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Generative AI tools can reflect our failure of imagination and that is when the real learning starts

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Although there is a huge amount of interest in generative artificial intelligence (AI) in the consumer world, particularly since the release of OpenAI's free ChatGPT program last November, in the hallowed halls of academia the response has been more wary. Concerns abound about academic integrity. There are also worries about how AI-generated content can be biased, inaccurate, and sometimes contain entirely false information, dubbed "hallucinations."

The cautious response is to be expected according to Houman Harouni, lecturer on education at the Harvard Graduate School of Education and a former elementary and high school teacher. He has compassion for educators trying to grapple with a rapidly shifting world shaped by machine learning.

"Technology creates a shock," he explains. "This shock is sometimes of a magnitude that we cannot even understand it, in the same way that we still haven't absorbed the sharp shock of the mobile phone."

Harouni has long wrestled with the impact of cutting-edge technology on education, including experimenting in his own classroom, and is convinced that when it comes to teaching "the medium is part of the message." He believes that getting school students and those in higher ed to engage with virtual worlds is essential.

"Where we want to get to is a place where you're dancing with it, dancing with robots," he says.

If the idea of waltzing with a robot creates apprehension for educators, Harouni has some advice :
1) Stop pretending that it doesn't exist
Educators must "help the next generation face the reality of the world and develop instruments and ways of navigating this reality with integrity," Harouni says. Students are well aware that technologies such as ChatGPT exist and are already experimenting with them on their own, but they need guidance about how to use them responsibly.

Teacher education and professional development programs should not ignore generative artificial intelligence either.
2) Use AI alongside your students
Engage with generative AI tools with your students in person, when possible. Otherwise, share AI-generated responses to questions during class time and ask students to consider them or have students experiment with the technology at home, document their experiences, and share them with the class.
3) Teach students how to ask the ChatGPT tool questions
"The educator's job is to understand what opportunities are left open beside the technology," Harouni says.

Teach students to do what artificial intelligence cannot do. For example, unlike robots, we can ask ourselves questions and that is what students need to be trained in: to know how to ask questions and to learn how to critique their own questions, frameworks, and the answers generated by AI, he says.

Students can start with topics and questions that they are interested in and ask ChatGPT for answers, he suggests. The knack is then getting them excited about asking follow-up questions. Harouni uses a personal experience with his 10-year-old stepdaughter and his newborn baby to illustrate his point. When his stepdaughter asked him why he kept telling her to be careful with the baby, Harouni turned to ChatGPT to help her to get to the bottom of her question.

"My creativity as the teacher or the parent at that moment is to say, 'What is it that you're really trying to ask? What is it that you really want to know?'"

While ChatGPT churned out a "whole bunch of answers about the fragility of the baby," with some patience, Harouni helped his stepdaughter discover the question that she truly wanted to ask which was what she could safely do with the new baby. "At the moment that the exploration [with AI] ends with the answer, you know that your work as a teacher begins," he explains.
4) Use generative AI tools to spark the imagination
One frequent concern about generative artificial intelligence is that students will use it to cheat and avoid the hard work of thinking for themselves, but Harouni says that tools like ChatGPT should really challenge teachers and professors to reassess the assignments they give their students.

"You have to stop thinking that you can teach exactly the way you used to teach when the basic medium has changed," he explains. If students can turn to ChatGPT or other AI language models for quick and easy answers then there is a problem with the lesson, Harouni believes.

"We have to create assignments that push [students] to the point where they have to question what is the framework that is being used here and what would it mean for me to radically change this framework," he says.

Harouni recently wrote about how he used ChatGPT to spur higher-level thinking among his students at HGSE when he presented them with a challenging case study that had no easy solutions. The students' initial responses were no better than the chatbot's ideas. Instead "it was after ChatGPT reflected to the students their failure of imagination that they could begin to think of options that they, or any automatic language scrawler, would not have readily reached for," he explained in a co-authored article for Wired.

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Embracing Artificial Intelligence in the Classroom

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Generative AI tools can reflect our failure of imagination and that is when the real learning starts

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AI Bias: National Institute of Standards and Technology

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AI Bias: National Institute of Standards and Technology

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Rooting out bias in artificial intelligence will require addressing human and systemic biases as well.

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As a step toward improving our ability to identify and manage the harmful effects of bias in artificial intelligence (AI) systems, researchers at the National Institute of Standards and Technology (NIST) recommend widening the scope of where we look for the source of these biases - beyond the machine learning processes and data used to train AI software to the broader societal factors that influence how technology is developed.

The recommendation is a core message of a revised NIST publication, Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (NIST Special Publication 1270), which reflects public comments the agency received on its draft version released last summer. As part of a larger effort to support the development of trustworthy and responsible AI, the document offers guidance connected to the AI Risk Management Framework that NIST is developing.

According to NIST's Reva Schwartz, the main distinction between the draft and final versions of the publication is the new emphasis on how bias manifests itself not only in AI algorithms and the data used to train them, but also in the societal context in which AI systems are used.

"Context is everything," said Schwartz, principal investigator for AI bias and one of the report's authors. "AI systems do not operate in isolation. They help people make decisions that directly affect other people's lives. If we are to develop trustworthy AI systems, we need to consider all the factors that can chip away at the public's trust in AI. Many of these factors go beyond the technology itself to the impacts of the technology, and the comments we received from a wide range of people and organizations emphasized this point."

Bias in AI can harm humans. AI can make decisions that affect whether a person is admitted into a school, authorized for a bank loan or accepted as a rental applicant. It is relatively common knowledge that AI systems can exhibit biases that stem from their programming and data sources; for example, machine learning software could be trained on a dataset that underrepresents a particular gender or ethnic group. The revised NIST publication acknowledges that while these computational and statistical sources of bias remain highly important, they do not represent the full picture.

