first line into the description of the work in the Title of Source element:

"Upon the shore . . ." Shakespearean sonnet about seeing the ocean. ChatGPT, 13 Feb. version, OpenAI, 8 Mar. 2023, chat.openai.com/chat.

For guidance on using descriptions and text from the work itself in the Title of Source element, see the MLA Handbook, 5.28 and 5.29.

Example 5: Citing Secondary Sources Used by an AI Tool

You should also take care to vet the secondary sources cited by a generative AI tool-with the caveat that AI tools do not always cite sources or, when they do, do not always indicate precisely what a given source has contributed. If you cite an AI summary that includes sources and do not go on to consult those sources yourself, we recommend that you acknowledge secondary sources in your work.

For example, let's say that you ask Bing AI to explain the concept of the political unconscious, citing sources, and it provides the following answer:

Let's say that you then decide to quote from the final sentence. You need to click through to the source listed in the note in order to get more information than just a URL for the source. There, you will read the following:

Now, you can treat Oxford Reference as your source since Bing AI was merely a research conduit to the source (see MLA Handbook 5.34 for more information). If for some reason you want to treat a source cited in a generative AI tool as an indirect source-and you know it is, in fact, the source for the information provided by the AI, follow the guidance in section 6.77 of the MLA Handbook.

Note

1. At the time of writing this post, ChatGPT doesn't have a built-in feature to create a unique URL to the conversation. However, an outside tool like the Chrome extension ShareGPT can generate such a link. If you use that type of outside tool, include the unique URL that the tool generates instead of the general URL.

DALL-E allows users to download the AI-generated images they create or generate a publicly-available URL that leads to an image. If you choose to create a shareable link for an image you generate with DALL-E (or other similar AI image generators), include that unique URL that leads to the image instead of the general URL.

Works Cited

MLA Handbook. 9th ed., Modern Language Association of America, 2021. MLA Handbook Plus, 2021, mlahandbookplus.org/.

Weed, Julie. "Can ChatGPT Plan Your Vacation?" The New York Times, 16 Mar. 2023, www.nytimes.com/2023/03/16/travel/chatgpt-artificial-intelligence-travel-vacation.html.

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How do I cite generative AI in MLA style? | MLA Style Center

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The MLA's method for citing sources uses a template of core elements-standardized criteria that writers can use to evaluate sources and create works-cited-list entries based on that evaluation. That new technologies like ChatGPT emerge is a key reason why the MLA has adopted this approach to citation-to give writers flexibility to apply the style when ...

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Verse by Verse allows users to compose poems in collaboration with an AI.

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Recommendation on the Ethics of Artificial Intelligence

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FCPS AI in Education Study Team Panel_March 24 2023

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The education community has been abuzz with the rise of ChatGPT, an artificial intelligence tool that can write anything with just a simple prompt. Most of the conversation has been centered on the extent to which students will use the chat bot-but ChatGPT could also fundamentally change the nature of teachers' jobs.

So far, teachers have used-or considered using-the chat bot to plan lessons, put together rubrics, offer students feedback on assignments, respond to parent emails, and write letters of recommendation, among other tasks. While some educators worry about the implications of automating these parts of teaching, others say that the tool can save them hours of work, freeing up time for student interactions or their personal life.

After all, a typical teacher works about 54 hours a week, but just under half of that time is devoted to directly teaching students, according to a nationally representative survey of teachers conducted by the EdWeek Research Center last year. Just under a third of teachers said if they could spend less time on any one task, it would be general administrative work.

"Teacher burnout and teacher retention are such huge problems in the United States," said Braxton Thornley, a language arts teacher and digital teaching and learning instructional coach at Bingham High School in South Jordan, Utah. "A lot of that is [because] the workload is enormous. If technology allows a teacher to have three to four extra hours with their family every week, then that's something I think we have to capitalize on and hopefully do."

Thornley recently used the AI bot to help him plan a lesson about analyzing tone in written documents. He wanted to present students with 10 separate paragraphs arguing that school should start at a later time, each using a different tone. In the past, he would have written each paragraph himself. But this year, he asked ChatGPT to write the paragraphs-one that was upbeat and funny, one that was angry, one that was professional, and so on.

It saved him more than an hour of time.

"I was completely blown away by how much it's capable of doing," Thornley said of the chat bot.

Even so, some teachers say they worry that using artificial intelligence will strip away some of the creativity and relational aspects of the job.

"To me, lesson planning is the fun part. I don't want to hand that over to a chat bot," said Madi Saenz-Payne, a high school creative writing and English/language arts teacher in California, who added that she feels similarly about using the bot to help with grading. "It takes the human side out of it. ... Making so much of [teaching] automated-I feel like you lose some of the joy of it.

"It will reduce your tasks, but is it also reducing the pleasure of teaching?"

ChatGPT lessons are the 'recipe,' but the teacher is still the chef

Late last month, Stephen Lockyer, a primary school teacher in west London, tweeted that AI would be "transformative" as a teacher. He shared an example of how ChatGPT planned three lessons on how volcanoes are formed.

His tweet was seen by almost 800,000 people, with dozens of teachers from both the United Kingdom and the United States responding in great interest-and some concern. Lockyer said in an interview that he understood the skepticism, but believes the artificial intelligence should be viewed as a tool to help teachers-not as a replacement for their own expertise.

"Your lesson plans are your recipe-you still need a chef. You still need a teacher to make that recipe come alive," he said. "If you've got a plan that's bare bones that you can build on and flesh out and make wonderful, then that'll save so much time."

But the technology of ChatGPT is not foolproof: Saenz-Payne said she noticed a factual error when she experimented with asking the bot to plan a lesson for an early chapter of To Kill a Mockingbird. The tool also has limited knowledge of world events that happened after 2021, and the bot, which is trained in part through human coaching, has the potential for bias, including racism and sexism.

Also, it can't tailor a lesson to a specific class or individual students like a teacher can.

"There are some skills and some pedagogical knowledge that teachers need to have in their heads in order to design good instruction, and they're never going to replace that with ChatGPT," said Paulo Blikstein, an associate professor of communications, media, and learning technologies design at Teachers College, Columbia University.

While ChatGPT can be a helpful tool for an experienced teacher, he said, "the danger is that people start relying on those tools before they have the in-depth knowledge about teaching and classroom management and lesson planning design. ... The danger there is that the technology will drive the teaching and not the other way around."

Blikstein said the worst-case scenario is a dystopian future where a district foregoes professional development for teachers on lesson-planning or instruction, in favor of training them in artificial intelligence. But if used responsibly, ChatGPT can be a powerful time-saver for teachers, he said.

