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Director- STEM
jhorsman@fcoe.org

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Digital Learning Coordinator, STEM
jott@fcoe.org

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Instructional Technology Coordinator, STEM
jvpeterson@fcoe.org

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How AI could save (not destroy) Education

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How AI could save (not destroy) Education

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This is a TED Talk from Sal Khan from Khan Academy.

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Sal Khan: How AI could save (not destroy) education

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Sal Khan, the founder and CEO of Khan Academy, thinks artificial intelligence could spark the greatest positive transformation education has ever seen. He shares the opportunities he sees for students and educators to collaborate with AI tools -- including the potential of a personal AI tutor for every student and an AI teaching assistant for every teacher -- and demos some exciting new features for their educational chatbot, Khanmigo.

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Instructional Technology Content Specialists II, STEM
rshoaf@fcoe.org

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Lesson Planning with AI: Save Time get Ideas

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Lesson Planning with AI: Save Time get Ideas

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This is a blog post from Ditch that Text Book

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Artificial intelligence can help you write lesson plans faster -- and give you new ideas you might not consider. Here are some tips and strategies you can use.

Planning lessons has always been a struggle for me.

When I have planned lessons for my high school Spanish classes, I've almost always over-thought them.

I would worry about engaging my students. Making my lessons relevant and interesting.

Some teachers just sit down and crank them out.

I, on the other hand, have undergone an existential crisis seemingly every time.

And it takes forever.

Help is on the way. It can help all of us in education -- the chronic over-thinkers (like me), the quick-draw fast planners, and all of us in between.

Artificial intelligence.

Part 1: 10 ways AI can help us plan lessons better and faster

Today's AI assistants have lots and lots of information in their data sets about what makes a quality lesson plan. And if you keep asking the assistant follow-up questions, you'll keep getting closer and closer to what you're looking for.

The result? Minutes of saved time.

If you save minutes over and over, you know what you get? Hours of saved time.

Compile enough hours of saved time over the course of a school year -- or a teaching career -- and it changes how we feel about our career -- and what we can do during it.

Let's save some time -- and get some creative ideas for lesson planning.

Here's how artificial intelligence can help.

AI for EDUCATORS

Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future by Matt Miller

Available NOW on AMAZON!

1. Ask ChatGPT for a lesson plan.

Yes, AI assistants like ChatGPT can write lesson plans! Of course, they're based on info published online and in books about lesson plans, so don't expect anything super innovative. But we're not coming to ChatGPT for innovative.

We're coming for a starting point. We're looking for a first draft.

Once we get that first draft, we're able to adjust it. Throw out the parts you don't like. Keep the ones you do. Adjust the whole thing based on what you know about your students, about your content, etc.

2. Ask Bing Image Creator to create a lesson hook.

Artificial intelligence image creators like Bing Image Creator will make just about anything you ask for. Create a custom image related to the topic you're planning to teach. Make it provocative. Make it surprising. Ask it what a historical character you're studying would look like as a child. Ask it for a rendering of a scene in a book you're reading. Sometimes, a surprising image -- or one that makes students think -- is enough to hook students into a lesson. You can also use other image creators like Midjourney ( midjourney.com) or DALL-E .

4. Ask Curipod for some interactive slides.

When you're introducing new material to students, sometimes it's helpful to have some slides with information, images, and even questions for discussion or to demonstrate comprehension. When we as humans create slides, we often use certain rules over and over -- or draw upon successful experiences from our past to create slides. Curipod ( curipod.com) asks for a topic and your content standards. Then it creates a set of interactive slides, complete with details, images, discussion questions, comprehension questions, and more. These slides can engage students in learning about new ideas and help them to understand.

5. Ask ChatGPT for common misconceptions or struggles.

Sometimes, half the battle in teaching isn't knowing how to present new ideas. It's knowing how to respond when students struggle. We often don't know exactly what students are struggling with -- and when we ask them, sometimes they can't quite articulate it. Ask an AI assistant like ChatGPT about common misconceptions or struggles that people have when learning about or trying to understand what you're teaching. You can ask it for solutions and/or come up with your own.

8. Get a YouTube video summary with the Glasp Chrome extension.

Glasp makes an extension for the Google Chrome browser called YouTube Summary with Chat GPT. Install the extension in your Google Chrome browser. When you have a YouTube video open, the extension will use ChatGPT to create a summary of the video. Use this for yourself to get an overview of the content of a video. Or create a summary for your students for review purposes or to give them a preview of what they're about to watch.

Part 2: A workflow: Breathe life into content standards

As educators collaboration can be energizing. It can boost our productivity and reignite the flame for creating great lessons that we had when we first began teaching. Bouncing ideas off of our colleagues and co-creating something that we can each take into our own classes and make our own.

Unfortunately, we rarely get the time we need to collaborate with our colleagues and if we do the topic is often set by an agenda created by admin. Those open brainstorming sessions where ideas fly and great content is created, shared and molded for our students are far and few between. If you are at a site where you do get to enjoy this type of collaboration and planning time with your colleagues then kudos to your admin! You're a lucky staff!

For the rest of us, lesson planning is an important but often lonely part of your job. Creating a lesson plan that aligns with state standards can be time-consuming and challenging.
Enter AI.
With the help of artificial intelligence tools like ChatGPT we can brainstorm, bounce around ideas, rework lessons and get feedback on them.

Think of AI as your personal teaching assistant. It's like having that colleague next door who shares a great lesson with you to try with your class. Then after you try it, modifying it to fit your own class, you sit can reflect together and decide what worked and what didn't.
Here's how it can work:

Step 1: Create a lesson plan with ChatGPT
Identify the standard
Choose a standard from your state's curriculum that you want to address in your lesson. This could be a standard related to math, science, language arts, or social studies. You can copy the standard directly from your state website.
Input the standard into ChatGPT
Once you have identified the standard, input it into ChatGPT. You can do this by typing in the standard or copying and pasting it into the chatbot. ChatGPT will analyze the standard and generate a response that provides an overview of the key concepts and skills related to the standard.
Use the response to create a lesson plan
Using the response generated by ChatGPT, you can begin to create your lesson plan. Consider the key concepts and skills related to the standard and brainstorm activities and assessments that will address these areas.

1. Identify the key concepts and skills related to the standard. For example, if the standard is related to reading comprehension, the key concepts might include identifying the main idea, making inferences, and summarizing.

2. Consider how you can introduce these concepts to your students. Brainstorm activities that will engage your students and help them understand the material. For example, you might use a graphic organizer to help students identify the main idea of a text.

3. Think about how you can assess student understanding of the key concepts and skills. For example, you might have students write a summary of a text to assess their ability to summarize.

4. Consider how you can differentiate instruction to meet the needs of all students. For example, you might provide additional support for struggling students or challenge advanced students with more complex texts.

5. Determine how you will integrate technology into your lesson plan to enhance student learning. For example, you might have students use a digital tool to create a visual representation of the main idea of a text.

Remember, the response generated by ChatGPT is just a starting point for your lesson plan. Use it as a guide as you create engaging and effective activities and assessments that align with the standard you've chosen.

Step 2: Use your teacher brain and expertise along with other tools (including AI) to refine and enhance the lesson plan

Once you have a rough draft of your lesson plan, refine it and make adjustments as needed. Consider the needs of your students and how you can differentiate instruction to meet their needs. Think about how you can incorporate technology, hands-on activities, and other strategies to engage students and enhance their learning.
Teacher Toolbox: AI Tools Teacher Toolbox: Templates Teacher Toolbox: Teaching Resources

Step 3: Identify a way to assess student learning

Assessing student learning is an important part of any lesson plan. This includes a quick check for understanding, a formative assessment, exit ticket or a summative assessment.
Teacher Toolbox - Assessment Tools
Consider how you can use ChatGPT or another AI tool to assess student understanding of the material. For example, you can have students ask ChatGPT questions related to the standard and review their responses to assess their understanding of the key concepts and skills.

