Before using AI in K-12 classrooms, teachers, administrators, and district leaders should understand what AI is and is not. Implementing AI apps without a solid foundational understanding does not serve students. But who to turn to for critical analysis of AI instead of hype?
Following these experts has helped me understand AI. Their work has influenced my posts about using a chatbot as a guest speaker and the 100% ethical AI app. With one exception, these are experts on AI, not K-12 education. Get clarity on AI, then think about using it in the classroom.
This list has none of the three B’s. That means:
- This list has no Tech Bros.
- This list has no AI Boosters.
- This list has no Billionaires.
These experts often speak about the ethical concerns of AI. Neither “an AI apocalypse” nor “student cheating” come up when they address AI ethical concerns.
With that, let’s meet the experts. Please follow them.
Timnit Gebru
Scientist and AI ethicist Dr. Timnit Gebru was the co-head of Google’s AI Ethics team until she co-authored a paper Google objected to. The paper, On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?🦜 (opens PDF), argued that Large Language Models such as ChatGPT and Gemini amplify bias and environmental racism. Two of Gebru’s co-authors are on this list. Anyone interested in AI should read their work.
She is now the Founder and Executive Director of the Distributed AI Research Institute (DAIR) and the founder of Black in AI, a community of Black researchers working in AI.
Here is Gebru’s TEDx talk about AI and marginalized communities.
Margaret Mitchell
Dr. Margaret Mitchell was Gebru’s co-head of Google’s AI Ethics team with Gebru until she co-authored the Stochastic Parrots paper. She lost her job two months after Gebru. She technically complied with Google’s request to take her name off the paper. Instead of “Margaret Mitchell,” “Shmargaret Shmitchell” is listed as one of the paper’s authors.
Mitchell makes sense of Gemini’s recent problems in her Time Magazine piece, Ethical AI Isn’t to Blame for Google’s Gemini Debacle.
Here is a TED talk Mitchell gave about AI while still at Google.
Emily Bender
Dr. Emily Bender is a computational linguist and Linguistics Professor at the University of Washington.
Bender co-authored a 2022 research paper, Situating Search (opens PDF), which argued that Large Language Models (LLMs) are not a search tool.
Bender is a co-author of the Stochastic Parrots paper. According to a profile of Bender in New York Magazine, “A stochastic parrot (coinage Bender’s) is an entity “for haphazardly stitching together sequences of linguistic forms … according to probabilistic information about how they combine, but without any reference to meaning.” “Stochastic Parrots” is an easy way to remember what LLMs do. Anyone interested in AI should read the profile.
At 11:45 of this episode of the Tomayto Tomahto podcast, she said, “The issues and dangers that we identified [in the Stochastic Parrots paper] have not been addressed.”
Here, Bender spoke about interacting with chatbots.
In this video, Bender and Mitchell talk about data sets and bias.
This is OpenAI CEO Sam Altman’s response to the term “Stochastic Parrots.”
As someone who wrote on March 9, 2020, “The fears over Coronavirus may be more hype than substance,” I should probably not throw stones at someone for saying something so incorrect. At least mine didn’t denigrate all of humanity.
Alex Hanna
Sociologist Dr. Alex Hanna is the Founder and Director of Research at the Distributed AI Research Institute (DAIR). She studies the ways data exacerbates racial, gender, and class inequality.
Hanna talks about algorithmic bias and AI in this video.
Joy Buolamwini
Dr. Joy Buolamwini is an AI researcher and the founder of the Algorithmic Justice League, which raises public awareness about the impacts of AI with a focus on harms to marginalized communities.
In an interview, Buolamwini said, “We can address algorithms of exploitation by establishing creative rights that uphold the four C’s: consent, compensation, control, and credit. Artists should be paid fairly for their valuable content and control whether or how their work is used from the beginning, not as an afterthought.”