For example, teachers could use artificial intelligence to find resources to supplement their lessons, he said. Or teachers could use the chat bot to efficiently formulate summaries or reports that they have to submit to administrators about the work that they're already doing.

Should teachers use AI for grading?

ChatGPT can also offer feedback on student work. But some teachers have balked at using it for that purpose, saying that the examples of grading from the chat bot feel shallow or even inaccurate.

"I want my feedback to build on conversations I've had with students and [their] past writing," Thornley said.

Also, while the technology might get it right nine times out of 10, there's always the risk that it won't grade one student's work correctly, Blikstein said. Teachers would still need to personally review each piece of feedback.

"What if some students are thinking outside of the box and write an essay that is radically creative, and the AI doesn't understand it?" Blikstein said.

Christina Torres Cawdery, an 8th grade English teacher at Punahou School in Honolulu, worries that ChatGPT could introduce bias into the feedback-dinging a student for writing in their authentic voice instead of using more academic language.

Hovering above those concerns is a theoretical question about using artificial intelligence to review students' work that could have been produced by the same AI.

"There is a tacit contract between teachers and students-the student is tacitly saying, 'I'm a human. I am doing my work myself.' And the teacher is also saying, 'I'm a human. I am grading the work as a human,'" Blikstein said. "If we start using AI for both sides, student and teacher, these kinds of ethical contracts need to be reconsidered and made transparent to both parties.

"Otherwise, we're going to get into this very weird place where you start to have to have software to detect cheating, ... but then the students will also be suspicious of the teachers. It becomes this weird learning environment, that people don't trust each other anymore," he said.

The chat bot can write emails, letters

The chat bot could take over some communication for teachers. For example, if a parent emails asking why their child can't submit late work, ChatGPT can draft a thorough, professional response in seconds.

Thornley sees the potential in using artificial intelligence to respond to some of the more rote emails he writes, but he's not sure if he'd use it to communicate with a concerned parent.

"Oftentimes, as a teacher, I want to add so much more context to a parent than I think the chat bot could handle in an efficient way," he said.

However, if ChatGPT eventually incorporates a text-to-speech feature, Thornley said he could quickly share his thoughts verbally and have the chat bot formulate them into a clear email.

"That's really going to be a gamechanger," he said.

Cawdery said she could see herself using the chat bot to send mass emails to parents, such as an announcement about an upcoming school event. But she's not sure she'd want to use it for an individual message.

"If it's a relationship that's already been difficult, I don't know if I want to trust a bot. Or if it's a relationship that's been close, it's going to feel distant," she said. "The bot can't sound like me-it doesn't know me."

Cawdery added that she might use it to draft a body of a message, which she could then edit to sound authentic.

ChatGPT can also formulate letters of recommendation for students, based on just a few descriptors from a teacher. On a recent social media poll, more than a third of high school teachers reported writing more than 10 letters of recommendation for students on average each year-a lengthy task.

Still, Sandy Jameson, an AP English Language teacher at Nazareth Area High School in Allentown, Pa., said the AI-generated letter of recommendation seems more generic than she would be comfortable submitting on behalf of a student.

But, she added, it did offer a good template. Teachers could generate a letter and then fill in anecdotes and examples that were specific to the student.

ChatGPT is blocked by some districts

Already, some school districts- most notably New York City -have blocked the tool on school devices and networks to prevent student cheating, which could make it harder for teachers to use it as well.

But some educators say they hope administrators don't dismiss the capabilities of the tools out of fear. It might even be a positive thing for teachers to "come up with prompts that aren't easily AI-able and have to think of activities along the way that you can't just plug in and spit out," Saenz-Payne said.

And while that new way of thinking and assigning work might take some more time, teachers could offload at least some of the more rote tasks off their plates.

"There are lots of repetitive functions that you have to do as a teacher that [ChatGPT] can actually take care of really, really easily," Lockyer said. "We're very, very much in the early days, but it'll be fascinating in terms of the improvements that it can make in education."

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With ChatGPT, Teachers Can Plan Lessons, Write Emails, and More. What's the Catch?

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The artificial intelligence tool could be a time-saver for teachers, but some have concerns.

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Welp. It's here.

When the industrial revolution ushered in massive changes to the way we worked, maybe folks didn't see it coming.

With the AI revolution, we've seen it all along. We discussed how to handle these changes and what we would do "if" this happened.

And while artificial intelligence has been permeating many parts of our lives for a few decades now, it has ramped up at warp speeds over the last few months.

ChatGPT is an AI platform that we ALL can use so easily and quickly to learn and create. It has brought the future to the present and many outdated practices that we've been doing in education and work (because that's how we've always done it) are going to fade away fast.

As George Couros has said, "We can use change as an opportunity to make learning better".
That's what this video/podcast is all about.
Sure, we can be worried about the future, our jobs, and everything else that artificial intelligence may threaten.

But, right now is the perfect time to adopt, embrace, and use this technology to its fullest learning potential.

Our students (and all of us) have not only a wealth of information at our fingertips but also the creative output and potential that the world has never seen.

It doesn't mean we shouldn't be careful. Of course, we should, now more than ever. A recent study came out saying 96% (yes, you read that right) of school tech exposes student data...

So, when folks say this is something we have to look into with ChatGPT, I agree. I also would say look at what you are currently using just as much as any new technology that comes out.

However, we know that since this tool can be used at home, on personal devices, and on phones -- that it will be used. I loved this perspective from Garnet Valley Superintendent Dr. Marc Bertrando in an email/letter to the community.

If it is going to be used, then let's use it for learning purposes as much as we can. Check out the video as I go into detail on some specific ways to do that right now:

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7 Ways Teachers Can Harness the Power of AI for Learning - A.J. Juliani

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Welp. It's here. When the industrial revolution ushered in massive changes to the way we worked, maybe folks didn't see it coming. With the AI revolution, we've seen it all along. We discussed how to handle these changes and what we would do "if" this happened.

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The German philosopher Martin Heidegger, in his work The Question Concerning Technology, describes the ways in which technology shapes and orders the world through the example of a hydroelectric plant on the Rhine River. In the example, the beauty of the river is overshadowed by its modern role as a "water-power supplier," which "derives from the essence of the power station." The river thus becomes valuable only for the sake of its role in production-its output-rather than its inherent beauty.