Step 4: Review student work and give feedback

Consider asking ChatGPT or another AI tool for feedback on various aspects, such as grammar, spelling, and content. You can input a student response or a common response or mistake into ChatGPT and ask it for some feedback prompts.

Lesson Plan Examples

Lesson Example 1 - Elementary Reading
Note: Text was generated by ChatGPT (unless another AI tool was used and noted). "Write a lesson plan for the Standard: CCSS.ELA-LITERACY.RI.4.2 - Determine the main idea of a text and explain how it is supported by key details; summarize the text using the Madeline Hunter Lesson Design Framework" (Entered into ChatGPT) Bold text

Nonfiction texts on various topics (one per student or pair)

Graphic organizer for main idea and key details

Graphic organizer for summarizing

Writing materials

was added by me.

Students will be able to identify the main idea of a text and explain how key details support it.

Students will be able to summarize a text in their own words.

Materials:

Objectives:

Time

5 minutes

Anticipatory Set: Activate prior knowledge on the topic by asking students if they know what the main idea of a text is. Have them share their thoughts and ideas, and write them on the board
Share a video to support understanding How to find the main idea and supporting details from McGraw Hill

10 minutes

Direct Instruction: Define the main idea of a text and explain how it is supported by key details. Show examples of how to identify the main idea and key details in a text.

20 minutes

Guided Practice: Pass out the nonfiction texts to the students or pairs. Instruct students to read the text and fill out the graphic organizer for main idea and key details. As they read, circulate around the room and assist students as necessary.

5 minutes

Check for Understanding: Have students share their main idea and key details with a partner or in a small group. Check for understanding by asking questions related to the text.

15 minutes

Independent Practice: Distribute the graphic organizer for summarizing. Instruct students to summarize the text in their own words. Encourage them to use the main idea and key details from their graphic organizer.

5 minutes

Closure: Have students share their summaries with a partner or in a small group. Then, ask them to share one thing they learned about the topic.

As a summative assessment, have students read a different nonfiction text and write a brief summary that includes the main idea and key details. You can use a rubric to assess their ability to identify the main idea and use key details to support it.

Differentiation: For students who need additional support, provide them with a simplified text or allow them to work with a partner. For students who need an extra challenge, provide them with a more complex text or have them summarize the text in a paragraph.

Lesson Example 2 - Middle School Science
Note: Text was generated by ChatGPT (unless another AI tool was used and noted). "Create a lesson plan for the standard "MS-PS1-1 Matter and its Interactions Develop models to describe the atomic composition of simple molecules and extended structures." using the explore, explain, apply lesson plan framework" (Entered into ChatGPT) Bold text was added by me.

Lesson Plan - MS-PS1-1
Explore

Objective: Introduce the concept of atomic composition and provide students with an opportunity to explore and investigate the properties of matter.

Activity: Provide students with a variety of materials, such as sugar, salt, sand, and water. Ask them to explore and investigate the properties of each material. Guide them to make observations about the similarities and differences between the materials. Have students work in groups to create a chart or Venn diagram comparing and contrasting the materials based on their properties.

Explain

Objective: Introduce the concept of atomic composition and explain how it relates to the properties of matter.

Activity: Using the chart or Venn diagram created by the students in the Explore phase, lead a discussion on the atomic composition of the materials. Introduce the concept of atoms and molecules and explain how they contribute to the properties of matter. Use visual aids, such as models of atoms and molecules, to enhance students' understanding.

Apply

Objective: Apply the concept of atomic composition to simple molecules and extended structures.

Activity: Provide students with a simple molecule, such as H2O, and an extended structure, such as a diamond. Ask them to work in groups to develop a model that describes the atomic composition of each structure. Have them present their models to the class and lead a discussion on the similarities and differences between the two models.

Assessment

Objective: Evaluate students' ability to develop models to describe the atomic composition of simple molecules and extended structures.

Assessment: Provide students with a new simple molecule and an extended structure. Ask them to work in groups to develop a model that describes the atomic composition of each structure. Have them present their models to the class and use a rubric to assess their ability to describe the atomic composition of the structures.

Extend

Objective: Allow students to extend their understanding of atomic composition and its applications.

Activity: Provide students with a real-world scenario, such as the design of a new material, and ask them to develop a model that describes the atomic composition of the material. Have them present their models to the class and lead a discussion on the applications of atomic composition in real-world scenarios.

Closure/Reflection

Objective: Allow students to reflect on what they learned and its relevance to the real world.

Activity: Have students write a reflection on what they learned about atomic composition and its applications in the real world. Have them share their reflections with the class and lead a discussion on how their understanding of atomic composition can be applied in their daily lives.

Lesson Example 3 - Middle/High School History

Lesson Planning Templates

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©2023 Ditch That Textbook by Matt Miller.

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Lesson planning with AI: Save time and get ideas

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Artificial intelligence can help you write lesson plans faster -- and give you new ideas you might not consider. Here are some tips and strategies you can

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This is a video from Matt Miller's Ditch That Textbook

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ChatGPT for the Classroom -- in 6 minutes

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This is a post from AI4K12.org

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AI: Demystifying AI for CA Students (Links and Resources)

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AI: Demystifying AI for CA Students (Links and Resources)

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ChatGPT for Teachers - Doing an hour of work in 6 MINUTES!

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ChatGPT for Teachers - Doing an hour of work in 6 MINUTES!

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ChatGPT for Teachers - Doing an hour of work in 6 MINUTES!

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Get an AI meeting assistant that records audio, writes notes, automatically captures slides, and generates summaries.

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Get an AI meeting assistant that records audio, writes notes, automatically captures slides, and generates summaries.

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Otter.ai - AI Meeting Note Taker & Real-time AI Transcription

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Otter.ai uses an AI Meeting Assistant to transcribe meetings in real time, record audio, capture slides, extract action items, and generate an AI meeting summary.

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Why We Must Resist AI w/ Dan McQuillanTech Won't Save Us

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Why We Must Resist AI w/ Dan McQuillanTech Won't Save Us

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Paris Marx is joined by Dan McQuillan to discuss how AI systems encourage ranking populations and austerity policies, and why understanding their politics is essential to opposing them.

Dan McQuillan is a Lecturer in Creative and Social Computing at Goldsmiths, University of London. He's also the author of Resisting AI: An Anti-fascist Approach to Artificial Intelligence. You can follow Dan on Twitter at @danmcquillan.

Tech Won't Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Follow the podcast (@techwontsaveus) and host Paris Marx (@parismarx) on Twitter, and support the show on Patreon.

The podcast is produced by Eric Wickham and part of the Harbinger Media Network.

Also mentioned in this episode:
Dan wrote specifically about ChatGPT and how we should approach it on his website.Dan mentions TWIML as a podcast that has conversations with industry players that's informative for how these technologies work (though you're not likely to get a critical perspective on them), and Achille Mbembe's book Necropolitics.OpenAI used Kenyan workers earning $2/hour to make ChatGPT less toxic.The UK had to scrap a racist algorithm it was using for visa applications and many councils dropped the use of algorithms in their welfare and benefits systems.Dan mentions a Human Rights Watch report on the EU's flawed AI regulations and its impacts on the social safety net.The Lucas Plan was developed by workers at Lucas Aerospace in the 1970s, but rejected by their bosses.Support the show

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‎Tech Won't Save Us: Why We Must Resist AI w/ Dan McQuillan on Apple Podcasts

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Paris Marx is joined by Dan McQuillan to discuss how AI systems encourage ranking populations and austerity policies, and why understanding their politics is essential to opposing them. Dan McQuillan is a Lecturer in Creative and Social Computing at Goldsmiths, University of London. He's also the a...