A more complete understanding of bias must take into account human and systemic biases, which figure significantly in the new version. Systemic biases result from institutions operating in ways that disadvantage certain social groups, such as discriminating against individuals based on their race. Human biases can relate to how people use data to fill in missing information, such as a person's neighborhood of residence influencing how likely authorities would consider the person to be a crime suspect. When human, systemic and computational biases combine, they can form a pernicious mixture - especially when explicit guidance is lacking for addressing the risks associated with using AI systems.

"If we are to develop trustworthy AI systems, we need to consider all the factors that can chip away at the public's trust in AI. Many of these factors go beyond the technology itself to the impacts of the technology." -Reva Schwartz, principal investigator for AI bias

To address these issues, the NIST authors make the case for a "socio-technical" approach to mitigating bias in AI. This approach involves a recognition that AI operates in a larger social context - and that purely technically based efforts to solve the problem of bias will come up short.

"Organizations often default to overly technical solutions for AI bias issues," Schwartz said. "But these approaches do not adequately capture the societal impact of AI systems. The expansion of AI into many aspects of public life requires extending our view to consider AI within the larger social system in which it operates."

Socio-technical approaches in AI are an emerging area, Schwartz said, and identifying measurement techniques to take these factors into consideration will require a broad set of disciplines and stakeholders.

"It's important to bring in experts from various fields - not just engineering - and to listen to other organizations and communities about the impact of AI," she said.

NIST is planning a series of public workshops over the next few months aimed at drafting a technical report for addressing AI bias and connecting the report with the AI Risk Management Framework. For more information and to register, visit the AI RMF workshop page.

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There's More to AI Bias Than Biased Data, NIST Report Highlights

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As a step toward improving our ability to identify and manage the harmful effects of bias in artificial intelligence (AI) systems, researchers at the National Institute of Standards and Technology (NIST) recommend widening the scope of where we look for the source of these biases - beyond the machine learning processes and data used to train AI software to the broader societal factors that influence how technology is developed.

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Stanford: AI Tools in Teaching and Learning

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Stanford: AI Tools in Teaching and Learning

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This article offers some guidance as we begin to more deeply understand and engage with AI tools in our teaching and learning practices.

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Natural language AI chatbots such as ChatGPT use vast amounts of text data to predict words or phrases in a given context. They can be used to mimic natural human language and to aid a wide variety of language-related tasks in much more sophisticated ways than previously possible.

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Eliminating AI bias requires drilling down into datasets, machine learning algorithms and other elements of AI systems to identify sources of potential bias.

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Experience an integrated media property for tech workers—latest news, explainers and market insights to help stay ahead of the curve.

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AI tools that educators can use to save time, from award-winning educator Lance Key

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AI tools can make teachers' lives easier and help them teach more efficiently, says Lance Key.

"We're just scratching the surface right now with what we're going to be able to do with AI," he says. "If we do it right, we'll be able to help kids, and they'll be able to have opportunities that they didn't have in the past."

Key is an award-winning educator and support specialist at the Putnam County School System in Cookeville, Tennessee. He focuses on helping teachers incorporate technology into their classrooms and has delivered more than 400 professional development presentations across the country.

He sees educators using more and more AI (artificial intelligence) tools for teaching, and recommends a few to consider. He excludes the hyper-popular ChatGPT from the conversation because we've got a feeling you may have already heard about that one.

"MagicSchool AI is really a great resource to help teachers prepare to teach," Key says. The AI-powered tool is designed to save teachers time and help prevent teacher burnout by assisting them as they differentiate, write assessments, write IEPS, communicate, and more.

"If I need a lesson plan written, it will write out a detailed lesson plan for me," Key says.

This tool from Meta AI Research allows people to create a drawing, upload an image of that drawing, and then have that image come to life in animation. Key says this is a favorite new tool of his and there is tons of potential for it in the classroom as what child wouldn't want to see their drawing animated.

"Canva now has AI built into it," Key says. "I can go to Canva and I can tell it to build me a presentation about digital citizenship, and it will build me a slideshow presentation." The Canva AI tool won't do all the work. "I'm gonna have to go edit and fix a few things on it," Key says, however, it can provide a solid foundation to build on for many presentations. It also has a tool called Magic Write, which will write first drafts of emails, captions, or other posts for teachers.

Another good platform for creating first drafts of presentations is Curipod, Key says. "It is like a Nearpod or like a Pear Deck, and it's got a feature in it that you give it your topic and it will build out that presentation," Key says. The tool is geared toward education and lets you choose the grade levels for your presentation. However, it is limited to five presentations per starter account at one time.

A third tool Key recommends for creating presentations is SlidesGPT. Though he noted it is not quite as fast as some of the other options, it is very thorough in its slideshow creation skills. In our recent review, we found that it was impressive overall, except the platform suffered from some of the inaccuracies and mistakes we've come to expect from AI-generated content at this stage.

This is an AI test and quiz builder that can integrate with some learning management systems, allowing teachers to create quizzes on command. "You can say, 'I want a five-question quiz about the harmful use of tobacco' and it will build you out a five-question quiz that you can import straight into Google Classroom."

This is a visual whiteboard that works with ViewSonic and is one that Key regularly uses. "A teacher can draw a picture on her board, and then it gives her images to select from," he says. ESL teachers who Key works with have been particularly drawn to it. "It's been really neat because they've been working with our students on image and word recognition," he says. "So they could draw a picture in there and have the kids try to guess what it is. We have a lot of fun with that."

Runway is an image and movie generator that can quickly be used to create engaging videos with impressive green screen and other special effects. It's designed for teachers looking to make more engaging content for their students, and one that Key' and his colleagues frequently use.

Adobe Firefly is an AI image generator that also allows users to edit the image. "Adobe can make fliers and things for you just by typing in what you're looking for," he says. This can cut down on presentation or other types of teacher prep, but it can also be a fun tool to explore with students.