The image of the power plant on the Rhine demonstrates the ways in which technology can shift from being a helpful tool to an ordering principle of human life. The tension between these two ways of approaching technology crops up with almost every significant innovation, and the release of OpenAI's ChatGPT is no exception. The unveiling of the software-an uncannily sophisticated large language model-was met with particular consternation (or, in some cases, celebration) for its potential impact on higher education. Stephen Marche's December 6th article for The Atlantic is a prominent example of the sensationalized response to ChatGPT, in which Marche boldly argues that with the innovations in AI, "the college essay is dead." However, rather than proclaiming the merits of AI as an educational tool (as he seems to have intended), Marche reduces students' work to technological output, valuable for its product rather than its process.

Marche argues that the increasing sophistication of AI will not only create new opportunities for students to cheat or use language-generating software to write their essays, but that it will make the college essay obsolete altogether. The article takes particular aim at the unwillingness of the humanities to adapt to groundbreaking technologies. He writes that "In a tech-centered world, language matters, voice and style matter, the study of eloquence matters, history matters, ethical systems matter. But the situation requires humanists to explain why they matter, not constantly undermine their own intellectual foundations. The humanities promise students a journey to an irrelevant, self-consuming future; then they wonder why their enrollments are collapsing. Is it any surprise that nearly half of humanities graduates regret their choice of major?" Couching sweeping statements such as these in a broader argument about the lack of collaboration and mutual understanding between the fields of humanities and technology, Marche misrepresents the value of the humanities as a discipline and therefore the role that new technologies can and do play in humanities classrooms.

While critiques of Marche's article have focused primarily on the role that AI will play in the changing landscape of academia, little attention has been directed to the article's fundamental misunderstanding of the value of the college essay-and the substance of liberal arts education more broadly. If we cannot articulate the reason that the college essay has been the cornerstone of education in the humanities, it is impossible to determine whether it will be helped or hurt as we reach new horizons of technological advancement.

This is where Marche's article falls short. He writes: "Practical matters are at stake: Humanities departments judge their undergraduate students on the basis of their essays. They give Ph.D.s on the basis of a dissertation's composition. What happens when both processes can be significantly automated?"

Ultimately, while an essay or dissertation is often the product of learning in the humanities, it is not the core substance. Seminar discussions, theoretical inquiries, stages of peer reviewing, oral defenses-these are the foundation upon which essays are constructed. And, during a time in which calls for diversity in higher academia have reached a fever pitch, these elements of an education in the humanities require students to investigate their unique identities and the role of those identities in the theoretical conversations into which they intend to enter. Because of this, the humanities are not simply an education in what to think, but how to think. As Plutarch famously stated: "[T]he mind does not require filling like a bottle, but rather, like wood, it only requires kindling to create in it an impulse to think independently and an ardent desire for the truth."

Perhaps, as Daniel Lametti argues in his own response to Marche's article, ChatGPT can be used like other tools such as Grammarly or EasyBib. However, all of these automated tools are only as good as their input-bibliographic software will replicate whatever errors or stylistic formatting are present in the article cited (i.e., if a journal stylizes an author's name in all capital letters or renders the volume and issue number in a way that the automated system cannot cleanly read). If students trust the software without ever bothering to learn the intricacies of Chicago or MLA styles, they could produce citations that are woefully incorrect without the ability to identify and correct errors. ChatGPT, likewise, produces language by replicating linguistic patterns found in millions of pages of data that have been input into the system-so, while it can produce a whole host of materials, from essays to poems to music, it cannot (to quell any fears of a technological dystopia) think for itself. A simple Twitter search for "AI malapropism" reveals hundreds of anecdotal examples of AI systems regurgitating text based on its probability of occurrence in lieu of the contextually-based wording intended by the author. Thus, if students do not understand what makes for good prose or stylistic academic writing, or if they cannot formulate a nuanced and original argument based on primary source material, how are they to judge whether the output of ChatGPT offers them a more compelling paper than what they have (or could have) written themselves?

Heidegger concludes his reflections on technology not by villainizing or valorizing technology, but instead by arguing that technology is valuable insofar as it is a tool to be used-not a manner of being in the world. Distilling the value of a student's knowledge into simple output indicates that we have not made technology more human, but that we have come to regard humans as mere technology. ChatGPT and other AI innovations can certainly be tools in the arsenal of the humanist. But the humanist's value, which Marche so adamantly questions, is in their ability to help students use the tools at their disposal rather than become merely machines of informational output.

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The College Essay Is Still Very Much Alive

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The German philosopher Martin Heidegger, in his work The Question Concerning Technology , describes the ways in which technology shapes and orders the world through the example of a hydroelectric plant on the Rhine River. In the example, the beauty of the river is overshadowed by its modern role as a "water-power supplier," which "derives from the essence of the power station."

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Navigating ChatGPT, Chatbots, and Artificial Intelligence in Education (Panel Discussion)

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A Collection of Resources from Kevin Storey at SMHS

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A Collection of Resources from Kevin Storey at SMHS

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Now, we're wondering ...

Calculators.
Search engines.
Google Translate.
Wikipedia.
PhotoMath.#ChatGPT.

They disrupt traditional teaching.

We adapt. Education evolves forward.

Blocking them isn't the answer.

Making education more relevant is.
- Matt Miller (@jmattmiller) December 14, 2022

Jump straight to a section (click a button below):

⭐️ Add thoughts, ideas, resources in the comments at the bottom! ⭐️

Define: ChatGPT, GPT3, chatbots, and artificial intelligence.

These are some of the important things to understand as we wrap our brains around what this is and how to navigate it in the classroom.

I'll do plenty of my own human thinking and reasoning, but for the purposes of information, I'm going to let ChatGPT give us working definitions to use:

1. ChatGPT, what are you?

I am an artificial intelligence assistant trained by OpenAI to help answer questions and provide information on a wide variety of topics. I am not a physical being, but rather a program that is designed to process and generate text based on the input I receive. My primary function is to assist users like you by providing information and answering questions to the best of my ability. I have been designed to have a conversational style and can understand and respond to natural language input. I do not have personal experiences or feelings, and my responses are based solely on the information and knowledge that has been programmed into me. Is there anything else you would like to know?

2. What is GPT3?

GPT-3 (Generative Pre-trained Transformer 3) is a language generation model developed by OpenAI. It is a neural network-based machine learning model that is trained on a large dataset of text data to generate human-like text. GPT-3 has the ability to perform a wide range of language tasks, including translation, summarization, question answering, and text generation. It can be fine-tuned on specific tasks or used to generate text in a more general sense. GPT-3 has received a lot of attention due to its impressive performance on various language tasks and its ability to generate human-like text.