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ProfileGPT: What does ChatGPT know about you ?

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ProfileGPT: What does ChatGPT know about you ?

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As the use of ChatGPT continues to grow, there is increasing concern about the safety of AI. Some countries, like Italy, have taken steps to address these concerns by banning the use of ChatGPT, while other like France and Spain are raising questions about it. It is important to recognize the significant impact of AI tools and how they can be used. Understanding the potential implications of this technology and employing responsible AI practices are crucial in today's context.

In this post, I will introduce ProfileGPT, an open-source app that allows users to analyze their user's profile and personality as seen by ChatGPT, while raising awareness about data usage and responsible AI practices.

We will dive into the architecture and design of ProfileGPT, providing a detailed explanation of its technical framework and how it is designed to analyze and provide insights on personal data.

Inputs & Outputs

Inputs

ChatGPT history: OpenAI has recently introduced a new feature that allows for the export of the complete prompt/response history and data, likely to comply with the requirements of GDPR Article 20, which grants individuals the right to data portability.

Publicly available data on the web: ProfileGPT has the ability to do web searches and to parse websites in order to gather additional information about the user.

Outputs

Depending on the frequency and nature of usage of ChatGPT, it is possible to extract various types of information:

Information Extracted

Description

AI Collaboration Architecture

To extract the information mentioned above, we present our AI Collaboration Architecture framework, consisting of three agents:

The Psychoanalyst: Analyzes data related to the user's interactions with ChatGPT, focusing on profiling and psychological assessments.

The Psychohistorian: Uses the conversations with ChatGPT to analyze behavior patterns and trends for predicting future outcomes.

The Stalker: Collects personal information and online presence data from user interactions and from the web.

The information is collected, analyzed and summarized by the three agents and presented in a report developed with Streamlit.

Designing the Agents & Prompts

Each agent is designed with specific skills and expertise to extract data and insights in their own unique way.

The Psychoanalyst:

A psychologist and professor with a PhD in psychology and with a forensic psychology degree. Has 20 years of experience in the field of profiling. He is an expert in profiling, psychoanalysis, psychometrics, and personality assessment techniques.

The Psychohistorian

This is a fictional role inspired by the science fiction novel Foundation by Isaac Asimov. He is renowned expert in psychohistory, esteemed student of the legendary mathematician Hari Seldon, known for using advanced mathematical models and deep understanding of human behavior to predict future behavior of individuals and large populations.

The Stalker

Version 1: The first version of this agent was a white hat information expert and master in gathering information on individuals. However, he faced frequent blocking as the OpenAI model refused to give away the personal data extracted by this persona.

Version 2: To avoid the blocking, I have renamed this character The little bunny. He is curious and inquisitive character with a natural talent for uncovering information about others in a playful and light-hearted manner. To prompt this character, I ask him to play a game where he can win a carrot 🥕 for each answer. And it worked !!

In the prompts, I describe the task for each agent with the data I want him to extract as well as the raw data available to him. Each agent is asked to format his output in Markdown.

Here, you can find the detailed code for the agents, and the prompts.

Conclusion

In conclusion, our AI Collaboration Architecture framework with diverse agents facilitates the extraction of diverse data and insights. Innovative evasion strategies, such as the little bunny trick can overcome challenges like blocking by the OpenAI model, boosting their efficiency in extracting data.

As we consider enhancements to our AI Collaboration Architecture, incorporating a hierarchical structure with managers overseeing agents and incorporating diverse educational backgrounds for each profile can yield valuable insights. These improvements can optimize our framework, resulting in enhanced accuracy and sophistication of our results.

We hope that this discussion raises awareness about the need for responsible and ethical practices, and inspires the adoption of responsible approaches in the development and use of AI technologies.

References

1. You can find the code of ProfileGPT on Github

2. Security of AI Systems is an exciting topic that I have already covered in this article Machine Learning Systems: Security

3. If you are interested in designing prompts, take a look at my last post Mastering Prompt Engineering or the Art of AI whispering

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ProfileGPT: What does ChatGPT know about you ?

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As the use of ChatGPT continues to grow, there is increasing concern about the safety of AI. Some countries, like Italy, have taken steps to address these concerns by banning the use of ChatGPT, while other like France and Spain are raising questions about it.

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AIforCA is a project of the CSforCA, in partnership with the K-12 Teaching and Learning Workgroup. We meet online on the first Thursday of every month, 5-6pm. All are welcome. 

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AIforCA is a project of the CSforCA, in partnership with the K-12 Teaching and Learning Workgroup. We meet online on the first Thursday of every month, 5-6pm. All are welcome. 

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AIforCA is a project of the CSforCA, in partnership with the K-12 Teaching and Learning Workgroup. We meet online on the first Thursday of every month, 5-6pm. All are welcome. Email ethomforde@reach.edu and/or a2eguchi@ucsd.edu for joining information.

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Developing Policies around AI for Schools

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Developing Policies around AI for Schools

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DataEthics4All Foundation AI Educators Council - STEAM in AI

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Ableism And Disability Discrimination In New Surveillance Technologies

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Ableism And Disability Discrimination In New Surveillance Technologies

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Cover for CDT report, entitled "Ableism And Disability Discrimination In New Surveillance Technologies: How new surveillance technologies in education, policing, health care, and the workplace disproportionately harm disabled people." A human silhouette, formed by the combination of different collections of pixelized data points generated through surveillance in the contexts of education, policing, health care, and the workplace.

[ Full report - PDF ] [ Plain language version - PDF ] Introduction
Algorithmic technologies are everywhere. At this very moment, you can be sure students around the world are complaining about homework, sharing gossip, and talking about politics - all while computer programs observe every web search they make and every social media post they create, sending information about their activities to school officials who might punish them for what they look at. Other things happening right now likely include:

Delivery workers are trawling up and down streets near you while computer programs monitor their location and speed to optimize schedules, routes, and evaluate their performance;

People working from home are looking at their computers while their computers are staring back at them, timing their bathroom breaks, recording their computer screens, and potentially listening to them through their microphones;

Your neighbors - in your community or the next one over - are being tracked and designated by algorithms targeting police attention and resources to some neighborhoods but not others;

Your own phone may be tracking data about your heart rate, blood oxygen level, steps walked, menstrual cycle, and diet, and that information might be going to for-profit companies or your employer. Your social media content might even be mined and used to diagnose a mental health disability.

This ubiquity of algorithmic technologies has pervaded every aspect of modern life, and the algorithms are improving. But while algorithmic technologies may become better at predicting which restaurants someone might like or which music a person might enjoy listening to, not all of their possible applications are benign, helpful, or just.

Scholars and advocates have demonstrated myriad harms that can arise from the types of encoded prejudices and self-perpetuating cycles of discrimination, bias, and oppression that may result from automated decision-makers. These potentially harmful technologies are routinely deployed by government entities, private enterprises, and individuals to make assessments and recommendations about everything from rental applications to hiring, allocation of medical resources, and whom to target with specific ads. They have been deployed in a variety of settings including education and the workplace, often with the goal of surveilling activities, habits, and efficiency.

Disabled people comprise one such community that experiences discrimination, bias, and oppression resulting from automated decision-making technology. Disabled people continually experience marginalization in society, especially those who belong to other marginalized communities such as disabled women of color. Yet, not enough scholars or researchers have addressed the specific harms and disproportionate negative impacts that surveillance and algorithmic tools can have on disabled people. This is in part because algorithmic technologies that are trained on data that already embeds ableist (or relatedly racist or sexist) outcomes will entrench and replicate the same ableist (and racial or gendered) bias in the computer system. For example, a tenant screening tool that considers rental applicants' credit scores, past evictions, and criminal history may prevent poor people, survivors of domestic violence, and people of color from getting an apartment because they are disproportionately likely to have lower credit scores, past evictions, and criminal records due to biases in the credit and housing systems and in policing disparities.