Another tool Key recommends is TeachMateAi, which provides educators with a suite of AI-powered tools that generate various teaching resources. It is designed to make teaching prep and other administrative tasks associated with the job easier, so teachers can focus on time with students.
To share your feedback and ideas on this article, consider joining our Tech & Learning online community

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12 AI Tools Beyond ChatGPT That Can Save Teachers Time

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AI tools that educators can use to save time, from award-winning educator Lance Key

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Chatbots in 2023: Benefits, Applications & Best Practices

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Around 80% of business executives want to change the way they deal with customer relations by adopting chatbots. In this article, we offer a complete guide regarding chatbots to help executives to better understand:

Definition of chatbots.

Importance and benefits of chatbots.

Their main application areas.

Challenges you may face.

Best practices to overcome challenges and more.

What is a chatbot?

A chatbot is a computer program that enables people to get information from machines in a natural, conversational, way using text and voice

There are two major channels in which chatbots are implemented. One of them is text-based channels, such as Whatsapp, Messenger, Slack, and Telegram. The other channel is voice-based virtual assistants such as Alexa, Siri, and Cortana.

Feel free to check our list of top 20 use areas of chatbots.

Chatbots will bring more savings and efficiency

Chatbots provide savings thanks to automation that reach up to 60% for some industries. One of the best ways for reducing cost by using chatbots is deploying them for answering frequently asked questions by the clients. By doing so you can automate over 70% of your call service workload and augment your employees.

Chatbots solve important customer problems

According to McKinsey, for customers, the most crucial factors for successful customer engagement are reaching the desired outcome, speed, and ease of experience.

Chatbots offer a lot for businesses in this perspective because:

They can work 7/24.

They can perform multiple tasks.

They can serve in many languages.

They are deployed on digital platforms like custom mobile apps which provide easy access for customers.

Messaging apps are the right medium to implement chatbots

The widespread availability of messaging apps makes it a great target for potential expansion. Latest figures for monthly active users of messaging apps are over 5 billion. Platforms like Whatsapp, Facebook Messenger, WeChat, and Telegram have already made it possible to implement chatbots.

This makes reaching out to, and communicating with, customers on multiple platforms a reality. Think about salespersons for instance: they can only communicate with one-person at a time. Chatbots provide a huge scalability with a potential of communicating with millions of people at the same time all through messaging apps.

Chatbot use cases for your business

Chatbots have numerous possible benefits in diverse areas:

Marketing: Messaging has a larger social base than all other areas of social media. Brands have been experimenting heavily with chatbots since the launch of Facebook Messenger Platform and discovered numerous use cases engaging their customers daily. We compiled all chatbot applications brands can build.

Customer service: Customer service wages in the US is $100+ Billion p.a. Even small savings in wages can create massive benefits for B2C enterprises where customer reps spend a significant portion of their time answering simple questions.

Inside sales: Conversion rate is 10x more for leads that are contacted within 5 minutes according to an insidesales.com study. Achieving that with a human team takes a large team and low utilization. Bots can achieve such speeds at low cost.

Healthcare: Chatbots have significant potential in healthcare but regulatory challenges are likely to delay their adoption

Prescription reminders: Bots like Florence provide reminders for prescriptions set by patients. This could be quite a suitable service for hospitals or pharmacies.

Diagnostic-aid: Users tell Baidu Melody about their symptoms after which Melody asks several questions to produce a preliminary diagnostic.

Therapy: There are already numerous chatbot companies such as X2AI, Therachat or Woebot helping people manage their mental health.

To learn more about the various use cases of chatbots, click here.
Risks of launching your business' chatbot

Chatbots have significant potential but that does not make them easy to implement. We explained in our detailed blog post on chatbot failure how discoverability, customer expectations and technological limitations have limited traction for numerous bots. Unfortunately, customers are quite sensitive to chatbot failures. And, chatbots fail so frequently that we already have a section on chatbot failures.

Mitigate your chatbot's risks in 3 simple steps

For most large businesses, the benefits of launching your bot outweighs its risks, especially if best practices regarding chatbot development and testing are followed.

Most chatbots' dysfunctionalities can be avoided by following these 3 steps:

1. Extensive testing: There are so many bot testing tools that we have a dedicated article on chatbot testing frameworks and another on chatbot A/B testing.

2. A private beta release: Your team needs to eat its own dog food before the public has access to it.

3. Using a custom language matrix: Chatbot developers build a language corpus along with PR and marketing to ensure that bot's messages are consistent with company's messages. This ensures that the bot has a consistent personality and shares consistent messages. While restricting bots' conversational capabilities, this limitation provides peace of mind to executives in major corporations that are releasing their bots into the wild.

Turn your chatbot into a success with 3 tips

1. Make your chatbot easy to discover. You know the channels where your customers are reaching out to you. Your bot needs to be on the most popular channels: your website, Facebook page and so on.

2. Lower your customer's expectations as much as possible. Your chatbot won't be flawless from day one. So if you are in the early stages of adoption, make sure you let your customers know that the chatbot they're interacting with is still in its infancy and can make mistakes.

3. If your chatbot is designed to function like a menu, don't shy from adding buttons. No one likes to write 10 lines to trigger a simple transaction.

For more, discover how to build great chatbots in our detailed chatbot best practices article.

Should you implement a chatbot?

After analyzing the enhancements and advantages of chatbots, you should decide whether or not you really need to implement a chatbot.

The following checklist can help you realize whether implementation is right for you:

Decide on the value you are expected to gain by implementing a chatbot. The value proposition is a major factor in deciding on any project. So before this decision, performance metrics need to be defined and the cost of implementing the project and the benefit expected from the project should be included also.

