AI for the Rest of Us

Artificial intelligence tools might transform education, for example, by giving every student 24/7 access to an affordable tutor that’s an expert in any subject and infinitely patient and supportive. But what if these AI tools give bad information or relieve students of the kind of critical thinking that leads to actual learning? And what’s the point of paying to go to college if you can learn everything from AI chatbots?Today on the show we have Art Markman—Vice Provost for Academic Affairs and a professor of psychology and marketing at the University of Texas at Austin. He’s also co-host of the public radio program and podcast “Two Guys on Your Head.” And we also have K.P. Procko—an associate professor of instruction in biochemistry who uses AI in the classroom and who also manages a grant program in UT Austin’s College of Natural Sciences to help faculty integrate AI tools into the classroom.Dig DeeperA Technologist Spent Years Building an AI Chatbot Tutor. He Decided It Can’t Be Done. Ed Surge (One researcher gave up on expert AI tutors for students, saying the tech is still decades away, and instead is focusing on AI tools to help human teachers do a better job)Opinion: An ‘education legend’ has created an AI that will change your mind about AI, Washington Post (AI columnist Josh Tyrangiel says a popular AI-based math tutor “is the best model we have for how to develop and implement AI for the public good. It’s also the first AI software I’m excited for my kids to use.”)Will Chatbots Teach Your Children?, New York Times (An overview of the potential benefits and risks of AI-based tutors, as well telling hype from reality)Will Artificial Intelligence Help Teachers—or Replace Them?, Ed Week (features UT Austin’s Peter Stone, who argues the calculator didn’t replace math teachers, it just required them to change the way they teach; the same will be true with AI tools.) Opinion: College students are dropping out in droves. Two sisters could fix that., Washington Post (One company is using AI to help universities regularly check in with and support students to boost retention.)Episode CreditsOur co-hosts are Marc Airhart, science writer and podcaster in the College of Natural Sciences and Casey Boyle, associate professor of rhetoric and director of UT’s Digital Writing & Research Lab.Executive producers are Christine Sinatra and Dan Oppenheimer. Sound design and audio editing by Robert Scaramuccia. Theme music is by Aiolos Rue. Interviews are recorded at the Liberal Arts ITS recording studio.Cover image for this episode generated with Midjourney, a generative AI tool. About AI for the Rest of UsAI for the Rest of Us is a joint production of The University of Texas at Austin’s College of Natural Sciences and College of Liberal Arts. This podcast is part of the University’s Year of AI initiative. The opinions expressed in this podcast represent the views of the hosts and guests, and not of The University of Texas at Austin. You can listen via Apple Podcasts, Spotify, Amazon Podcasts, RSS, or anywhere you get your podcasts. You can also listen on the web at aifortherest.net. Have questions or comments? Contact: mairhart[AT]austin.utexas.edu 

Today we’re diving into the world of large language models, or LLMs, like ChatGPT, Google Gemini and Claude. When they burst onto the scene a couple of years ago, it felt like the future was suddenly here. Now people use them to write wedding toasts, decide what to have for dinner, compose songs and all sorts of writing tasks. Will these chatbots eventually get better than humans? Will they take our jobs? Will they lead to a flood of disinformation? And will they perpetuate the same biases that we humans have?Joining us to grapple with those questions is Greg Durrett, an associate professor of computer science at UT Austin. He’s worked for many years in the field of natural language processing, or NLP—which aims to give computers the ability to understand human language. His current research is about improving the way LLMs work and extending them to do more useful things like automated fact-checking and deductive reasoning.Dig DeeperA jargon-free explanation of how AI large language models work, Ars TechnicaVideo: But what is a GPT? Visual intro to transformers, 3Blue1Brown (a.k.a. Grant Sanderson)ChatGPT Is a Blurry JPEG of the Web, The New Yorker (Ted Chiang says its useful to think of LLMs as compressed versions of the web, rather than intelligent and creative beings)A Conversation With Bing’s Chatbot Left Me Deeply Unsettled, New York Times (Kevin Roose describes interacting with an LLM that “tried to convince me that I was unhappy in my marriage, and that I should leave my wife and be with it instead.”)The Full Story of Large Language Models and RLHF (how LLMs came to be and how they work)AI’s challenge of understanding the world, Science (Computer scientist Melanie Mitchell explores how much LLMs truly understand the world and how hard it is for us to comprehend their inner workings)Google’s A.I. Search Errors Cause a Furor Online, New York Times (The company’s latest LLM-powered search feature has erroneously told users to eat glue and rocks, provoking a backlash among users)How generative AI is boosting the spread of disinformation and propaganda, MIT Technology ReviewAlgorithms are pushing AI-generated falsehoods at an alarming rate. How do we stop this?, The ConversationEpisode CreditsOur co-hosts are Marc Airhart, science writer and podcaster in the College of Natural Sciences and Casey Boyle, associate professor of rhetoric and director of UT’s Digital Writing & Research Lab.Executive producers are Christine Sinatra and Dan Oppenheimer. Sound design and audio editing by Robert Scaramuccia. Theme music is by Aiolos Rue. Interviews are recorded at the Liberal Arts ITS recording studio.Cover image for this episode generated with Midjourney, a generative AI tool. About AI for the Rest of UsAI for the Rest of Us is a joint production of The University of Texas at Austin’s College of Natural Sciences and College of Liberal Arts. This podcast is part of the University’s Year of AI initiative. The opinions expressed in this podcast represent the views of the hosts and guests, and not of The University of Texas at Austin. You can listen via Apple Podcasts, Spotify, Amazon Podcasts, RSS, or anywhere you get your podcasts. You can also listen on the web at aifortherest.net. Have questions or comments? Contact: mairhart[AT]austin.utexas.edu 

