AI takes a huge amount of energy to run and could make it harder to fight climate change. On the other hand, AI could help make our energy systems more sustainable, efficient and safer. Three experts talk all things AI and energy with a live audience. The talk was part of a daylong symposium titled “Policy Leadership in the Age of AI”, hosted by the LBJ School of Public Affairs at The University of Texas at Austin.

Meet the panelists:

Michael Pyrcz is a professor in UT’s Cockrell School of Engineering and the Jackson School of Geosciences, who researches and teaches about ways to apply data analytics and machine learning to improve the exploration and safe production of minerals, groundwater and conventional energy, a.k.a. oil and gas. He also shares educational content on YouTube and elsewhere under the alias GeoStatsGuy.

Varun Rai is a professor in UT’s LBJ School, who studies the spread of clean energy technologies and how real-world factors – from economics to politics to regulation to social behaviors – drive the adoption of these technologies.

Rob James is an attorney at the law firm Pillsbury, who leads a number of energy and infrastructure projects for the firm in Texas and California. Those projects have included AI data centers and zero-emission power generation and storage.

Dig Deeper

The A.I. Power Grab, NYTimes (Oct. 2024)

A bottle of water per email: the hidden environmental costs of using AI chatbots, Washington Post (Sep. 2024)

Four ways AI is making the power grid faster and more resilient, MIT Technology Review (Nov. 2023)

Microsoft deal would reopen Three Mile Island nuclear plant to power AI, Washington Post (Sep. 2024)

Extreme Weather Is Taxing Utilities More Often. Can A.I. Help?, New York Times (Sep. 2024)

Fixing AI’s energy crisis, Nature (focused on reducing computer hardware’s power consumption - Oct. 2024)

A.I. Needs Copper. It Just Helped to Find Millions of Tons of It., New York Times (July 2024)

AI is poised to drive 160% increase in data center power demand, Goldman Sachs (May 2024)

Photos from Policy Leadership in the Age of AI Symposium (Oct. 2024)

Episode Credits

Our 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.

The cover photo for this episode is by Thomas Meredith, courtesy of LBJ School of Public Affairs.

About AI for the Rest of Us

AI 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 

Kara Swisher, the one-of-a-kind tech reporter, podcaster and book author, dropped by The University of Texas at Austin’s Cactus Café for a spirited conversation with a live audience about her concerns over the concentration of power in a few big tech companies, the capacity of tech to be used as both a tool and a weapon, her embrace of self-driving cars and her belief that AI will never replace human creativity. 

Swisher is the host of the podcast On with Kara Swisher and the cohost of the Pivot podcast with Scott Galloway, both distributed by New York magazine. Her latest best-seller is Burn Book, a memoir of her many years covering Silicon Valley.

Dig Deeper

The Hammer of Witches, Wikipedia

Is it Time to Regulate AI?, AI for the Rest of Us (Sep. 12, 2024)

Episode Credits

Our 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.

The cover photo for this episode is © Philip Montgomery / New York Magazine.

About AI for the Rest of Us

AI 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 

How much of our news is AI-generated right now and how might that change? With more and more misinformation posing as news, how can we sort out fact from fiction? And, in the face of falling revenue, can AI help save the news industry?

Robert Quigley is a professor of practice in UT Austin’s Moody College of Communications where he teaches digital journalism and podcasting. As the director of media innovation for the college, he focuses on artificial intelligence and journalism. He leads a group of educators from across campus who share best practices for AI in the classroom. He’s a co-host of Check Out This Podcast, a show that helps you discover your next favorite podcast. He led a project where students used AI to generate news stories, called The Future Press.

Dig Deeper

Wyoming reporter caught using artificial intelligence to create fake quotes and stories, Associated Press (Aug. 2024)

Redefining news with AI, Moody College of Communications at UT Austin (Jan. 2024)

How an AI-written Star Wars story created chaos at Gizmodo, Washington Post (July 2023)

How Will Artificial Intelligence Change the News Business?, The Intelligencer (Aug. 2023)

Google is testing an AI tool that can write news articles, TechCrunch (July 2023)

Can AI help local newsrooms streamline their newsletters? ARLnow tests the waters, Nieman Lab (May 2023)

Episode Credits

Our 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.