The medium the chatbot implemented is another factor. Will it be voice-based or text-based? What would be the connection between the consumer and the bot? Those are some of the basic questions. Chatbot is expected to reflect the brand's personality, but will it be possible to construct that so as to continue seamless brand experience.

What is the available data? The decision will ultimately come down to deciding which resources to use and once the decision is made, it takes some time to train the chatbot. If there exists some data of the desired characteristics, initial stages may be completed more easily otherwise the process requires a brand new collection method, making the initial steps to last longer.

What is the future of chatbots?

Forrester research provides us a timeline of chatbot technology. Currently, we are still experiencing the initial stages. Therefore, any investment in a chatbot will likely generate a greater return thanks to first-mover's advantage. Compounding is still the keyword for early adaptation. The potential to fully personalize the experience still requires some time, but we are likely to reach that point in 5 years.

Another future development that holds promise is chatbots interacting with one another. Like APIs, chatbots can request services from one another and communicate seamlessly, without even needing to expose formal APIs. Such fluid exchange between bots can enable a wide range of services.

For example a Google for chatbots with advanced natural language understanding skills can not only answer any question, it can also complete any transaction given that you have the means to complete it. While a pure web based meta service like Google can return information, it can not do anything on your behalf on other websites unless they have an API integration. However, a chatbot programmer only needs to make his bot better understand natural language and that bot will be able to serve both humans and bots effectively.

How to learn more?

Hope you are more clear about what chatbots are and their promise. You can choose your area of interest to learn more:

Are you looking for a conversational AI vendor? Let us know:

Find the Right Vendors

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Chatbots in 2023: Benefits, Applications & Best Practices

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Explore what chatbots/conversational bots are, their benefits, use cases, & how you could start building one today to transform your business.

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Published November of 2020!!!!!!! How did I miss this boat??

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Nowadays, Artificial Intelligence (AI) is a widely discussed subject in the circles of business at all levels. The majority of business experts and analysts claim that AI is our future. However, if we think carefully, AI is not the future - AI is the present! Let's take your email service as an example. It uses AI to sort emails for you not to get spam. Amazon and other e-commerce platforms use AI to recommend goods to the customers taking the information that has been collected. Siri, Alexa, and Google Assistant turn to AI to enhance their user's experience. Although technology is in the basic stage of its development, many companies already invest huge budgets in AI, assuming that AI-powered products have a very promising future.

One of the fields that AI could transform entirely in the nearest future is Learning (Training) and Development (L&D). But, before we talk about the ways AI will transform the Learning and Development sector, we should discuss the part AI takes in Learning and Development.

Why is Artificial Intelligence Important to Learning & Development?

Learning and Development specialists should be aware of rapidly developing technology and use it to enhance the learning processes. In terms of AI, L&D experts should explore and implement AI improvements to develop new training strategies and techniques. Leading research and advisory company Gartner predicted that by the end of 2020 about 85% of customer services would be performed by machines (bots), not humans. One more report claimed that about 20% of the training materials would be produced by AI. Moreover, the Bank of America stated that by 2025 AI would be the reason for $14-33 trillion industrial expansion annually.

Thus, AI will have a great influence on the L&D sector. L&D specialists need to track huge amounts of information using AI software and machine learning. This information will give L&D experts insights that will help them develop new training programs for effective learning.

7 Ways how AI is transforming Learning and Development

The most important way AI will change the training, learning, and development sector is to help organizers establish more optimized and effective training methods and techniques. So, here we propose 7 ways how AI is about to transform L&D:

Personalizing the learning pathways

Every person has a different style of how he/she learns and processes new information. That's why the schooling process would be more effective if these preferences were taken into consideration. AI allows training programs to adapt to the needs of each employee. The benefits of adopting AI in Personalized Learning are:

Time is saved. Employees achieve their learning goals faster as they get information based on their personal preferences and objectives.

Engagement is encouraged. Learning system powered with AI analyses each learner and proposes a learning program based on his/her past performance and objectives.

The learning process is automated. With AI, you can build a learning platform where all data, programs, materials, schedules based on individual learner's experience, preferences, and objectives are stored, tracked, and delivered.

ROI is growing. The formula is simple: faster learning, paired with greater engagement leads to better learning results. Better learning results lead to a positive return on a company's learning investment.

Integrating training into the routine workflow

Stephen Walsh, a co-founder of Andres Pink, states that 93% of organizations wish to integrate learning into the routine workflow. However, 56% of learning is very formal and delivered face-to-face. Most of the learners are not satisfied either with the schedule of training or the format of information delivery. A learning system, powered with artificial intelligence is the solution to this problem as well and the benefits are simply the same: time is saved, employees are engaged and involved, the learning process is automated and the profit of the organization grows at the speed of light! When powered with AI, the learning system will provide a program, materials, and schedules that are personally developed for each employee.

Reinforcing training and development

Reinforcement is a process used to make learning valuable and remind the learners to apply meaningful knowledge in practice. It's no secret that employees are too busy and sometimes lazy to work on their development. Bryan Austin in his "Modern Corporate Learner" paper, claims that specialists are eager to dedicate only 1% of their precious time to learning and professional development. And the MASIECenter, an international learning LAB, states that employees finish only 15% of the learning programs that were assigned to them. Despite this fact, organizations spend billions of dollars on employee development programs annually. AI-equipped learning programs are called to solve the problem with poor reinforcement of training and development and can improve your reinforcement program, including:

automation of all the processes that save time;

personalizing the learning and reinforcement processes that boost engagement;

personalizing the learning and reinforcement processes, that improves completion rates;

automation of analytics that measures learning effectiveness and others.

Improving completion rates

As mentioned above, today only 15% of employees are ready to complete their learning programs. However, with Artificial intelligence delivering training content in the learner's preferred learning format that is followed up with reinforcing stimulating methods, completion rates will improve. Here are 4 tips on how to improve completion rates using AI:

develop a learning program based on the personal preferences of each employee;

make the course short and engaging;

turn to professionals to create a learning platform where all the processes will be automated;

once you measure learning effectiveness, do not forget to report on the results or even reward your employees.