Buolamwini shared an approach all schools should take when evaluating AI apps: “We continue to ask questions that go beyond hype or doom and ask if the AI systems being adopted in our schools, workplaces, and hospitals actually deliver what they promise.”
Watch Buolamwini’s TED talk to learn about algorithmic bias.
“We continue to ask questions that go beyond hype or doom and ask if the AI systems being adopted in our schools, workplaces, and hospitals actually deliver what they promise.”
Dr. Joy Buolamwini, ‘Unmasking AI’ and the Fight for Algorithmic Justice
A conversation with Dr. Joy Buolamwini, By Nabiha Syed, The Markup, November 18, 2023
Here Buolamwini delivers her poem, “AI, Ain’t I A Woman?”
Sasha Luccioni
Dr. Sasha Luccioni is a scientist and AI researcher. She and Dr. Mitchell are two of the writers of an interesting post about AI watermarking – the practice of labeling synthetic content.
In Luccioni’s TED talk, she addressed the actual harms of AI. Neither “students cheating” nor “AI taking over the world” is among them.
Meredith Broussard
Meredith Broussard is a journalism professor at New York University. Her research focuses on artificial intelligence in investigative reporting and ethical AI, with an interest in using data analysis for social good.
In this video, Broussard spoke about what AI is and how that is related to intelligence.
Luiza Jarovsky
Luiza Jarovsky is a lawyer and CEO of Implement Privacy who focuses on AI and privacy.
Jarovsky said something about writing and generative AI that resonates: “If you have something to say, say it…If you don’t have anything to say, don’t stuff it with AI-generated text.” She was referring to LinkedIn comments, but to me, that quote applies to all writing.
Gary Marcus
Emeritus Professor of Psychology and Neural Science at New York University Dr. Gary Marcus critically examines AI. His Twitter feed helped cut through the hype about Sora and debunk the myth that AI is growing exponentially.
In this TED Talk, Marcus spoke about how he loves AI, but is worried about its direction and risks.
Paris Marx
Paris Marx is a tech critic, author, and the host of the Tech Won’t Save Us podcast, which The New York Times named one of the 6 Podcasts to Make Sense of AI. Anyone interested in educational technology should subscribe to the podcast. His interview with Emily Bender is an informative introduction to AI and Large Language Models.
Dan Meyer
Dan Meyer is the only expert on this list with a K-12 background. His Math-focused Substack critically examines educational technology. His thoughts on AI in the classroom are sober and informed. As the excitement about AI in education grew, Meyer retained his critical lens. For samples of the wisdom Meyer brings to the conversation about AI in education, please read his posts, Happy 60th Birthday, ChatGPT!, Khanmigo Doesn’t Love Kids, and Generative AI Asks Teachers to Eat Scraps From the Table.
Essential Resources
Here are resources you can use to learn about AI from the experts:
- On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?🦜 (opens PDF)
- You Are Not a Parrot – New York Magazine
- A Twitter list of these experts
- A YouTube playlist of these videos so you can watch them uninterrupted by my prose.
Continuing The Conversation
What do you think? Whose insight do you turn to understand AI? Comment below or Tweet me at @TomEMullaney.
Does your school or conference need a tech-forward educator who critically evaluates AI? Reach out on Twitter or email mistermullaney@gmail.com.
Blog Post Image: The blog post image is a mashup of three images. The background is Education and reading concept by Sensay on Adobe Stock. The books and lightblub icon is 3d minimal self-development concept by peerapong on Adobe Stock. The robot is White male cyborg thinking and touching his head 3D rendering by sdecoret on Adobe Stock.
AI Disclosure:
I wrote this blog post without the use of any generative AI. That means:
- I developed the idea for the post without using generative AI.
- I wrote an outline for this post without the assistance of generative AI.
- I wrote the post from the outline without the use of generative AI.
- I edited this post without the assistance of any generative AI. I used Grammarly to assist in editing the post. I have Grammarly GO turned off.
- I did not use any WordPress AI features to write this post.
Tom Mullaney 
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