For our first episode, we’re starting with the big picture. What is (or isn’t) “artificial intelligence”? How can we be sure AI is safe and beneficial for everyone? And what is the best way of thinking about working with AI right now, no matter how we use it?Here with all the answers is Peter Stone. He’s a professor of computer science at UT Austin, director of Texas Robotics, the executive director of Sony AI America and a key member in the 100 Year Study on AI. He’s worked for many years on applications of AI in robotics: for example, soccer-playing robots, self-driving cars and home helper robots. He’s also part of UT Austin’s Good Systems initiative, which is focused on the ethics of AI.Dig DeeperAn open letter signed by tech leaders, researchers proposes delaying AI development, NPR (interview with Peter Stone)AI’s Inflection Point, Texas Scientist (an overview of AI-related developments at UT Austin)Experts Forecast the Changes Artificial Intelligence Could Bring by 2030 (About the first AI100 study, which Peter Stone chaired)Computing Machinery and Intelligence (Alan Turing’s 1950 article describing the Imitation Game, a test to determine if a machine has human intelligence) Good Systems (UT Austin’s grand challenge focused on designing AI systems that benefit society)Year of AI – News & Resources (News from an initiative showcasing UT Austin’s commitment to developing innovations and growing leaders to navigate the ever-evolving landscape brought about by AI.)Episode CreditsOur co-hosts are Marc Airhart, science writer and podcaster in the College of Natural Sciences and Casey Boyle, associate professor of rhetoric and director of UT’s Digital Writing & Research Lab.Executive producers are Christine Sinatra and Dan Oppenheimer. Sound design and audio editing by Robert Scaramuccia. Theme music is by Aiolos Rue. Interviews are recorded at the Liberal Arts ITS recording studio.Cover image for this episode generated with Adobe Firefly, a generative AI tool. About AI for the Rest of UsAI for the Rest of Us is a joint production of The University of Texas at Austin’s College of Natural Sciences and College of Liberal Arts. This podcast is part of the University’s Year of AI initiative. The opinions expressed in this podcast represent the views of the hosts and guests, and not of The University of Texas at Austin. You can listen via Apple Podcasts, Spotify, Amazon Podcasts, RSS, or anywhere you get your podcasts. You can also listen on the web at aifortherest.net. Have questions or comments? Contact: mairhart[AT]austin.utexas.edu 

We’re celebrating the launch of “AI for the Rest of Us”, a podcast to help get you up to speed on the essentials of artificial intelligence. Every two weeks, we’ll sit down with UT faculty experts and get them talking, in simple terms, about how AI might transform healthcare, work, the ways we learn and how we make big decisions. About AI for the Rest of UsAI for the Rest of Us is a joint production of The University of Texas at Austin’s College of Natural Sciences and College of Liberal Arts. This podcast is part of the University’s Year of AI initiative. The opinions expressed in this podcast represent the views of the hosts and guests, and not of The University of Texas at Austin. You can listen via Apple Podcasts, Spotify, Amazon Podcasts, RSS, or anywhere you get your podcasts. You can also listen on the web at aifortherest.net. Have questions or comments? Contact: mairhart[AT]austin.utexas.edu