Providing accessibility

AI products make training programs reachable to a wide group of learners, including people with different types of disabilities. For example, Google presented an Automatic Captions Video App in 2009, which could help deaf people. Besides, the App is equipped with auto-translation functionality that helps people enjoy watching videos in more than 50 languages. For blind people, AI delivers programs and solutions that create alternative texts for pictures and images. Google presented Cloud Vision API that utilizes neural networks to distinguish the context and create a textual version for an image. Thus, with AI, experts will develop training programs accessible to any learner.

Measuring learning and training effectiveness

Averaging the learning process performance is very crucial, but time-consuming. Once L&D professionals use AI systems they collect and analyze data quickly to get certain insights on learning effectiveness. The insights point out learner's progress and emphasize learner's knowledge gaps, if any. Then an AI-equipped learning program suggests ways to fulfill the uncovered gaps. With AI, a 4-level Kirkpatrick Evaluation Model will perform even more effectively to guarantee that the initial learning goals are accomplished.

Focusing on AI-based digital tutors

AI-based tutors can replace teachers, lecturers, speakers, and coaches. Sounds implausible? But it's true! Just a couple of years ago DARPA (Defence Approach Research Agency) sponsored a study that was called to develop a digital tutor to copy the interplay between an experienced specialist and a learner. The aim was to diminish the time spent by navy trainees to achieve some high-tech skills. The experiment revealed that when working with AI-based digital tutors, trainees not only obtained the skills quickly but also overperformed experienced experts. It means that potentially AI-based tutors could replace existing experts with time, and the learning process will be even more effective.

Bottom Line

Ultimately, applying AI in training, learning and development will allow learners to receive training content based on their preferences, skills, and personal traits. Moreover, AI makes programs accessible to all learners even with different types of disabilities. If personalized, AI-powered learning courses will significantly improve completion rates and boost engagement. In addition to that, a learning platform driven by artificial intelligence enables organizers to offer training options for the employees 24/7, track results, analyze data, measure learning effectiveness, and make learning even more effective and efficient.
Summary:
How do we use AI in everyday life?

Artificial intelligence or AI is a branch of computer science that brings together multiple disciplines, with the aim of creating smart machines - devices and systems capable of performing complex tasks that often require human intelligence, but in a manner that equals or exceeds the capabilities of humans. Uses: Virtual Assistants or Chatbots. Agriculture and Farming. Autonomous Vehicles and Aircraft. Online Commerce (eCommerce) and Shopping. Security and Surveillance. Manufacturing and Production. Healthcare and Medical Imaging Analysi. Health and Safety.
Summary:
AI in Training, Learning, and Development

Learning and Development specialists should be aware of rapidly developing technology and use it to enhance the learning processes. In terms of AI, L&D experts should explore and implement AI improvements to develop new training strategies and techniques. 7 Ways how AI is transforming Learning and Development: Personalizing the learning pathways. Integrating training into the routine workflow. Reinforcing training and development. Improving completion rates. Providing accessibility. Measuring learning and training effectiveness. Focusing on AI-based digital tutors.

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7 Ways AI is Transforming Learning and Development

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Artificial Intelligence in learning and development (L&D) is very powerful, making the process easier and more effective for everyone

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With the rise of generative artificial intelligence, students need to develop new skills—and educators need to embrace new ways of teaching.

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Because artificial intelligence will likely become the primary way humans access information, professors must prepare students to use the technology effectively in their lives and careers.

Students will especially need to learn skills related to effective prompt engineering, which refers to the ability to craft questions that elicit the most useful answers from AI platforms.

The more comfortable that faculty become with using AI, the better they will be at teaching students how to use this skill ethically and effectively in the years to come.

While ChatGPT has only recently captured public attention, artificial intelligence (AI) is not new. Some form of the technology has been around since the mid-20th century. However, the fact that AI is now being used for more applications and is more accessible to the general public has changed the conversation, as we realize that the technology will have a significant impact on 80 percent of jobs -including teaching.

Indeed, in the very near future, AI models will likely be the primary way we access knowledge-and higher education institutions will be where many people learn to use the technology effectively. This new reality makes it clear that it's time for educators to master a new skill set relevant to AI and to teach those skills to their students.

Model the Technology

Although many learners are experimenting with AI models such as ChatGPT, the first place most learners should learn how to use AI effectively is in the classroom. But this will happen only if schools have introduced relevant learning activities into their curricula and have linked those activities to appropriate learning objectives.

However, because many faculty are not comfortable using AI, they will need to learn how to integrate the technology into their classrooms. Schools can start by showing students and faculty how AI can be viewed as an ally, rather than an enemy. To convey this message, schools can take several steps to expose students and staff to the technology:

Create seminars to train faculty in how to introduce use cases of AI and how to emphasize the benefits and limitations of this technology.

Use learning experience platforms (LXPs) that leverage adaptive learning and AI processes that allow faculty to detect when students are having difficulty with the material and to customize their courses. Faculty can use feedback from an LXP to help students gain a deeper understanding of their weaknesses and enhance academic outcomes.

Use robotic process automation (RPA) systems to automate repetitive tasks, such as the students' submission of assignments to correctors. Such automation frees up faculty's time so they can concentrate on their primary missions.

Delegate to AI other routine administrative tasks, such as accepting admissions forms and generating emails and automatic replies, allowing staff more time to offer individualized support to learners.

Perfect the Art of 'Prompt Engineering'

Once faculty are comfortable with the technology, the most critical competency they will need to teach is the art of prompt engineering -the skill of formulating questions in ways that elicit the most useful answers. Effective prompt engineering encompasses the following areas where both faculty and their students will need to refine their knowledge and abilities:

Large language models (LLMs). Understanding LLMs-the algorithms that lie behind the output of generative AI-is a vital component to harnessing the potential of and tailoring interactions with ChatGPT. Only through meticulous and unambiguous prompt construction can users elicit desired responses from the language model.