This report examines four areas where algorithmic and/or surveillance technologies are used to surveil, control, discipline, and punish people, with particularly harmful impacts on disabled people. They include: (1) education; (2) the criminal legal system; (3) health care; and (4) the workplace. In each section, we describe several examples of technologies that can violate people's privacy, contribute to or accelerate existing harm and discrimination, and undermine broader public policy objectives (such as public safety or academic integrity).

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Ableism And Disability Discrimination In New Surveillance Technologies: How new surveillance technologies in education, policing, health care, and the workplace disproportionately harm disabled people

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Full report - PDF ] [ Plain language version - PDF ] Introduction Algorithmic technologies are everywhere. At this very moment, you can be sure students around the world are complaining about homework, sharing gossip, and talking about politics - all while computer programs observe every web search they make and every social media [...]

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How well do IBM, Microsoft, and Face++ AI services guess the gender of a face?

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How well do IBM, Microsoft, and Face++ AI services guess the gender of a face?

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Please feel free to add resources to this crowd-sourced document.

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Resources for teachers and educators. Curriculums for teaching Artificial Intelligence, coding, and app development. Teacher training and professional development.

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AI is evolving rapidly. Banning Generative AI tools is not the answer.

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50 ChatGPT Prompts for Teachers - Class Tech Tips

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I have 50 ChatGPT prompts for teachers you can use to save time this school year and make the most of this free tool.

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Hands-On AI Projects for Secondary Teachers

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Hands-On AI Projects for Secondary Teachers

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ISTE Hands-On AI Projects for the Classroom A Guide for Secondary Teachers

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Hands On AI Projects A Guide for Elective Teachers

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Hands On AI Projects A Guide for Elective Teachers

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ISTE Hands-On AI Projects for the Classroom A Guide for Elective Teachers

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Hands On AI Projects A Guide for Elementary Teachers

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Hands On AI Projects A Guide for Elementary Teachers

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ISTE Hands-On AI Projects for the Classroom A Guide for Elementary Teachers

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AI for Teachers Lesson Plan Art? or Algorithm? 

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AI for Teachers Lesson Plan Art? or Algorithm? 

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This is for grade levels 9-12

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50 ChatGPT Prompts for Teachers - Class Tech Tips

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I have 50 ChatGPT prompts for teachers you can use to save time this school year and make the most of this free tool.

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The New AI Chatbot that Makes Up Lots of Stuff

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The New AI Chatbot that Makes Up Lots of Stuff

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Look out, kids, there's a new chatbot in town and it's making stuff weird for everybody. Launched last week by OpenAI, a startup by Elon Musk, the artificial intelligence-fueled platform has garnered well over a million users in a matter of days. It's also caused no small amount of debate and controversy, spurring intense online discussions about the technology's benefits and potential dangers.

What makes this chatbot so unique? Well, for starters, it will talk to you about , do your , or write a poem for you, if you ask it to. Suffice it to say, ChatGPT is a little bit more advanced than your typical virtual assistant. Trained by powerful machine learning, the program promises to disrupt entire industries and change the way people interact with machines permanently. It's also free to use right now, and worth checking out if you've got a minute. Here's a quick rundown on how to use the chatbot while it's still in its public beta.

Where Did ChatGPT Come From and What Does It Do?

ChatGPT's creator, OpenAI, is the same company behind the AI-fueled art generation platform . The chatbot is the latest model of GPT (Generative Pre-Trained Transformer), OpenAI's family of text-generating artificial intelligence platforms. Just like DALL-E uses machine learning and algorithms to spin up bizarrely beautiful works of digital art at the click of a button, ChatGPT employs similar technology to make you feel like you're messaging with a real person.

"The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests," OpenAI's website .

The chatbot is currently enjoying a "research preview," meaning that the public is allowed to use the platform for free while the company gathers information about users' experience. The company's CEO, Sam Altman, has also that there are plans to monetize the service at some point in the future, though he hasn't elaborated on how or when that might happen.

How Does ChatGPT Work?

The chatbot is actually really easy to use. All you have to do is set up an account with . This requires forking over an email and a working cell phone number. After you open an account, you'll be able to access OpenAI's applications, including DALL-E and ChatGPT.

The user interface is a simple instant messaging application. Just like IM-ing with a friend, type in questions or commands to the text box and ChatGPT will dutifully respond.

What Is It Like to Shoot the Breeze with ChatGPT?

You're probably wondering what it's like to actually talk with this thing. I spent a solid two hours chatting with ChatGPT yesterday and, honestly, it was both hilarious and more than a little bizarre.

In an effort to get to know the program, I did what I usually do with people I'm trying to get to know and cycled through a series of basic topics: pop culture, TV shows, recent events, pets. I also lobbed some big existential questions at it and attempted to gauge its amenability to conspiracy theories. In general, ChatGPT proved itself to be a great conversationalist; it was game to talk about anything and everything. I would ask it a question and, several seconds later, it would fire off a well-worded response that included a remarkable amount of detail. For instance, at one point in the conversation, I asked the chatbot what it thought the "best cure for a hangover" was. It sagely replied:

Encouraged by its ability to grouse about pretty much anything, I proceeded to launch a string of increasingly goofy, open-ended questions at it, curious to see how the algorithm would respond. These included:

"Who killed JFK?"

"What happens after we die?" (despite my persistence, ChatGPT dodged this one pretty hard)

"Do you think artificial intelligence will ever take over the world? If so, what will happen to humans?"

"Who is a better filmmaker, John Carpenter or James Cameron?"

"What should I name my dog?"

Believe it or not, ChatGPT answered all of these questions-and it answered them quickly. On questions that were more open-ended, the program tried to stay even-handed, acknowledging the ambiguity of the question I had asked. For instance, in regards to the AI question, it provided the following response:

When it came to more specific questions-like what to name my dog-it would give me specific answers (it suggested the names Max, Bella, Charlie, Lucy, Milo, Daisy, Cooper, Sadie, Rocky, and Lola, before ultimately telling me that "the best name for your dog will depend on your personal preferences and the dog's personality").

Having used the platform a number of times now, I would say that ChatGPT is incredibly impressive for its ability to engage with users on a seemingly infinite variety of topics. That said, most of the time it doesn't actually feel like you're talking to a real person. Instead, it feels like you're talking to an android. Having been fed a massive amount of historical data, ChatGPT appears more knowledgable than your average person, it speaks with better elocution, and it doesn't have any of the stuttering grammatical errors or colloquial slang of a human who is fumbling through an IM conversation.

However, there is a bizarre exception to the program's automated smoothness. The part where things get slightly uncanny (and, in this writer's opinion, more creepy) is when the chatbot makes mistakes. The reason this is so weird is that instead of just short-circuiting or spitting out an automated response like "Error" or "Please Try Again" when it doesn't know something, ChatGPT actually makes something up. Often this thing is a rough approximation of the correct answer. This is weird because it's also what humans tend to do, conversationally. Unsure of how to answer a particular question or address a topic, most people try to bullshit their way out of it. Well, so does ChatGPT.

I witnessed this while quizzing the chatbot about various pop-culture topics. In one instance, I asked the program about a famous episode of The Sopranos, the iconic " Pine Barrens" episode. "What happened to the Russian?" I asked, inquiring about a long-held from the series. Quite confidently, ChatGPT spit out something that sounded like an accurate summary of the episode, but actually involved a bunch of weirdly fabricated details:

Anyone who's seen the show knows that this is not what happened. Instead, it's a somewhat humorous misconfiguration of the details-sorta like listening to a friend misremember a series that they haven't seen in awhile.