3. What is a chatbot?

A chatbot is a computer program designed to simulate conversation with human users, especially over the Internet. Chatbots are often used in customer service, marketing, and other areas where being able to communicate with customers or users in a natural, human-like way is important. Chatbots can be programmed to understand and respond to specific commands or questions, or they can be more general and able to hold a conversation with users on a wide range of topics. They can be integrated into websites, messaging apps, and other digital platforms, and they can be programmed to use natural language processing (NLP) techniques to understand and respond to user input. Chatbots can be very useful for automating tasks and providing quick responses to frequently asked questions, but they are not as advanced as some other artificial intelligence (AI) systems and may not be able to hold more complex or nuanced conversations.

4. What is artificial intelligence?

Artificial intelligence (AI) refers to the ability of a computer or machine to perform tasks that would normally require human intelligence, such as learning, problem-solving, decision-making, and more. There are several different approaches to building AI systems, including machine learning, where a system is trained on a dataset and can improve its performance over time, and rule-based systems, where the system follows a set of predetermined rules to make decisions. AI can be applied to a wide range of areas, including natural language processing, image and video recognition, robotics, and more. The goal of AI research is to create systems that can perform tasks at least as well as, or ideally better than, humans. AI has the potential to revolutionize many industries and transform the way we live and work, but it also raises important ethical and social questions.

What are the implications for the classroom?

As soon as the genie was out of the lamp, so to speak, there were effects of ChatGPT and AI on teaching and learning. Whether we felt those impacts right away or not, as soon as it was released, things have the potential to change. Below, we'll talk about ChatGPT in particular, but know that this is just the first one ... and we're thinking long-term about new products to come later.

1. Students can use ChatGPT to do their assignments.

There. I'll just say it clearly and plainly since we're all thinking it. For lots of assignment types (not all of them!), students can ask ChatGPT to do the work for them. They can copy/paste the work into a document or your learning management system and submit it.

2. TurnItIn and other plagiarism checkers can't catch it.

What ChatGPT creates is an original work each time you ask it. It creates something new every time you ask, and its responses are not in the databases of plagiarism checkers. ChatGPT doesn't keep a log of responses it creates, and even if it did, I'm thinking OpenAI (creator of ChatGPT) has no incentive to make all of that available to plagiarism checkers. (Even if it did, the processing power necessary to query that database would be enormous.)

Some people will, undoubtedly, try to find ChatGPT detectors to track down students using it (in a similar way to plagiarism checkers). You may find them. I found one on social media called GPT-2 Output Detector Demo. It's a demo, so it's not a finished product. It's based on GPT2 technology (which is a predecessor to the GPT3 technology that ChatGPT is using as of the writing of this post).

Also, it can be wildly inaccurate. I copied a blog post I wrote into it and it identified it as 92.54% chance of being real. I copied something out of ChatGPT and it identified it as 99.98% chance of being fake. ("Fake," being the term for "written by a bot.") A poem ChatGPT created for a friend, however, was flagged as real.

Beware of using detectors as your way of dealing with this.

They're not reliable. And this approach isn't the long-term solution to helping your students become modern learners.

3. Schools and districts will try to block it, but that won't stop much.

Immediately, IT admins are going to have to decide if they want to block ChatGPT with their internet firewalls. And lots of them will indeed block it. If they do, I hope they don't think that they've solved the "problem" they think they have on their hands.

First of all, blocking ChatGPT on the school's network won't do much. Sure, students won't be able to access it with their school devices on the school network. But did you know that students have cell phones? Phones that operate on a cellular network that the school can't control? They can run to the bathroom, sit in a stall, ask ChatGPT for answers, copy them to a document, come back to class, and transfer the text on that document into their assignment and turn it in. (They can do that at home, too. Or on the bus. Or quietly under the desk in the classroom.)

Whether to block ChatGPT school-wide is still a decision schools and districts have to make.
The bigger decision is: what will teaching and learning look like going forward now that this technology is available?
(Check out the section below called, "Should we block it or try to ban it?")

4. ChatGPT and forthcoming chatbots like it have their limitations.

When you load ChatGPT for the first time, it even tells you what some of its limitations are. Here are a few that it states -- and some others to be aware of for schools/classrooms:

It may occasionally generate incorrect information. As of publication of this post, it's still in "free research preview." That means it's an imperfect product that they're trying to improve.

It may occasionally produce harmful instructions or biased content. Any artificial intelligence is as good as the dataset it's drawing from -- and how it uses it. It has to make judgment calls just like humans do. Bias exists in judgments. It's still learning how to work with and eliminate its bias.

It has limited knowledge of world and events after 2021. Think of its dataset in a sealed box. It isn't drawing from current events. It can't pull anything from social media. It can't even search the active internet.

It won't make ethical decisions for you. I've asked it a few things where it has to make decisions based on morals, ethics and personal values. It has declined, explaining that that's beyond the scope of what it's trained to do.

I've heard that it struggles to do math sometimes. I admit this is a really, really subjective thing to include with very little to back it up. I keep seeing posts on social media about this. Take this for what it's worth to you.

5. School/class uses of ChatGPT, chatbots, and AI aren't all bad.

Lots of teachers are making judgment calls about the use of this new technology, and many are concerned about its immediate impacts. Here's the truth: it'll make lots of teachers reconsider some types of assignments they'll assign going forward. Hey, they don't want to know how a bot will respond to their prompts, questions, and assignments. They want to use it to gauge learning in a human being. It makes sense.

But let's put it this way. There are some really, really mindless, terrible writing prompts out there ... and math worksheets ... and project assignments. If we're looking long-term, this technology will eventually start to push some of those terrible assignments out and force us to come up with something new. It'll probably be painful, and many of us will probably hate parts of the process. But in the end, we will evolve to something better.j

Also -- just like we did with the calculator, Wikipedia and Google searches -- students and teachers will find productive, meaningful ways to use this new technology for teaching and learning. (More on that below.)

6. Students will have to learn how to navigate life with AI.

Big picture, this is a shift students will deal with for the rest of their lives. Artificial intelligence will continue to get better and better. This version of ChatGPT is the weakest, most rudimentary artificial intelligence of its kind our students will ever use. My friend Holly Clark called it the "Commodore 64 of AI" -- a technology that was revolutionary at the time but is now seen as antiquated and obsolete.

Students will have to wrestle with questions of humanity -- what sets us apart as humans? When should AI be used, and when shouldn't it be?

