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Nearly 60% of school leaders now use the technology, with school communications and hiring among popular uses, a Rand report found.

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Human Creativity vs. AI: The New Copyright Landscape

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Listen to this episode from AI Applied: Covering AI News, Interviews and Tools - ChatGPT, Midjourney, Gemini, OpenAI, Anthropic on Spotify. The conversation delves into the evolving landscape of copyright in relation to AI-generated content. It discusses the recent guidelines from the US Copyright Office, emphasizing the importance of human creativity in the creative process.

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Generative AI technologies have disrupted classrooms in a way not seen since the dial-up internet boom of the 1990s. As teachers, how can we cut through the hype surrounding AI in education to understand its limitations, ethical harms, and potential affordances for learning, access, and equity?

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The Exploited Labor Behind Artificial Intelligence | NOEMA

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Supporting transnational worker organizing should be at the center of the fight for “ethical AI.”

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To help you prepare for teaching and learning in the age of artificial intelligence (AI), here is a pedagogical approach, plus some extra resources, to help you tackle assignment design. These ideas aim to help you reinforce your learning goals and prepare students for the future, which I believe, involves collaboration with AI.

I heard at a conference that AI should actually stand for Assisted or Augmented Intelligence, which I think makes more sense. AI is certainly powerful, but it requires, at minimum, prompting to start a task and a lot of humans to program it in the first place. Below is one illustration of tasks where the AI and human contributions may vary. Human contribution is most useful for multi-dimensional, complex tasks with unexpected events, but much of our everyday work can be handled by technology.

AI is infiltrating everyday life, almost every profession, and the academic fields of the future. In business, marketers are using AI to write content and format it for specific consumer goals. In engineering, coders are using AI to generate initial code and get feedback to expedite their creative processes. Researchers of various fields are using AI to run simulations, analyze data, and polish up papers.

Now, AI is embedded in many tools we commonly use on our campus, including those supported by WashU (Microsoft Word, Gmail, Padlet, Gradescope, etc.). Most of us will use these tools without knowing it, and many of us will deliberately seek out these tools to help complete a task, solve a problem, begin brainstorming, reduce administrative work, get help, and more. Hence, using AI is not only inevitable, but valued in most aspects of life. You can learn more at Inside Higher Ed Emerging Technology and AI report (June 2023).

Knowing how to use AI well for specific goals will certainly play a role in the future workplace. To prepare students, we need to recognize AI's role and, if possible, leverage it so that it enhances teaching and learning. This means a high level of both human + AI contribution in a way that helps both students and technologies grow. At times, this may mean that you keep AI contribution low so that students build essential skills, and at other times you keep human contribution low so that AI can flourish in what it does best and humans can learn how to use it effectively. The method below will help you consider how to create with AI as depicted in the top right quadrant in this figure:

The spectrum method considers human to AI collaboration as a range to which students and AI can contribute to different degrees to individual assignments. For instance, consider what contribution may look like for an essay assignment either created completely by AI or by a student:

In between the extremes of only AI or only human contribution are forms that will likely become more common, particularly human essay with AI review, which has been generally accepted as tools like Grammarly have come on the scene to help students check essays for grammar and style improvements. Even AI-generated essays with human refining could become commonplace in specific contexts where it makes sense to have AI generate a generic idea or general framework for humans to then tweak (think: anything that may already have a template or standard language, e.g., emails, contracts, slogans).

The value of outlining these different types along the spectrum is that it helps you see where AI may contribute and decide what level of student and AI contribution makes sense. In my workshops, I ask participants to copy/modify a table or create their own using AI prompts, all provided in this open, collaborative document that I invite you to contribute to.

Short link: https://tinyurl.com/HumanAISpectrum

In the collaborative document, you can also find additional tables for different assignments from coding to independent research. Feel free to copy and build on these tables.

Once you have a table that clearly outlines where humans and AI can contribute, it can also serve as a communication tool specifying what the boundaries are for your class assignment. See the figure below for an example where human essay with AI review is allowed, but additional AI contribution is not permitted (i.e., students can use Grammarly or similar tools).