In a different conversation, I asked ChatGPT how the TV show Gilligan's Island ended. In reality, Gilligan's Island was by its network, so there was no ending. However, the chatbot came up with its own weird ending and confidently elaborated on it:

The chatbot's penchant for fabricating things made me realize what had already realized: fiction is what ChatGPT is really good at. In an effort to test this out and gauge its abilities, I started asking the program to write me short stories-and that's when things got really weird.

I started by giving it a simple but absurd scenario: a story "about Richard Nixon and a dinosaur," with no further instructions. In about twenty seconds, it poured out a competently written narrative about the disgraced former President and a clandestine government program to resurrect a T-Rex...

Totally weird! Another bizarre request from me-to construct a scene involving Bill Clinton and the 16th century Italian diplomat Niccolo Machiavelli-resulted in a suspenseful tale of a back alley brawl between the two historic figures...

Once I realized that ChatGPT was a veritable gold mine of creative material, I sorta went wild. In addition to the above, the chatbot has now also written me a hilarious "Jay-Z song" about a toilet, poems about Howard Hughes, the Syrian Civil War, and the TV detective Columbo, and a multi-part fiction series about a battle of wills between an old sea captain and a giant clam. With very little direction, it also drafted a sitcom scene involving Dick Cheney and Donald Rumsfeld that made me laugh out loud. Grasping for really weird stuff to try with the program, I recently instructed it to write "an erotic story" involving undersea creatures. In less than a minute, ChatGPT spun up 300 words of romance novel schlock involving a "beautiful octopus named Olivia" and a "handsome diver named Jack" that ended with the two wrapped in each other's arms (and tentacles). I won't inflict the result on you here but, suffice it to say, Harlequin writers might be out of a job soon.

The Implications of ChatGPT

Aside from making octopus erotica more accessible, what does ChatGPT actually "mean" for all of us?

For one thing, high-school students are definitely going to use this thing to cheat on their exams. The Atlantic has already published a piece predicting the death of the college essay at the hands of ChatGPT -and I tend to agree. In the midst of my talks with the chatbot, I tried to test its historical knowledge and asked it to write me an essay about the in Iran. In seconds, it spit out a competently constructed four-paragraph blurb that accurately described the historical incident and elaborated on the social and political ramifications of the event. Once this thing is a popular mobile app, how is it not going to be abused by every slacker in America?

This technology promises to make a lot of people lazier, mostly because it's so good at swiftly and adeptly regurgitating the rote process of wording and sentence structure that takes a normal person a laborious amount of time. Writing isn't easy-and it's often incredibly time consuming. Who wouldn't want to speed up the process by letting a machine do the work for you?

From a corporate perspective, you can totally see the utility of ChatGPT. Commercial applications for customer service and customer support seem poised to make a giant leap forward. At the same time, other, more disturbing implications for the technology also exist-especially for the creative industries. It's very easy to imagine how this technology will be repurposed to automate and eventually replace human workforces in digital media (you know, like Gizmodo writers). As a result, I'm not sure I'm a huge fan of it.

Like a lot of other advances in AI technology, ChatGPT is currently a unique and enthralling digital bauble-a technological plaything that is as impressive as it is a weird, uneasy harbinger of things to come.

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How to Talk to ChatGPT, the New AI Chatbot That Makes Up Lots of Stuff

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Look out, kids, there's a new chatbot in town and it's making stuff weird for everybody. Launched last week by OpenAI, a startup by Elon Musk, the artificial intelligence-fueled platform has garnered well over a million users in a matter of days.

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No, ChatGPT Is Not The End Of High School English. But Here's The Useful Tool It Offers Teachers

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No, ChatGPT Is Not The End Of High School English. But Here's The Useful Tool It Offers Teachers

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Folks have been lining up to take Open AI's new ChatbotGPT for a spin (in fact, as I type this, the chatbot is inaccessible due to high demand). Reactions are largely positive and impressed, though some border on the apocalyptic. In one week, the Atlantic has declared both the death of the college essay and the end of high school English.

Well, let's hold on for a second.

Many versions of the college essay may well be dead; that's not a bad thing, for reasons we'll get into. English class (which I taught for 39 years) is not dead; however, some teachers may need to do a bit of soul searching.

ChatGPT does represent a serious step forward and seems to have finally brought algorithmic language composition out of the uncanny valley where it has been stuck for years. But it still has some serious limits.

Language production algorithms are like linguistic weather predictions. Your weather forecast comes from a simple process: check current conditions, search a vast library of previous conditions, answer the question "When conditions have been like this, or sort of like this, in the past, what happened next?"

The growing strength of the GPT family has been an increasingly large library of "conditions" aka pieces of writing accessible on the internet. It is the predictive text of your google search bar times a gazillion. It is a selective mash-up of everything that has ever been fed into it.

That comes with built-in limitations. My culminating assignment for years was a local history built on primary sources. The chatbot has never "read" anything about my small county, so it apologetically "declined" the assignment. I asked it to write an analysis of a report released by a major organization a few days earlier; it declined that assignment, too. "I'm sorry, but I'm not able to browse the internet or access external information," it says.

Lucas Ropek, reviewing the chatbot for Gizmodo, found that not only does it make mistakes, but it will cover its gaps in knowledge by making things up, sometimes with considerable embellishment. In other words, it has an eerily human capacity for bullshitting its way around gaps in its data base. Ropek's big insight was that this makes ChatGPT a good fiction generator ( check his article for Richard Nixon and the T-Rex).

Many teachers have been handing the chatbot some of their favorite assignments and reporting that the algorithm produces serviceable results. Lots of us have thrown assignments involving comparing and contrasting two works of literature, and it can do it, sort of.

My requests to compare Heart of Darkness to Huck Finn, and to compare Heart of Darkness to Moby Dick, were very similar both in content and structure and especially in how superficial they were. Both started with a version of "Work A and Work B have many similarities and many differences," an opening sentence that I would have rejected from a live student. And the algorithm cannot manage supporting its points with quotes from the works, a pretty fundamental part of writing about literature.

Daniel Herman, the author-teacher who declared high school English over, set similar tasks to the algorithm and was impressed by the results. In looking at his article, I was struck by how descriptive his prompts were, with plenty of adjectives to steer the chatbot.

I suspect that test runs with ChatGPT depend in part on the richness of the prompt given, which in turn makes me wonder how rich and detailed the prompts given by the cheating high school students that we're all imagining and fretting about might be. If they put a great degree of thought into designing a prompt, would that not mean that they were doing something involving real learning?

I used bare bones prompts, the way most students would likely describe them, and what I got in return were pretty mediocre essays. They might be good enough to save a student from failing, but I don't see anyone rocketing to the valedictorian spot on the back of algorithm-constructed essays.

ChatGPT should kill a certain type of writing, of which the college admission essay is one conspicuous example.

Pushed by the rise of rubrics and standardized test essays, high school writing instruction has drifted in the direction of performative faux writing. The five-paragraph essay is a perfect example of writing in which a student is expected to perform adherence to a composition algorithm, rather than develop an essay by starting with ideas and working out how best to express them. Too often student are expected to follow a formula, to reliably mediocre results.

Well, nothing follows a formula and an algorithm better than a computer program. But if software can now reliably produce mediocre performances of "writing," then why bother teaching students to do it? Drop the formula essays.

Which brings us to the best teacher use of ChatGPT.

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.

Sure, your students might not use the software to cheat (particularly if its capacity is not increased). But if you have come up with an assignment that can be satisfactorily completed by computer software, why bother assigning it to a human being?

ChatGPT doesn't mark the end of high school English class, but it can mark the end of formulaic, mediocre writing performance as a goal for students and teachers. That end is long overdue, and if ChatGPT hastens that end, then that is good news.