That makes it critical that faculty incorporate the use of platforms such as ChatGPT into their classrooms. Then, they can teach students how to steer ChatGPT's output toward their intended objectives. For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human. To do this, they must first understand how LLMs work.

Communication. Students might view effective communication as less important when they are inputting a prompt into ChatGPT than when they are interacting with their professors or peers. But providing clear and explicit instructions in an AI prompt is just as essential as providing clear instructions to colleagues-good communication helps users streamline their interactions with AI.

Faculty can help students learn how to refine their questions to achieve increasingly precise responses (known in research as an iterative approach). They will learn to establish context, define the task, and specify the desired outcome for the language model.

For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human.

The better students are at communicating with AI, the more likely it is that they will have seamless and rewarding learning experiences as they use AI to deepen their understanding of complex concepts, find solutions to problems, or explore new areas of knowledge.

Contextualization. When it comes to mastering prompt engineering, contextualization can be just as important as an iterative approach. With this skill, students will provide relevant factors and background information within the prompt to help the language model understand the specific context of each query. By setting the stage and giving necessary details, they increase the chance of receiving accurate and meaningful responses.

Role-playing. Here, students learn to assume different personas or perspectives in different prompts. This can help students obtain responses that align with specific viewpoints or generate creative outputs based on the chosen character.

Those who learn the skills listed above will become adept prompt engineers who will make the most of this technology in a variety of job roles and situations. They will be able to use AI effectively to streamline the problem-solving process, achieve a specific result, or improve their overall job performance. But faculty can set them up for success only by embracing ChatGPT and generative AI in the classroom, as pedagogical tools to help students exercise and expand their critical thinking abilities.

Disrupting Traditional Teaching Models

It's an understatement to say that AI technology is having a seismic effect on faculty. It clearly is disrupting traditional teaching methods and practices, so much so that many faculty initially reacted by banning its use in their classrooms. But just as ChatGPT offers students a new way of learning, it compels faculty to adopt a new way of teaching.

In fact, there is immense potential in utilizing ChatGPT as a practical learning tool to foster and enhance students' creativity and design thinking. If faculty incorporate relevant exercises into their courses, students can learn to use AI not only to write better questions and generate more innovative ideas, but also to discover the technology's limitations.

So, how should faculty embrace AI in their classrooms instead of banning its use? They can adopt evolved pedagogical models that use AI to develop skills in several areas:

Assessment. The rise of AI will inspire the revision and rethinking of teaching and assessment methods. Faculty can use AI platforms to diversify student assessments, including formative, normative, and ipsative evaluations. They can even use AI to assess the new set of skills related to AI itself. These skills include the development of analytical mindsets, familiarity with intelligent user interfaces, the ability to look beyond statistics to instead use predictive analytics, and an understanding of artificial neural networks.

However, while looking at students' final deliverables in a particular course still will be an important part of assessment, those deliverables will not be the only measure of student learning. The objective should shift from focusing on deliverables to evaluating the different stages of the learning process itself.

Faculty can use AI to streamline their own workloads, turning to ChatGPT to handle repetitive tasks while they concentrate on the most valuable aspects of teaching and learning

In other words, educators will need to do more than confirm that students solved a problem when they assess student learning. Educators also will need to ask students to explain how and why they solved a problem in a particular way. For example, faculty can ask learners to detail how they have used AI tools to create their deliverables-from case studies and analyses to full-length dissertations. Learners also could share whether they found the technology useful and how they adjusted to make AI work for them.

Critical thinking. Using AI as a complementary tool may improve students' learning process while challenging their critical thinking abilities. Encouraging human-machine collaboration reinforces a student's ability to adapt the technology to any environment or job role.

Adaptability. There is an urgent need to prepare the future users, designers, and shapers of these technologies to keep up with the pace of change. An essential part of teaching students to use AI is to introduce them to new platforms and functionalities as these innovations arise.

Better yet, faculty also can use AI to streamline their own workloads. They can turn to ChatGPT to handle the repetitive tasks. They can use the platform for help writing syllabi, for example, while they concentrate on the most valuable aspects of teaching and learning: adopting innovative pedagogy, nurturing creative thinking and problem-solving abilities, and ensuring that students develop essential future skills.

AI Is Here to Stay

It is inevitable that faculty increasingly will be working hand-in-hand with AI models to support their teaching. For that reason, higher education institutions must support faculty as they face this new challenge and do as much as possible to make that collaboration a success.

In essence, university faculty are, in a sense, gardeners who are nurturing two different seeds in fertile ground. On the one hand, they are developing AI-ready students; on the other, they are shaping the future use of AI technologies. Faculty might not be able to stop the AI trend from growing, but in this role, they can direct its growth by preparing students to use it as effectively and ethically as possible.

In the coming years, it will be interesting and enriching to observe how faculty teach AI models, as well as how students decide to use AI models to solve problems in the classroom. The technology might also help us address one of the more challenging aspects of teaching: how to engage students in their learning process.

Students will need to master the competencies we outline above if they are going to be able to work effectively with AI. In fact, we believe that as faculty and students experiment more with AI models, they will come to view the technology not as a threat, but as a teammate in their work.

The more schools enable faculty and students to strengthen their technological skills, the more they will support successful AI-human interactions. And the more they support these interactions, the faster we all will accelerate a shift in our mindset, from merely assessing AI's capabilities and implications to improving and refining the way we use it.

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How AI Is Reshaping Higher Education | AACSB

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With the rise of generative artificial intelligence, students need to develop new skills-and educators need to embrace new ways of teaching.