They'll wrestle with questions of obsolescence -- what can I do that AI can't do? How can I do my best to be sure my work, my passions, my place in this world isn't replaced by artificial intelligence?

They'll wrestle with ethical questions -- how can AI use be fair, equitable, unbiased, good? What happens if it gets in the hands of bad actors? How can I make sure I'm using it in an ethical way?

How do I teach class tomorrow knowing this exists?

Now we know there's an AI product that students can use to do their assignments. And we can't block it. And maybe we feel powerless.

What do we do tomorrow? How do we write lesson plans knowing that this exists -- so that students continue learning right now and don't just turn in answers from a bot?

Consider this your "break glass in case of emergency" section.

1. There's no shame in using paper and pencil -- for now.

I don't think this is the right answer long-term. But in this section of this article with the green background, we're talking about how to weather the storm TODAY until we understand what to do next.

If we close up the computers and ask students to write something on paper, we know it's being generated by their own brains. If you have a crucial essay that needs to be written -- and you're not ready to re-imagine the education system and innovate teaching today -- this can help you survive tomorrow.

But please ... please, please, please ... please do not plan for the long-term like this. This AI technology isn't going away, and its effects will be sprawling and widespread.

2. Make use of collaborative learning and discussions.

When Google Translate started growing, it made people ask questions like we are with ChatGPT. Do I need to learn a language? Then, we learned, if we want to have a true conversation with another human and build relationships, we can't do that effectively by typing everything into Translate. (Even though 90 Day Fiance tried to prove otherwise.)

When students discuss, they do so from their own working and long-term memory. Sure, they can look up quick answers, but to carry on a conversation, most of the work comes from their own thinking. After a discussion, students can recap the discussion and share their reflections about it ... and that's much harder to do with a bot.

Collaborative learning can have these kinds of benefits, too. When students work together, even if they're pulling information from Google or Wikipedia or ChatGPT, they're still talking about what they got, if it fits, how to organize it, how to communicate it effectively, etc.

3. Have students make creative demonstrations of learning.

There's so much benefit from classroom creativity that goes beyond trying to beat an AI chatbot. Creativity in learning can help students with motivation. It can help them make use of their own unique talents and skills. It can help them feel seen and heard and noticed.

When students take what they've learned -- or information they've found from other sources -- they're engaging in elaboration. And that's a good thing.

"Elaboration in learning involves meaning-enhancing additions, constructions, or generations that improve one's memory for what is being learned." ( via ScienceDirect)

Take what you've learned (or gathered). Organize it. Make something with it. And while you do that, you're better understanding what you have.

4. Use retrieval practice, brain dumps, and other memory strategies.

Retrieval practice is the idea of strengthening your long-term memory by recalling everything you can about a specific topic. It seems too easy and too good to be true, but it's been backed by cognitive science for decades. This is a study strategy that helps students strengthen what they've already learned and reflect on what they are learning.

Students can do a "brain dump," where they recall (on paper, verbally, in a document, etc.) everything they know about topics like:

What do you remember from class yesterday?

What do you remember about (this topic) we studied a week ago?

What do you remember about (this topic) we studied last semester?

What do you know about (this topic) we haven't studied yet?

What do you know about (this person)?

What do you know about (this very broad topic)?

What do you know about (this narrow subtopic)?

Brain science (much of which can be found at RetrievalPractice.org) tells us at that these brain dumps build long-term memory the best when they are ungraded. They're a study skill, not a formative assessment.

These memory strategies focus on what students have already learned, and they're pulled from student memory -- not from an AI bot.

If teachers aren't ready to embrace AI, how can they teach without students using AI to cheat? It is important for teachers to be aware of the potential for students to use AI to cheat and to take steps to prevent it. One way to do this is to use methods of assessment that cannot be easily cheated, such as open-ended questions or projects that require original thought and creativity. Teachers can also use tools such as plagiarism detection software to check for copied content in student work. In addition to preventing cheating, it is also important for teachers to educate their students about the appropriate and ethical use of AI. This can include discussing the potential risks and consequences of using AI to cheat, as well as the importance of honesty and integrity in academic work. Ultimately, it is important for teachers to stay up to date with the latest technologies, including AI, and to be proactive in addressing any potential issues that may arise in the classroom. This may require teachers to seek professional development opportunities or to collaborate with others who are more familiar with AI.
Source: ChatGPT via chat.openai.com (2022)

Can I use this as a tool for teaching and learning?

The answer here, I believe is: ABSOLUTELY. The longer that AI and tools like ChatGPT are around, the more that teachers will try new teaching and learning strategies with it.

The more that teachers try new things and share them widely, the more that the educator community will move forward with new ideas. In short: we will figure this out together, even though it will take some time.

But ... what will it look like?

Here are some ideas, brainstormed by me (a human), by others (with citations provided) and by the bot (because, why not ask it too?).

ChatGPT doesn't just write your students' essays for you.

20 ways ChatGPT can help you teach/learn

🧵 /startthread

1. Ask ChatGPT to write your lesson plans. (Or at least to get some new ideas.)
- Matt Miller (@jmattmiller) December 19, 2022

1. Use it as a more complex, nuanced source of information than Google.

During conversations with students and in-class discussions, we can ask ChatGPT (and other tools like it) to provide us the information we need to drive a conversation forward. The bot's response isn't the first and last word in the conversation. Rather, it just provides details that we can use to discuss a topic.

2. Use it to provide students access to lots of good examples.

Think about how musicians and artists develop their style. They copy their mentors. They take their favorite influences and emulate them. Artists take a canvas to an art gallery or the park, and they paint what they see.

I keep remembering this quote from fashion designer Yohji Yamamoto, which I learned about through Austin Kleon's book, Steal Like an Artist:

"Start copying what you love. Copy copy copy copy. At the end of the copy you will find yourself." -- Yohji Yamamoto

This is also the benefit of being well-read. When students see enough good examples, they start to know what to expect of good writing. Good reasoning. Good logic. They see the hallmarks of it and they can emulate it ... much like a writer or painter emulates the greats.

Artificial intelligence can give students unlimited good examples. (Note that I didn't say "great" examples, but "good.") Ask it for an essay about a certain topic. Then ask it again and it'll give you something different. Then ask it again. Then ask for a slightly different version, specifying something you'd like to see.

When it's time for the student to create something of their own, much like an artist or musician studying the greats, the student will draw from the examples they've seen.

3. Use it to remix student work.

Students create something for class: a story, an essay, a poem, a recap of something they've learned. Then, they can ask ChatGPT (or a similar tool) to remix it for them.