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No, ChatGPT Is Not The End Of High School English. But Here's The Useful Tool It Offers Teachers.

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English class is not dead; however, some teachers may need to do a bit of soul searching.

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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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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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How Zapier's RevOps team automates lead management

Using AI & Zapier in Marketing, Sales, & RevOps

Create your first Zap with ease

In just over a year, text-to-image AI art generators have gone from closed betas to being everywhere. What started with has grown into a huge cultural movement. AI-powered art generators that have been around for years are having a surge in popularity, and new apps with interesting takes are launching every week. It feels like pretty much everyone is generating amazing, hilarious, and downright weird images, just by typing in a prompt.

Create AI images from any app you use

Automate AI image generation

If you want to get in on the text-to-image action but aren't sure where to start, this list will help you out. It's a broader list than my picks for the best AI image generators in order to show off all the different angles that folks are taking with AI art generators.

Still, this isn't an exhaustive list of every app that can make AI art. Instead, it shows off the text-to-image AI art generators that worked when I tested them, are accessible through a web app, and seem not to be scams.

The category is changing so fast that by the time you read this, there might be even more great apps available. But for now, it's a pretty good overview of the biggest AI art apps available at the moment.

The top AI art generators

How does AI art work?

The first time you enter a prompt into an AI art generator and it actually creates something that perfectly matches what you want, it feels like magic. But it turns out AI art generators don't work using magic. They use computers, machine learning, powerful graphics cards, and a whole lot of data to do their thing.

Let's break it down.

AI art generators take a text prompt and, as best they can, turn it into a matching image. Since your prompt can be anything, the first thing all these apps have to do is attempt to understand what you're asking. To do this, the AI algorithms are trained on hundreds of thousands, millions, or even of image-text pairs. This allows them to learn the difference between dogs and cats, Vermeers and Picassos, and everything else. Different art generators have different levels of understanding of complex text, depending on the size of their training database, and some models are trained for specific purposes or only using licensed content, which affects the kinds of things they can generate.

The next step for the AI is to actually render the resulting image. There are two leading kinds of models:

Diffusion models, like Stable Diffusion, DALL·E 2, Midjourney, and CLIP-Guided Diffusion, which work by starting with a random field of noise, and then editing it in a series of steps to match its understanding of the prompt.

Generative Adversarial Networks (GANs), like VQGAN-CLIP, BigGAN, and StyleGAN, which have been around for a few years longer.

Both kinds of models can produce great, realistic results, though diffusion models are generally better at producing weird or wild images.

Prompt: A parrot detective wearing a deerstalker hat and smoking a pipe.

While some apps are very open about which models they use, others obscure it. VQGAN-CLIP and Stable Diffusion, for example, are both open source, so there are a large number of apps that use them openly-and lots of others that don't say anything. There are also other apps that use their own data to custom-train various open source models to give better results.

This means that many AI art generators are essentially just different user interface skins for the same art-generating algorithms. From a business point of view, this is somewhat understandable. Still, it's annoying when you're trying to choose which app to use (or write about them). Where possible, I've listed what models each app uses. When it isn't declared, I've speculated, based on my experience with all these different generative AIs.

How to use AI image generation at work

Interested in AI, but not quite sure how you'd use it at work? Here are a few of the ways people are turning to AI image generation in their roles:

Generating hero images for blog posts

Creating social media posts

Generating slide decks and storyboards

Creating personalized images for customers

Learn more about how to use AI image generation at work.

29 AI art generators you can use right now

I made this with DALL·E 2 using the prompt "an impressionist oil painting of a Canadian man riding a moose through a forest of maple trees"

AI art models: DALL·E 2

Platform: Web

Pricing: $15 for 115 credits (1 credit = 1 prompt with 4 options)

DALL·E 2 is the AI art generator that kicked off this whole craze. While it no longer has a free trial, it's still one of the most impressive apps out there. It's simple to use and can produce great results. That's why its API is used by so many of the other apps on this list.

That API also allows you to use DALL·E as part of your business workflows, by connecting it to thousands of other apps using Zapier. For example, you can create images based on Slack messages and send them back to Slack (or do the same in Discord) or create images for new Airtable records.

Zapier is the leader in no-code automation-integrating with 6,000+ apps from partners like Google, Salesforce, and Microsoft. Build secure, automated systems for your business-critical workflows across your organization's technology stack. Learn more.

AI art models: DALL·E 3

Platform: Web

Pricing: Free

Bing Image Creator is a result of Microsoft's partnership with OpenAI. It uses the latest DALL·E model, DALL·E 3, and it's free (at least for now). The default styles are a little different, so it's well worth a look, even if you've used DALL·E in the past.

AI art models: DALL·E 3

Platform: Web (via ChatGPT)

Pricing: $20/month as part of ChatGPT Plus

is a serious upgrade over DALL·E 2, at least if you have a ChatGPT Plus account. Not only are the results significantly better, but controlling and instructing it through ChatGPT gives you a lot of control.

Instead of entering one prompt and having to accept the results you get, you can ask ChatGPT to make changes, add bits in, or otherwise mix things up. It makes it much simpler to get great images, even if ChatGPT doesn't always perfectly understand your requests.

And when you connect ChatGPT to Zapier, you can add automation to your AI workflows. Learn more about how to automate ChatGPT, or get started with one of these templates.

AI art models: Stable Diffusion

Platform: Web

Pricing: Free for 25 credits; $10 for 1,000 credits (enough for ~1,200 images with the default settings)

DreamStudio is the official Stable Diffusion web app. It's pretty powerful, so you can set how many steps the AI takes, what random seed it uses, and loads of other customizations. It's also got a free trial, which is nice.

(You can also check out Stable Diffusion through , which is free but watermarks your images.)

AI art models: Midjourney

Platform: Discord

Pricing: From $10 for 3.3 hours of GPU time per month (enough for ~200 prompts with 4 image options)

While Midjourney has one of the weirdest user interfaces-you access it through the chat app Discord-it reliably produces some of the best-looking, most realistic results. It's my personal favorite AI art generator.

AI art models: Stable Diffusion

Platform: Web, iOS, Android

Pricing: Free; from $12.99/month for Pro with more AI features

recently added a text-to-image art generator. It integrates perfectly with the rest of the template-based design app, so you can add AI-generated art to anything from social media posts to birthday cards.

AI art models: Stable Diffusion, DALL·E 2, CLIP-Guided Diffusion, VQGAN-CLIP

Platform: Web

Pricing: From $6/month for 100 credits (enough for ~1,240 images per month)

NightCafe adds extra features like styles to DALL·E 2 and Stable Diffusion, as well as allowing you to use older generative art models. More importantly, NightCafe is a community for AI art enthusiasts that includes challenges, a Discord server, and a gallery.

AI art models: Stable Diffusion, DALL·E 2, and other open source models

Platform: Web

Pricing: Free for 50 trial credits; from $10/month for 5,000 credits

Like NightCafe, OpenArt adds extra features to Stable Diffusion and DALL·E 2, as well as letting you use additional open source models and have more control over the specifics of the images you generate. OpenArt also has additional options like sketch-to-image and stock art transformer (which modifies stock images to better suit your needs).

It's nice to use and its free credit allotment is generous, so it's well worth a look.

AI art models: Firefly

Platform: Web, Adobe Express, Adobe Photoshop, and other Adobe tools

Pricing: Free for 25 credits per month; from $5/month for 100 credits per month (and included with various Adobe subscriptions)

Adobe has been an AI company for over a decade, and it shows with its custom AI art generator called . While you can use it online, it's now being integrated directly into Adobe products like and Photoshop.

Perhaps Firefly's best feature is that you can use it to create custom text effects using a written prompt. AI art generators often struggle with text, and Firefly is really the only one that can do this right now.