No matter what you choose, I suggest walking students through the table, your boundary, and specifying why that boundary is drawn where it is. There are great reasons from "no AI is allowed in this intro language course so that you learn to construct grammar yourself" to "it's not a problem to use AI to generate code, but you need to adjust it to fit into the rest of the code that a company may be using."

Use this chance to reinforce your learning objectives for students and connect the assignment to a larger why. Here are some questions that you can consider as you go through the process of modifying/building your table and drawing your boundary:

What does the future of work look like in your discipline? How will your academic and professional contexts leverage AI to enhance its work?

Where will students need to know how to use AI (and how to not use AI) to do their work?

Where does your class fit into students' academic experience? What human-specific skills should they learn now? What AI-related skills should they learn now?

What are your learning goals for students? What should they be able to do/know on their own and thus need to practice/apply? What should they be able to do/know with the help of AI?

Want some more basic information about generative AI tools, particularly ChatGPT? See our CTL resources with recommendations for ChatGPT and AI Composition Tools or Incorporating ChatGPT into Your Assignments. You can also contact us to discuss your teaching goals or learn more at ctl@wustl.edu.

Don't like this spectrum approach, particularly for assessments? Consider the two-lane method from Professor Danny Kim at the University of Sydney, which balances AI contribution with student assessments within a controlled environment. You can learn more about this method in a session on Harnessing the Power of AI: Transforming Assignments and Assessments in Higher Education ( YouTube video), where I got the wonderful images in the "Why Collaborate with AI?" section above.

Learn more about how AI will be used by your students in academic and professional contexts. Current and future usage in various disciplines range from political campaigns writing emails to a changing landscape of software development. Students may even be recruited by companies that provide ChatGPT Plus as a work perk. Talk with your colleagues (and students!) about what they see in your field. These approaches work best in conjunction with wider departmental discussions about how students should (or should not) be collaborating with AI as they move from introductory to advanced courses in your discipline. Perhaps boundaries move up or down to align with AI collaboration skills essential to their future as professionals, scholars, and citizens of the world.

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(Re-)Designing Assignments where Students Collaborate with Artificial Intelligence - Center for Teaching and Learning

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To help you prepare for teaching and learning in the age of artificial intelligence (AI), here is a pedagogical approach, plus some extra resources, to help you tackle assignment design. These ideas aim to help you reinforce your learning goals and prepare students for the future, which I believe, involves [...]

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Exclusive: The $2 Per Hour Workers Who Made ChatGPT Safer

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A TIME investigation reveals the difficult conditions faced by the workers who made ChatGPT possible

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No One Writes Alone: Peer Review in the Classroom - A Guide For Instructors

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No One Writes Alone: Peer Review in the Classroom - A Guide For Students

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Americans are now spending more time alone than ever. It’s changing our personalities, our politics, and even our relationship to reality.

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12 truths I learned from life and writing | Anne Lamott

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Stephen Fry reads Nick Cave's stirring letter about ChatGPT and human creativity

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What comes after the Homework Apocalypse

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How AI Could Transform the World for the Better

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Session 1 Introducing Artificial Intelligence Tools

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Artificial Intelligence in Education: Our Vision

Digital Promise's vision for artificial intelligence (AI) in education puts people first:

Safe, equitable, and meaningful AI in education uses emerging technologies to improve education by enhancing how we teach and learn. Grounded in inclusive innovation, Digital Promise pursues AI in education to foster a future where every person engages in sustained and impactful experiences of powerful learning that lead to a life of well-being, fulfillment, and economic mobility.

We observe a race to launch AI tools at scale before agreeing on what problems people want to solve, what values educators must protect, and what goals educational systems should be designed to achieve. Shared vision, values, and goals arise from people working together. Our human-centered approach emphasizes how the increasing capabilities of computers can augment human intelligence, enabling people to engage in teaching and learning experiences more deliberately. Working across research, edtech, and practice, Digital Promise:

Builds partnerships among educators, innovators, researchers, and other impacted community members to establish a shared vision of powerful learning in an AI-enabled world

Defines core values including anti-racism and anti-bias and finds ways to hold AI-enabled products accountable

Engages in research partnerships and hosts research communities to investigate how and whether AI can help us to achieve our goals, and

Works with policymakers to safeguard learners' rights, data privacy, and to ensure equitable opportunities to learn.