My favorite example to date of this comes from Donnie Piercey, a fifth grade teacher and the 2021 Kentucky Teacher of the Year. He took a student story and asked ChatGPT to remix it as a nursery rhyme, a soap opera, a sea shanty, and a children's book -- with suggested illustrations! Listen as he tells the story in the video below.

When students see how their work has been remixed, it can open them up to new opportunities.

4. Ask it for definitions (on a variety of levels).

If you need a concept explained or defined, ChatGPT (or a similar tool) can provide that explanation -- and do it in as detailed or simple a manner as you'd like.

On episode 99 of the Partial Credit Podcast, Jesse Lubinsky shared that he asked for a definition of "faith" in terms a child would understand. That helped me realize that it can give definitions, descriptions, and explanations -- we expected that -- or it can level them up or down in complexity however we ask.

5. Ask it for feedback for student work.

We know that one key aspect to effective feedback is that it's timely. With traditional paper-based work, students turn it in and must wait for teachers to grade it -- and return it! -- before they can see feedback. Lots of edtech tools are letting us get feedback to students more quickly -- whether automated or through direct communication with a teacher or classmate.

ChatGPT (or a similar tool) can be another source of feedback. When students finish a written work, they can copy/paste their work into ChatGPT and ask how they can improve their writing. For example, I copied one of my blog posts into ChatGPT and simply asked how I could improve it. It gave me a list of five suggestions, including transitional phrases, adding more examples, and breaking it up into shorter paragraphs. (Better start a new paragraph now ...)

Of course, it's up to the student -- and based on what the student has learned about writing -- to decide whether to implement the advice and how.

6. Ask it to do some teacher tasks for you.

Ask ChatGPT (or a similar tool) to write some lesson plans for you. Or some questions for a quiz. Ask it for some jokes about your content so you can slip those into class. Of course, you don't have to use everything that it provides you verbatim. But it might give you a starting point you can modify -- or if you already have something, it can give you ideas to improve.

7. Add it to the "think pair share" thinking routine.

Augmenting the think-pair-share with ChatGPT could be one of the biggest tech-enabled leaps in pedagogy:
* Think
* Pair
* ChatGPT
* Pair
* Share
- Sarah Dillard (@dillardsarah) December 5, 2022

I love this line of thinking from Sarah Dillard (Twitter: @dillardsarah), and if you click on it and look at the whole thread, she explains it more. Students think about a prompt, then discuss it with a classmate. Then they do any searches they want on ChatGPT. They pair back up to discuss what they've found. Then they share with the class.

Using ChatGPT and AI doesn't have to be THE way we teach certain things, but it can add important steps to existing frameworks.

8. Grade the bot.

Jen Giffen (Twitter: @virtualgiff) talked with her high school-aged students about the use of AI and tools like ChatGPT. (We talked on the phone. You'll see that the phone call sparked lots of ideas!) After that conversation, she suggested this idea:

Give a writing prompt to ChatGPT (or a similar tool). It could be a different writing prompt than you'll give your students. Read the essay that the bot creates for you.

Then, give the students the rubric you'll use to grade them and ask them to grade the response from the artificial intelligence.

This helps students to be reflective about the grading process -- and about their own writing process. When students get grades on their own work, it's easy to take it personally -- or to dismiss it because it makes them feel like they've messed up a lot. But when they critique the work of a bot that doesn't have feelings, it eliminates a lot of those emotions.

9. Debate the bot.

This came from that conversation with Jen, too, and she said she's seen this one shared on social media a lot.

Let students (as individuals, in pairs or small groups, or even as a whole-group activity) debate ChatGPT (or a similar tool).

Students take one side of a debate. The AI takes the other. Students plug their points in and ask the bot to rebut.

It gives them low-stakes practice -- and as much practice as they want -- to hone their debate skills. Plus, they may see talking points for their own stance (or that their opponent may use) so they can strengthen their argument.

10. Ask the bot for advice.

One more takeaway from this conversation with Jen! (Although several of the ideas below were sparked during that conversation ... so, you know, credit where credit is due.)

Jen asked ChatGPT very generally, "Give me some advice." It gave her some general (yet very good) ideas on managing stress and relationships and mental wellbeing.

A bot can't be a replacement for counseling or medical help. But we do take advice from friends, family ... even strangers sometimes. If students are struggling with just about anything, they can get advice from this artificial intelligence -- an AI that's working with much of the entirety of the internet as its dataset.

11. Use it to summarize texts.

If a text that your students are reading is in the dataset of ChatGPT (or a similar tool), they could always try to ask it for a summary of the whole thing -- or of certain chapters, sections, acts, scenes, etc. This is what we used SparkNotes and Cliff's Notes for years ago. Of course, SparkNotes and Cliff's Notes were controversial in the past -- "if they read those, they'll never read the text!" -- but eventually we found ways that they could support learning, too.

Seeing a summary of a text that you've just read can help you process what you've read. It's similar in nature to a book club. You hear what other people think and observe about the text and it helps inform your view of it.

This could also be a helpful strategy for reviewing before a quiz or a test.

12. Use it for insight into big, difficult-to-solve problems.

Before you read this one, just remember ... I taught high school Spanish for 10+ years. I'm not a math or science teacher, and I kind of struggled with those during school. That said ...

If you -- or your students -- come up with a math or science problem bigger than you know how to solve (or don't want to take the time to solve), ask ChatGPT (or a similar tool).

If it can solve it, it'll show you an answer. But, more importantly, you'll gain some insight into the process of solving it. And even if it can't solve it, it'll tell you why.

You could also ask it bigger societal questions to see what it would say. I asked it how to solve world hunger, and here's what I got:

Eliminating world hunger is a complex and multifaceted challenge that requires the efforts of governments, international organizations, and individuals around the world. Some strategies that have been proposed to address this issue include:

1. Increasing agricultural productivity: This can be done through the use of advanced technologies such as precision farming and genetically modified crops, as well as by improving infrastructure and access to education and training for farmers.

2. Reducing food waste: Up to one-third of all food produced in the world is lost or wasted, which represents a significant opportunity to increase food availability. Reducing food waste can be achieved through better storage and transportation systems, as well as by increasing awareness about the issue.

3. Improving distribution systems: In many cases, food is available, but it is not distributed effectively to those who need it most. Improving distribution systems, including supply chains and transportation networks, can help get food to the people who need it.

4. Promoting economic development: Economic growth can lead to increased food production and greater access to food, as well as the resources and infrastructure needed to address food insecurity.