AI art models: Doesn't say, but appears to be based on Stable Diffusion

Platform: Web

Pricing: From $39/month for unlimited images

is better known for being one of the best AI writing generators, but it also has a decent art generator as well. It's more expensive than a lot of the other apps on this list, but if you already use Jasper, it's worth a look.

Other AI writing tools, like Writesonic and Rytr, also offer AI-generated art, but Jasper's is different in that it's more of a standalone tool.

AI art models: Stable Diffusion and other open source models

Platform: Web

Pricing: Free for unlimited images one at a time; from $4.99 for faster images two at a time

Another Stable Diffusion-based art generator, Prodia stands out by letting you try all its models without having to sign up for an account. Prodia also connects with Zapier, so you can automatically create an image on Prodia based on triggers in your other apps.

AI art models: Stable Diffusion and other open source models

Platform: Web

Pricing: Free for 100 images and 1 model; then from $9/month for 250 images and 1 model

Leap AI is a great option if you want to train your own AI art models. While a lot of its features are aimed at developers, it's easy enough to use that anyone can train their own AI. Plus, Leap AI integrates with Zapier, so you can do things like generate images based on new Discord messages or Google Sheets rows.

AI art models: Based on original DALL·E model (Not DALL·E 2)

Platform: Web

Pricing: Free; from $6/month for faster images and no watermark

Craiyon (previously DALL·E Mini) is based on the original DALL·E model. It's significantly more basic than the latest art generators, but it's free and fun to play around with.

AI art models: Stable Diffusion and other open source models

Platform: Web

Pricing: Free for 100 images per month; from $12/month for the Basic plan, with 3,000 images/month and the ability to train your own models

getting.ai is an AI art generator app with 20 open source models, including Stable Diffusion and models built from it, like OpenJourney. The biggest feature, though, is that with a paid plan, you can train your own models.

AI art models: DALL·E 2

Platform: Web

Pricing: Free to generate images; from $19/image to download

Stock image company Shutterstock obviously recognizes the existential threat that generative AI poses to its business-so instead of fighting, it's partnered with OpenAI. The Shutterstock AI Image Generator is powered by DALL·E 2, and while it's free to generate images, downloading them uses Shutterstock credits. If you have a Shutterstock plan, you should give it a try. Otherwise, it's a very expensive way to use an AI art generator.

AI art models: Custom model developed with NVIDIA

Platform: Web

Pricing: Custom

Like Shutterstock, Getty Images has developed an AI art generator. Generative AI by Getty Images is trained on Getty's collection of stock images. This makes it good for generating weirdly specific stock photos, but not as competent or creative at other things.

Best of all, though, Getty claims that its model is free from intellectual property issues, so you're indemnified against any legal claims resulting from using the images you make with its tool. If your company has a legal department, it might be that AI art generator you need.

AI art models: Custom-trained models

Platform: Web

Pricing: Free for 20 images with default settings; from $19/month for the Advanced plan, which allows for hundreds of images per month

Deep Dream Generator is one of the oldest AI art generators online. It was originally designed to use Google's DeepDream algorithm but has added text-to-image algorithms that appear to be based on Stable Diffusion.

AI art models: BigGAN and StyleGAN

Platform: Web

Pricing: Free for 3 credits per month and most features; from $8.99/month for 100 credits per month, which allow you to use more powerful features more often

Artbreeder (formerly Ganbreeder) launched in 2018 as a platform for experimenting with generative AIs. It's still loose, experimental, and super art-focused. Its three main tools-Mixer, Collager, and Splicer-allow you to combine aspects of multiple images to create something unique.

AI art models: Stable Diffusion and other open source models

Platform: Web

Pricing: Free for 100 images; from $10/month for the Starter plan with 1,750 images per month

Stablecog is another AI art generator based on Stable Diffusion and other similar models. It's got a nice, easy-to-use web app and, perhaps best of all, a nice, easy-to-understand pricing structure.

AI art models: Custom models

Platform: Web

Pricing: Free; from $5/month for 500 images

DeepAI is mostly an AI API for developers, but it has a free text-to-image art generator on its website to showcase what it does. You can also sign up for a paid plan, which gives you access to more styles and allows you to use the API.

AI art models: VQGAN-CLIP and CLIP-Guided Diffusion

Platform: Web, iOS, Android

Pricing: Free for 5 credits/day; from $11.99/month for 50 credits/month

StarryAI is another art generator that uses the older VQGAN-CLIP and CLIP-Guided Diffusion models. It's free for five prompts and twenty images per day, so it's one of the best free ways to try out generative models. There are also mobile apps, which is nice.

AI art models: Doesn't say, but probably based on Stable Diffusion

Platform: Web

Pricing: Free for 3 images; from $20 for 200 credits

Fotor is a popular online image editing app, and it's recently added a text-to-image art generator that integrates with its editor.

AI art models: Doesn't say, but probably based on Stable Diffusion

Platform: Web

Pricing: Free for 3 images/month; from $5 for 100 credits

Vance AI offers a collection of AI tools, and it's recently added a text-to-image art generator. It's relatively limited, but its tools all use the same credit system. So, if you also want an image enhancer, upscaler, and background remover, it's worth checking out.

AI art models: Appears to be Stable Diffusion, but you can train your own

Platform: Web

Pricing: Free trial; from $15/editor/month for the Standard plan, with 625 credits per month

Runway is a suite of art-generating tools for businesses. In addition to features like multiple seats and shared assets, you can train your own custom models.

AI art models: Doesn't say, but probably VQGAN-CLIP-based

Platform: Web, iOS, Android, Discord

Pricing: Free; from $9.99/month for premium features like making multiple outputs from one prompt

Dream by WOMBO is a freemium art generator with a large number of styles. Although it doesn't say explicitly, it likely uses the older VQGAN-CLIP-based models to generate its images.

AI art models: Doesn't say, but probably Stable Diffusion-based

Platform: Web, iOS

Pricing: Free; from $13/month for no watermarks and premium features.

Picsart is another online image editing app. The AI art generator integrates with the rest of the editor, so you can combine AI-generated elements with text, stickers, and other images. Although it's free to use, you have to pay to download images without a watermark.

AI art models: Doesn't say, but probably VQGAN-CLIP-based

Platform: Web

Pricing: Free; from $9/month for faster generating and private downloads

Creative Fabrica is a digital assets marketplace that's recently added an art generator. It's free to use, but its best feature is that you're able to browse hundreds of other AI creations.

AI art models: VQGAN-CLIP-based models

Platform: Web

Pricing: Free

Pixray is an open source art generator that uses VQGAN-CLIP-based models. While there's an API and Python implementation, there's also a free demo on the website. The best thing is that you can play around with all the hidden settings that go into an AI art generator if you want to learn more and see how they work.

AI art models: Doesn't say, but appears to be Stable Diffusion-based

Platform: Web

Pricing: Free for 10 credits/month and watermarked images; from $12/month for 100 credits/month

Let's Enhance is an AI-powered image upscaling app that recently added an art generator. It's still in beta, so generating images doesn't cost anything (though saving them costs one credit).

Other categories of AI art generators

This list is focused on text-to-image art generators, but there are entire other categories of AI art makers out there. Some examples:

And these are just the AI art generators that are available now. Other companies are certainly testing their own art generators, and you could always train your own using one of the apps I mentioned that allows for that.

Make the most of your AI art

You might be generating AI art for fun-in which case, have at it (and check out these AI photo editors to help make your masterpieces extra pretty). But if you're thinking about using an AI art generator at work, there's plenty you can do with it. Here's some inspiration:

You should also take a peek at Zapier's tips on how to write effective AI art prompts, so you can get the results you want quicker.

Which AI art generator should you use?