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Artificial Intelligence in Education - Digital Promise

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Western man’s will to disappear is getting installed in the omni-operating system

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Living in the Bay Area, I sometimes rub elbows with people who are friendly, thoughtful and very intelligent, but who seem to live in a different dimension. I mean the workers who are busy digging in the Uncanny Valley, looking for gold.

On Tuesday I participated in a panel discussion on AI. It was a small event in San Francisco, put on by some venture capitalists and academics from Harvard. There were people from OpenAI and Tinder, among other firms, as well as the CEO of Replika, which peddles AI "companions" and has 30 million users. You can design your own Replika - someone who is "Always here to listen and talk. Always on your side."

Asked what metaphor comes to mind when thinking about AI, I offered two:

In the Hebrew tradition, a golem is a crude anthropomorphic creature made of clay or mud, brought to life by ritual incantations. In the Mishnah, the word "golem" refers to someone who is unsophisticated; in modern Hebrew it simply means dumb. "If commanded to perform a task, a golem will perform the instructions literally. In many depictions, golems are inherently perfectly obedient," according to Wikipedia.

Also from Wikipedia: In the world of the occult, an egregor is an independent, artificial being that arises from a collective mind. It may be created deliberately, as an "efficacious magical ally, but the egregor's help comes at a price, since its creators must thenceforth meet its unlimited appetite for future devotion."

I went on to deliver a much-condensed version of my post " AI as self-erasure. " My point was to consider how use of chatbots is likely to affect human subjectivity, and considered the case of a man who outsources the composition of a toast for him to deliver at his daughter's wedding to chatGPT. To do this would be to not show up for her wedding, in some sense that seems important. We are the language animal, so LLMs are aimed right at our essence, as Talbot Brewer put it in a lecture on "degenerative AI" several months ago in Charlottesville.

I think it is safe to say I won't be getting any funding from the VCs.

The wisest person in attendance was Sherry Turkle, and the most interesting exchange was between her and the founder-CEO of Replika, a woman named Eugenia Kuyda. Turkle pointed out that apologetics for tech often come in the form of a slippery slope that begins by invoking some disability or another. She told a story from her own research (she interviews people about their use of various technologies) of a family who got an AI robot dog for grandma. They got the robot because grandma is allergic to dogs, and wouldn't it be nice for grandma to have companionship? It's better than nothing! When Turkle revisited the family a few months later, they'd gotten rid of their own dog and replaced it with a robot. She says the usual trajectory is from "Better than nothing" to "better than anything," where "better" means without friction between self and world. The real is displaced by the fake.

When people begin using AI companions, they have no illusions that they are talking to a real person. But something funny happens along the way, and users invest themselves in the relationship as though it were real, leading to a kind of split in the person - living apart from reality as his rational mind knows it to be. The reflexive character of chatbots (they learn and adapt to you) makes them especially powerful generators and sustainers of fantasy.

Turkle made the point that AI companions aren't qualified to converse with you about life's challenges because they don't have standing to do so: they haven't lived a life. They haven't suffered loss or fell in love or struggled with parenthood. I thought this was a nice point.

Kuyda, the Replika founder, is alert to humanistic critiques of AI companions such as Turkle offers, and seems to take them seriously, but is apparently not ready to allow them to interrupt the great march forward. To be fair, she strongly endorsed two limiting principles: not offering Replika to children (that would be an unregulated social experiment on developing minds), and not tying the firm's revenue to "engagement" (which is Valley speak for addiction-by-design). These are both very important restraints, as far as they go. Or would be, if they could be sustained against the demands of investors for maximum returns.

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In which your humble correspondent addresses the Ministry of Love