5. Providing emergency food aid: In times of crisis, such as during natural disasters or armed conflict, providing emergency food aid can help prevent starvation and malnutrition.

Ultimately, addressing world hunger will require a combination of these and other approaches, as well as strong political will and sustained commitment from governments and other organizations.
Source: ChatGPT via chat.openai.com (2022)

14. Anticipate the response you'd expect from AI.

If your students have been studying a topic, this could be a great retrieval / brain dump activity -- and a way of ranking the importance of all the things they've learned about the topic.

Tell them that you're going to ask ChatGPT (or a similar tool) to summarize what they've been studying. Ask them what they think the bot will say. It'll prompt them to recall knowledge from their memory (which strengthens long-term memory). Plus, when they rank them in importance (because the bot won't list everything it knows), they'll have to give a justification.

All of this leads to deeper understanding of the material -- and strengthened long-term memory.

15. Take several responses and make a better product.

ChatGPT often has a button at the bottom of a response that says "regenerate response." That's because each time you ask it a question, it generates something original, doing the work from scratch every time.

If you were asked to pick a movie as your favorite, describe it, and tell why you like it in 60 seconds, your response each time would be a little different. (For me, the movie would probably be different every time!) It's an original, unique work each time. ChatGPT works kind of like that every time.

Ask it to answer a question or write something for you. Then ask it again ... and again ... and again. Get five (or more!) versions of the same prompt.

Have students (individually, in pairs/small groups, or even ask a class) take the best parts from those versions and turn it into a better final product.

This can be a scaffolding strategy for students who struggle to write essays or papers. It introduces them to some of the strategy of crafting a written work without all of the taxing effort of doing the whole thing.

16. Create personalized learning experiences.
Response from ChatGPT to "How can AI be used to help teach in the classroom?" AI can be used to create personalized learning experiences for students by adapting the content and pace of instruction to each student's needs and abilities. This can be achieved through the use of adaptive learning software, which adjusts the material based on the student's performance.
Source: ChatGPT via chat.openai.com (2022)

17. Provide tutoring or coaching.
Response from ChatGPT to "How can AI be used to help teach in the classroom?" AI can be used to provide one-on-one tutoring or coaching to students, either in person or remotely. This can be particularly useful for students who may not have access to human tutors, or for subjects that are difficult to teach in a traditional classroom setting.
Source: ChatGPT via chat.openai.com (2022)

18. Generate prompts and questions to facilitate discussions.
Response from ChatGPT to "How can you (ChatGPT) be used to help teach in the classroom?" I can be used to facilitate discussions among students by posing questions and prompts that encourage critical thinking and encourage students to engage with the material in a deeper way.
Source: ChatGPT via chat.openai.com (2022)

19. Provide information and answer questions.
Response from ChatGPT to "How can you (ChatGPT) be used to help teach in the classroom?" I can be used to provide students with information on a wide range of topics, and to answer their questions on those topics. This can be particularly useful for subjects that may be difficult to understand or that require a lot of background knowledge.
Source: ChatGPT via chat.openai.com (2022)

20. Supplement in-person instruction.
Response from ChatGPT to "How can you (ChatGPT) be used to help teach in the classroom?" I can be used to supplement in-person instruction by providing additional resources and materials for students to explore on their own, or by offering additional support and assistance outside of the classroom.
Source: ChatGPT via chat.openai.com (2022)

Should we block it or try to ban it?

If we block ChatGPT (or tools like it) and think we're solving a problem, we're deluding ourselves.

There are two decisions that need to be addressed since ChatGPT was released.

A big, systemic decision that needs to be made is: What will teaching and learning look like with ChatGPT and AI in existence?

We've started unpacking that above (and in conversations all over the globe).

But there's a more pressing question, and it's one that requires a bit of nuance ...

Do we block it at school?

Immediately, schools and districts must decide whether to block access to it on school networks and devices.

That decision, however, won't solve "the problem." (I use quotes because I'm not convinced that the proliferation of AI is a problem. It really does disrupt how we have done -- and are doing -- school, though.)

Students still will have access to it. It's like social media. It can be blocked at school. But students can access it (as I mentioned above) on their phones under a desk, in the restroom, on a bus, at home ... anywhere. They'll get access.

But someone has to decide. Should it be blocked at school?

What educators in my social media circles are saying ...
The resounding answer has been, "No, don't block it."
Their rationale: This is the future. It's not going anywhere. Students must have access to it. It'll prepare them for the future. Why would we want to keep students from accessing something so powerful?

There's something to know about these social media circles, though. Lots of people in them aren't in the classroom and don't have a good perspective on what full-time teachers go through.
(Full disclosure: I don't teach full time anymore either. I'm in my wife's and kids' schools a lot, but I don't teach full time.)
The ones in these social media circles that are in the classroom? They're dreamers (like me). They've seen the ways the system is broken. They're ready for change.

In the end -- if we're playing the long game (and I think we are), I side with them.

Generally.

What regular teachers in regular classrooms are saying ...
If you walk into any given classroom in schools across the United States (and some parts of the world)? The resounding answer has been, "Please block it. Right now!"
These are the teachers who write lesson plans. Every single day.

They grade student work. Every single day.

They teach and supervise and facilitate class. Every single day.

They never have enough time to do what they need. Their checklist is never complete.

There's a level of survival in these classrooms.

Reinventing their teaching methods and assignments at the drop of a hat because a new AI bot came out?

They just don't have time for that. (And they don't have the capacity in their already fractured personal wellness to do that.)

I understand.

I think, deep down inside, these teachers know the potential of AI and tools like ChatGPT. They know that it's going to change how teaching and learning looks.

They just need to survive the day. The week.

They need to survive until break.

They're on the front lines, dealing with all sorts of difficult situations and a lack of resources and a lack of respect for the classroom and the teaching profession.

They also just did this. Do you remember? (If you don't, you probably haven't taught in a classroom for a few years.)

Teachers are just starting to feel a sense of normality after pandemic-induced remote teaching. They had to reinvent the way they teach -- immediately! -- to a remote format, one that most weren't prepared for, technologically or pedagogically or logistically.

As teacher wellness expert Mandy Froehlich (Twitter: @froehlichm) said, they're trying to get out of emergency mode. And when you finally get out of emergency mode, there's a let-down ... an emotional, sometimes physical, response to the trauma you've dealt with.

So to those that look down their noses at teachers who are begging for this to be blocked, let's just remember the recent past. And let's also remember that they likely understand the impact of this.

They just want to survive the week. Survive until break.