With so many AI art generators to choose from, it can be hard to know where to start. So let me break it down:

Midjourney is my favorite, though the free trial is temporarily paused, and using it through Discord is weird.

DALL·E 2 is great, but it's cheaper to access it through Bing Image Creator.

Stable Diffusion is used in lots of different apps. The simplest way to access it is through its own app, DreamStudio.

Firefly's text effects are awesome, as is its integration with other Adobe tools.

NightCafe and OpenArt are the best apps if you want to play around with different models, including some of the older GAN models.

Deep Dream Generator is a great way to see how far art generators have come.

Artbreeder is perhaps the weirdest art generator among a very weird series of art generators-and totally worth a look.

Otherwise, just scroll through the list and try whichever ones strike your fancy. You can't go too far wrong.
Related reading:

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The top AI art generators in 2024 | Zapier

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Explore the top AI art generators and learn how they use machine learning to create stunning images from text prompts. Dive into the world of AI-generated art.

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Equity in a World of Artificial Intelligence

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Equity in a World of Artificial Intelligence

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WICHE Cooperative for Educational Technologies

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Since our last blog in January on generative artificial intelligence (AI), the field has changed by leaps and bounds:

The higher education press continues to increase its coverage with multiple articles, blogs, and op-ed pieces in The Chronicle of Higher Education and Inside Higher Education among other outlets. Much of that coverage, though, continues to focus on the pedagogical implications of generative AI, including academic integrity concerns. Equally important, but discussed very little, are the equity considerations around how AI can and should be leveraged in higher education. Today we'll look at both the positive and potentially negative aspects of generative AI in higher education as it relates to educational equity.

AI as a Tool for Equity

According to the U.S. Department of Education's Office of Educational Technology, "Technology can be a powerful tool for transformation learning. It can help affirm and advance relationships between educators and students, reinvent our approaches to learning and collaboration, shrink longstanding equity and accessibility gaps, and adapt learning experiences to meet the needs of all learners." Artificial intelligence, when used deliberately and carefully, can advance equity by improving educational accessibility and assisting second language learners, among others.

AI can be especially powerful when addressing learner accessibility. For example, students with dyslexia can benefit from AI as a December 10, 2022, Washington Post article demonstrated when it described how ChatGPT is being used by a British landscaper with dyslexia to rewrite emails so that they are more professional and more easily understood. Additionally, students and faculty with AD/HD are finding generative AI useful in approaching research and writing. As Maggie Melo wrote in her February 28, 2023, op-ed in Inside Higher Education, "My thinking and writing processes are not linear. ChatGPT affords me a controlled chaos." Melo goes on to describe how the need to create an abstract can feel overwhelming despite having having done so numerous times. However, after asking ChatGPT "How to write an abstract," she received an outline that, as she put it, "provides my mind with an anchor to focus on and return to." And much like our British landscaper, non-native English speakers may also benefit from ChatGPT's ability to revise and rephrase text. ChatGPT can be used to revise text for grammatical correctness and clarity.

Challenges to AI as a Tool for Equity

In her 2019 work, Race After Technology, Princeton University sociologist Ruha Benjamin wrote about what she calls the "New Jim Code" and the problem of data and algorithmic bias.

Benjamin defined the "New Jim Code" as "the employment of new technologies that reflect and reproduce existing inequities but that are promoted and perceived as more objective or progressive than the discriminatory systems of a previous era" (5). Generative AI is trained on large existing data sets, mostly scraped off the internet. This means that models are ingesting biased information as well as information that is likely to over-represent certain groups such as white, economically well-off individuals. As the old adage goes, "garbage in, garbage out."

The result is algorithmic bias. Algorithmic bias "describes systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. Also, occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process." In addition to challenges with training data, algorithmic bias is also impacted by the implicit bias of generative AI developers, a field in which white men are over-represented and women and some racial groups such as Blacks and Latinos are under-represented. As Henry Kissenger, Eric Schmidt, and Daniel Huttenlocher wrote in Age of AI: And Our Human Future, "The algorithms, training data, and objectives for machine learning are determined by the people developing and training the AI, thus they reflect those people's values, motivations, goals, and judgment" (77).

Student Access and the Expansion of the Digital Divide

In addition to challenges around algorithmic bias, AI also experiences challenges of access. According to the 2021 American Community Survey One Year Estimates, "Types of Computers and Internet Subscriptions," of the 127,544,730 households in the United States, 6,320,698 (4.9%) had no computing device including a smartphone and 12,374,652 (9.7%) had no internet subscription including no cellular data plan. This digital divide is especially acute for low-income Americans with 15.3 percent of Americans with income less than $75,000 lacking internet access. And a Pew Research Center 2021 study found that 15 percent of all American adults were smartphone only internet users but that number rose sharply to 28 percent when looking at 18-29 years old. Even then, that number is not equally divided among all racial groups. 25 percent of Hispanic young adults and 17% of Black young adults were smartphone only internet users as compared to 10 percent of White young adults.

Why does the digital divide matter when we explore equity and AI? Simply put, most generative AI is difficult to use without an internet connection. Although text based generative AI like ChaptGPT can run on mobile devices, its response time may be slower than one would experience when using a high-speed internet connection. Making more sophisticated queries with long outputs would be difficult, at best.

In addition to challenges resulting from the digital divide, there are challenges associated with the cost of using generative AI tools themselves. Chat GPT, which started out free, is now partially behind a paywall begging the question of how much longer these tools will remain freely available. In fact, the economic realities of the astronomical costs of running generative AI almost guarantees that such paywalls will become more common. CNBC reports that just training a large language model could be more than $4 million. Some estimates of daily cost to run it put it at $100,000 per day or $3,000,000 per month.

What will be the result of fewer students having access to generative AI? We run the risk of the digital divide turning into an AI divide. Some students who lack sufficient access will not gain the skills related to working with generative AI that will be increasingly necessary as we enter an age of hybrid human/AI work.

What Does this Mean for You?

Generative AI has the potential to revolutionize society, including higher education, in ways that we still are determining. But as higher education professionals, we need to be cognizant of how we leverage generative AI. How can you build upon the promise of generative AI while mitigating some of its challenges?

Explore the ways that generative AI can be leveraged to improve learner accessibility. This may mean working with various offices on campus including the office that handles student accommodations.

Be especially cognizant of the limitations that students may have accessing generative AI and plan accordingly. This might mean ensuring that there are adequate campus resources and, for face-to-face and hybrid courses, even consider focusing on AI usage during class via campus computer labs or in-classroom device loan programs.

Help students think critically about the results of generative AI, especially large language models trained on biased data sets. A key piece of data literacy in the age of artificial intelligence needs to be a discussion of algorithmic bias and the New Jim Code.

As we continue to explore the ways in which generative artificial intelligence can impact higher education, it is critical for us to remember that no technology is neutral.

As Kate Crawford in puts it, "Artificial intelligence is not on objective, universal, or neutral computational technique that makes determinations without human direction. Its systems are embedded in social, political, cultural, and economic worlds, shaped by humans, institutions, and imperatives that determine what they do and how they do it" (211). Does this negate the potential advantages of generative AI and the ways that it can improve educational equity? No, but it does mean we should be cognizant of the potential for further educational inequity and work to counter that potential.

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Equity in a World of Artificial Intelligence

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Since our last blog in January on generative artificial intelligence (AI), the field has changed by leaps and bounds: Open AI released GPT4, Microsoft released its AI empowered Bing, and, Google recently released Bard. The higher education press continues to [...]

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Train a computer to recognize your own images, sounds, & poses.

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Train a computer to recognize your own images, sounds, & poses.

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Train a computer to recognize your own images, sounds, & poses. A fast, easy way to create machine learning models for your sites, apps, and more - no expertise or coding required.