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Since the release of ChatGPT late last year, the essay has been declared dead as an effective way to measure learning.As educators have looked to alternatives to assigning essays, one idea that has bubbled up is to bring back oral exams.

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As AI Chatbots Rise, More Educators Look to Oral Exams - With High-Tech Twist - EdSurge News

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Since the release of ChatGPT late last year, the essay has been declared dead as an effective way to measure learning. After all, students can now ...

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How is AI currently utilized in higher education? As of fall 2023, we are still in the early stages of figuring out what AI integration means for higher ed. In some classrooms, such as my own, we talk about what AI can and can't do. We look at examples of output from large language models (LLMs) and critique how well it did with the responses. Next semester, my students will spend time working with prompt writing, reflecting on LLM output and reflecting on when knowledge and learning matter versus when human-AI hybrid writing makes sense. For many faculty, that last question is causing the most friction around campuses.

How the past influences the present

Instructors across the disciplines question how and where their students will use AI. Will students offload the conversion of knowledge into learning, or will students still be motivated to spend time struggling with concepts and gaining deep understanding of topics? While I see that as a valuable question, I also reflect on my own childhood. I grew up with card catalogs and encyclopedias. It was a big deal to have your own set of encyclopedias at home! We learned what we could from the books we had access to and memorized facts to regurgitate on tests. This was the epitome of knowledge and learning before the internet became widely available. Now, if my child asks me a question about anything, we can Google it on my phone from wherever we happen to be. Telling a student to go to the library to access a physical copy of something is the outlier instead of the norm.

Thinking about how information production and knowledge holding have shifted in just a few decades, I think there are lessons to be learned for higher ed. How we approach our subjects in the face of AI will both radically and also barely change. For instructors who have had the opportunity to participate in pedagogy learning groups, there may be a lot of overlap in what they already know about teaching and what changes AI might bring to the classroom. Here are some examples:

Many people are just now coming to the idea of the flipped classroom to have students grapple more deeply with concepts before turning to AI for help. But the idea of the flipped classroom is credited to Jonathan Bergman and Aaron Sams in 2006.

Another pedagogy model that instructors employ is the concept of transformative learning, which provides students with a disorienting dilemma of some kind and then walks them through the process of exploration and reflection to see if/how students were changed in some way through exposure to this new concept. Jack Mezirow is credited with developing this concept in the 1970s.

The concept of Scholarship of Teaching and Learning (SoTL) is another one that instructors might benefit from thinking about. In exploring SoTL projects, instructors take time to interrogate a teaching practice of their own and see if it really works or if it works the way that they think it does. The origins of SoTL can be traced back to Ernest L. Boyer's 1990 book Scholarship Reconsidered: Priorities of the Professoriate.

I also find value in prioritizing process over product, which can be credited to Säljö in 1979. This theory takes away from students the stress and burden of the "three tests and a final" or "three papers and a final" model that seems to have taken hold in many places and instead focuses on how students get to the final product. There is value and learning to be gained in the journey and not just the destination. Many other pedagogical theories have stood the test of time, but these deeply impact how I approach my classrooms.

Using pedagogical theories to approach teaching with AI

So why is this gaze backward when we are talking about the future of AI in higher ed? It is a reminder both that what was old is new again and that many of us already have at least a few tools in our pedagogy toolboxes to tackle the changes that AI will bring to our approaches to teaching.

Recommended Resources

When I think about the theories presented above, I think about how I have structured and restructured my classroom over time. At one point, I completely removed reading responses because they weren't working for me. Now they are back, but not as a product wholly unto themselves. Instead, they form the basis for our classroom discussion in the following meeting. Can students use AI to write their responses? Yes, quite easily, which is why they aren't the only measure of understanding and why we have class discussions as well. Students turn in their reading responses before class, then get into small groups in class to discuss the reading. After that, we come together as a large group and discuss the reading. The reading responses are also low-stakes points value, taking the pressure off students to cheat. And, if you wanted to add some transformative learning questions to the reading responses, you could get even deeper into what the readings meant to the students.

It is these minor tweaks to assignments that we already have - and using the pedagogical tools that already exist - that can make the most difference in our teaching and students' learning. As instructors, we know that knowledge matters. We understand why being strong critical thinkers is important for both work and citizenship participation, and we get that there is joy in the struggle to turn words on a page into life-long deep learning. Now, we have to take the time to emphasize these ideas to our students, as well as teach them when it might be appropriate to turn to AI for help and when AI will be more of a hindrance.

We are all tired from having to retool everything for emergency remote learning in such a short amount of time. And having to retool again for AI might seem overwhelming. My advice is to start small and involve your students in the process. Take time to develop AI literacy activities for your classes. Have students reflect on the usefulness and validity of AI to their assignments and understanding. Help students (and ourselves) learn to see AI as a tool instead of a way around work. Through small tweaks and little steps forward, we can help create authentic and valuable learning for our students in this new AI-enhanced world. Using the tools that we already have can help us shift our teaching to theory-driven ways rather than with a scattershot approach. By focusing on what we can do instead of what we can't control, we have the chance to bring some wonderful changes to higher ed that can benefit our students even after they leave our halls for the outside world of adulthood.

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AI in Higher Ed: Using What We Already Know About Good Teaching Practices - EdSurge News

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How is AI currently utilized in higher education? As of fall 2023, we are still in the early stages of figuring out what AI integration means for ...

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ChatGPT caused quite a stir when it launched to the public toward the end of 2022. The artificially intelligent chatbot inspired a range of reactions across the education world, from hype to hysterics.

EdSurge journalists have been reporting and writing about the implications this technology could have on everything from academic integrity to the future of the education workforce. You'll find our coverage gathered in this collection, along with other articles that offer insight about what AI might mean for education.