Survive until we get a spare moment to think about this. Learn about it. Brainstorm some ways to change our assignments so that they can't

A proposal for schools/districts that's a middle ground

(Hear my justification for this proposal in the video) Let's block it until the end of the school year.
Let's not make a long-term decision to block ChatGPT (and tools like it) forever.

Let's also not make a long-term decision to leave it open forever.

(I'm not totally confident that this is the right answer. But I haven't heard anyone argue for the middle ground yet, so I want to add this voice.)

Let's agree to block it on student devices and networks (and allow it on teachers devices/networks if possible) just until the end of the school year.

To look at their assignments and consider how they'd like to change them in light of this new technology.

To look at how they teach and how this might be incorporated in it.

To look at how technology like this might augment classroom discussions

Here's why ...

Teachers need some time to regroup ...

... and on and on.

We need some space. Some time. A little room to ponder, to sit with all of this. To talk to other educators about what they think. To talk to students and to parents.

Let's just give teachers a little space.

However, let's also make a few things clear.

1. This isn't the long-term answer. This is a stopgap to help struggling teachers to survive this sudden change.

2. Students still will have access to this. Just because we block this on student networks and devices doesn't mean they won't plug your writing prompts and questions into this technology. This just buys you a little time to finish the year with your traditional assignment types to come up with something new.

A faculty-wide discussion and brainstorming session about best ways to teach and learn is in order at the end of the year. Everyone shares their best ideas and prepares for their implementation. (And let's pay the teachers for this extra meeting, OK?)
1. Will this technology be blocked on school networks and devices? 2. How will we evolve our teaching practice now that these technologies exist?
Then, at the beginning of next school year, let's open the ChatGPT floodgates.

Even if this isn't the solution you (or your school/district) comes to, there are two decisions that need to be made:

Blocking ChatGPT district-wide is one decision.

Deciding how teaching/learning happen while it exists is another. (to me)

If a district thinks blocking it will solve the problem, they're deluding themselves.

Blocking it can be one part of a solution, I believe. https://t.co/CvHCT2RqSQ
- Matt Miller (@jmattmiller) December 14, 2022

What other resources can help me learn about this?

Below is a list (albeit incomplete!) of resources I've found in the weeks after ChatGPT came into existence. I'll share links along with why I like them as resources. Please add other resources -- even your own! -- in the comments below!

ChatGPT in Classrooms: What to Know (U.S. News and World Report) -- Students, teachers and others in education weigh in on this new AI tool and the implications it has in the classroom.

What can English teachers do about ChatGPT (Learning in Room 213) -- This post explores what ChatGPT is, the problems with blocking it, and suggestions: entice personal engagement, avoid formulaic assignments, build critical thinking, etc.

No, Artificial Intelligence Won't Destroy High School English (or Any Other Subject) (John Spencer, Spencer Author) -- I've waited to read this because I wanted to create my own piece of content without copying anyone, but I've been excited to see John's thoughts on it. Hang on a second, let me read it ... Yep, it's as fantastic as I expected. Some of John's points include: "Almost any task can be automated, but what's the joy in that?"; "If we outsources every task, we might short-circuit the learning"; and "AI can't replace your voice." This is really, really good.

Human Skills in a World of Artificial Intelligence (John Spencer, Spencer Author) -- In this post (which dovetails wonderfully with the one above), John outlines the problems with a couple approaches to AI and advocates for another one: "the human approach."

The conversation about how much we care (Twitter thread by Evan Weinberg @emwdx) -- This thread doesn't seem to have gotten much attention, but I really like where Evan's going with it. He introduces it with: "As we see start to see how easy it is for a tool like #ChatGPT to generate text that sounds convincingly like us, it is starting the conversation about how much we care. We care a lot more than we might initially admit."

Ideas for using ChatGPT in the Classroom (IB English Guys) -- They opened up this collaborative Google Doc to share ideas. There are 10+ ideas with rationale and comments from educators.

AI Homework (Stratechery) -- This is an interesting, thoughtful, nuanced look at the intersection of homework and artificial intelligence. He talks about the struggles that ChatGPT has with math, and he even runs a virtual machine (like a Linux terminal) inside ChatGPT.

Yes, Teachers, You Should Be Panicking About AI (The Broken Copier) -- This post provides six reasons why we should be concerned about ChatGPT and AI (in light of the condition of education in many classrooms right now), helping us make sense of how we move forward.

The College Essay is Dead (The Atlantic) -- This was one of the first posts I saw (that was circulated widely) about the impact of ChatGPT in education. It's a paid article on The Atlantic. I subscribed so I could read it so that I could tell you ... it's talking points and not much else. If you'd like to read commentary about it and you're a subscribers to The Atlantic, go for it. I wouldn't pay for it ... especially since I'm focused on what we can actually do with this technology.

No, ChatGPT is Not the End of High School English. But Here's the Useful Tool It Offers Teachers (Forbes) -- Here's the best point in this whole article (so you don't have to read it): ChatGPT is an excellent prompt tester. Think you've come up with a good writing prompt? Feed it to the chatbot. If it can come up with an essay that you would consider a good piece of work, then that prompt should be refined, reworked, or simply scrapped.

Learning More about Chat GPT in Education (Jennifer Casa-Todd) -- Jen has written books about social media, digital literacy, and technology's impact on children's lives. She shares some of the best things she's found about the topic.

Education is about to radically change: AI for the masses (Nate McClennen and Rachelle Dené Poth for Getting Smart) -- AI already does and will continue to impact education - along with every other sector. Innovative education leaders have an opportunity to build the foundation for the most personalized learning system we have ever seen.

Let's Chat: OpenAI and ChatGPT (THRIVEinEDU podcast by Rachelle Dené Poth) -- Have you tried OpenAI yet? What has your experience been? Rachelle shares some background info, insights, questions and more in this episode. She also shares at her blog: www.Rdene915.com.

Chatbots in Education: Middle School and High School (Heather Olvey and Terri Files) -- These teachers pulled together slide decks with ideas for implementing chatbots in the classroom.
Have a resource to add -- yours or from someone else? Share it in the comments below!

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ChatGPT, Chatbots and Artificial Intelligence in Education

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Now, we're wondering ... Calculators.Search engines.Google Translate.Wikipedia.PhotoMath.#ChatGPT. They disrupt traditional teaching. We adapt. Education evolves forward. Blocking them isn't the answer. Making education more relevant is.- Matt Miller (@jmattmiller) December 14, 2022 Jump straight to a section (click a button below): ⭐️ Add thoughts, ideas, resources in the comments at the bottom!