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For Education, ChatGPT Holds Promise - and Creates Problems - EdSurge Guides

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Generative AI has many possible implications on everything from academic integrity to the future of the education workforce.

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Education Week: Parents Are Open to AI Use in Schools. But They Have a Lot of Questions

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Education Week: Parents Are Open to AI Use in Schools. But They Have a Lot of Questions

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A flurry of surveys since ChatGPT was released nearly a year ago have highlighted how educators and students view-and use-artificial intelligence tools. But there's one major stakeholder who has been mostly left out of the conversation: parents.

A new poll from the National Parents Union seeks to address that gap and shed light on parents' thoughts, concerns, and hopes regarding AI and their children's education. Overall, the findings show that parents are uncertain but also open to the possibilities of how AI can advance their children's learning.

Four in 10 parents say they know a "little general information" about artificial intelligence, and about six in 10 say they have heard little to nothing about how AI can be applied in education.

Even so, the majority of parents-more than two thirds-believe that the potential benefits of AI to K-12 education either outweigh or are equal to the potential drawbacks. Only 16 percent of parents feel that the downsides outstrip any potential benefits.

But parents' current openness to AI can't be taken for granted, said Keri Rodrigues, the president of the National Parents Union. School and district leaders need to inform parents about how they're leveraging artificial intelligence in their schools before parents develop misconceptions and fears about the technology.

"I think one of the shocking things is that 62 percent of parents have heard little to nothing about AI. Every other aspect of industry, our economy, our society is talking about this technology," said Rodrigues. "I am always encouraging our superintendents, state chiefs, principals, our educators directly, you need to be transparent around, 'here's how we're incorporating AI in the classroom,' so [parents] are not filling that unknown space with stuff we hear on the internet."

ChatGPT, which can write essays in seconds and even pass a standardized bar exam, gave the general population easy access to generative artificial intelligence tools and spurred a rush to incorporate the technology into education as well as discussions around how these tools might be used or abused.

But AI is not new to K-12 education. Schools have used it in adaptive assessments, translation services, and programs to plan bus routes, to list a few examples.

The National Parent Union survey, which was fielded at the beginning of October, included 1,515 parents of public school students in grades K-12 from across the country.

About half of the parents in the poll said they're confident their child's school is well prepared to use AI in their "child's education" and that by introducing their children to AI, the schools are helping prepare their children for careers in the future that will require AI literacy and skills.

Schools 'don't know where to start'

But that leaves 29 percent who say their children's schools are not preparing their kids and 18 percent who are unsure. Those numbers are concerning, said Pat Yongpradit, the chief academic officer of Code.org and the Lead of TeachAI, a new initiative to support schools in using and teaching about AI.

"My response to that is, 'yeah, schools, you need to be proactive, you need to be promoting AI literacy, you need to be preparing students for the future,'" he said. "I think it's not because they don't want to do it, it's because they don't know where to start."

Yongpradit said schools can start by focusing on teaching AI literacy to students and teachers. Their outreach to families can begin with reassuring parents that the use of AI will comply with existing policies while they work on incorporating guidance around the use of AI in schools into existing school and district policies. TeachAI has a toolkit with resources addressing these challenges, including a sample letter schools can send to parents.

"Help parents understand that we're all figuring this out together and that uses will change as we learn more about evidence-based practices," Yongpradit said. "But reassuring parents that you're on top of this, working on guidance, and working on existing policies-parents will feel confident that schools are being active and not passive."

What parents see as the benefits of using AI in education

Pascale Small, who lives in Maryland, is one such parent who said she would like more information on how AI is used in her children's education.

"We have probably been using it without knowing it ... when we're using all these different apps, like I use for my district an app called Clever," said Small, who has one child in preschool and two more in early elementary school. "Have I explicitly heard my district tell me, 'we're using AI, and ChatGPT?' I haven't heard them specifically say that. But I wish they would. I would love for my district to show me as a parent how these tools can positively affect pedagogy, student learning and my child's creativity."

So, what do parents view as the benefits of AI?

Many see potential in leveraging AI in online tutoring. Fifty-six percent say they see that idea as having the best effect on K-12 education. And 53 percent say they see benefits in AI tools providing initial feedback on students' homework before they turn it in.

"We think about online tutoring programs, we know that high-impact tutoring is critically important to addressing learning loss we saw during the pandemic and a lot of parents don't feel like that's being done fast enough," said Rodrigues.

Overall, the majority of parents do not feel comfortable with the prospect of teachers using AI to help grade assignments-46 percent viewed that idea favorably. A little more than a third believe that allowing their children to use AI to help write essays would have a positive effect on their learning.

Even so, many parents do see upsides to teachers using AI. Around half of the parents surveyed said they see good potential in educators using AI to customize curriculum and lesson plans to their children's needs and to analyze student performance data.

In many ways, parents and educators are in the same boat when it comes to grasping the new technology. A survey completed in June of teachers, principals, and district leaders by the EdWeek Research Center found that only 1 in 10 said they know enough about AI to teach about it or use it in their work. An overwhelming majority said they had received no professional development on how to incorporate AI into their work.

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Parents Are Open to AI Use in Schools. But They Have a Lot of Questions

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Sixty-two percent of parents say in a new poll that they have heard little to nothing about how AI can be used in education.

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As school districts in the Treasure Valley see a rise in the use of artificial intelligence, educators say they’re figuring out ways to ensure the new tools are being used responsibly and don’t impede student learning.

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A discussion about Artificial Intelligence and Academic Misconduct was held on Oct. 16, hosted by Associate Dean of Students Shawna Casperson.

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A discussion about Artificial Intelligence and Academic Misconduct was held on Oct. 16, hosted by Associate Dean of Students Shawna Casperson. The event was held as an open discussion, with the primary audience being faculty members. During the event, Casperson asked thought-provoking questions rega…

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K-12 AI curricula: a mapping of government-endorsed AI curricula