Elements of the cover image for this episode were generated using Midjourney and Photoshop’s generative AI tools.

About AI for the Rest of Us

AI 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 on AI for the Rest of Us, we’re talking about AI and the law. What are the biggest risks of AI that are not currently regulated? Do the makers of AI chatbots like ChatGPT owe something to content creators whose material was scraped to train the models? What kinds of things could we do to make AI safer and more useful for everyone? And could too much regulation stifle innovation and US competitiveness?

Matthew Murrell is a lawyer and lecturer in The University of Texas School of Law who is teaching a new class on the Law of AI in fall 2024. According to Murrell, one of the biggest risks of AI that isn’t currently regulated is aggregation, the ability for companies to assemble copious amounts of data about a person to build a rich profile of their life, which could be misused by nefarious actors. He noted another top concern: automated decision-making tools that perpetuate discrimination against historically marginalized people. He said in many cases, AI doesn’t present entirely new legal questions, just new twists on old questions. And he predicts that in the near term, most new regulations will likely be amendments to existing laws.

Dig Deeper

The Times Sues OpenAI and Microsoft Over A.I. Use of Copyrighted Work, New York Times (Dec. 2023)

California Legislature Approves Bill Proposing Sweeping A.I. Restrictions, New York Times (Aug. 2024) (Governor Newsom will have until Sept. 30 to consider whether to sign the bill into law)

Microsoft calls for new laws on deepfake fraud, AI sexual abuse images, Washington Post (July 2024)

Episode Credits

Our 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.

Elements of the cover image for this episode were generated using Midjourney and Photoshop’s generative AI tools.

About AI for the Rest of Us

AI 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 on AI for the Rest of Us, we’re talking about the ways that AI is being used—or might be used—to help make high-stakes decisions about all aspects of our lives—from who gets hired for a job—to what interest rates people get on loans—to whether or not someone who’s been convicted of a crime gets parole. Are AI systems better than humans at making these decisions? Why is it so tempting to give up our decision-making authority to machines? And what can we do to make sure these systems are fair and unbiased?

Craig Watkins is a professor in the Moody College of Communications at UT Austin who’s been wrestling with these questions.Watkins is executive director of the IC2 Institute and a principal investigator with Good Systems, a university-funded initiative that supports multi-disciplinary explorations of the technical, social, and ethical implications of artificial intelligence.

Dig Deeper

Video: Artificial Intelligence and the Future of Racial Justice, S. Craig Watkins, TEDxMIT (Dec. 2021)

Designing AI to Advance Racial Equity (Craig Watkins’ Good Systems project)

Dr. S. Craig Watkins on Why AI’s Potential to Combat or Scale Systemic Injustice Still Comes Down to Humans, Unlocking Us with Brené Brown, (Apr. 3, 2024)

Opinion: Are These States About to Make a Big Mistake on AI?, Politico (Apr. 2024)

Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study, The Lancet (This study found that GPT-4’s accuracy at diagnosing medical conditions varied depending on a person’s gender and race/ethnicity. Also, it was less likely to recommend advanced imaging for Black patients than Caucasian patients.) (Jan. 2024)

Wrongfully Accused by an Algorithm, New York Times, (the story of a Black man arrested for a crime he did not commit, on the basis of faulty facial recognition software) (June 2020)

Companies are on the hook if their hiring algorithms are biased, Quartz (2018)

Episode Credits

Our 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.

About AI for the Rest of Us

AI 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 on AI for the Rest of Us, we’re talking about AI in healthcare. There are a lot of wild claims about what AI can do to help make us healthier—so how can we figure out what’s real and what’s hype? And are there some potential pitfalls with these new technologies?

Scott Graham is an associate professor of rhetoric at the University of Texas at Austin and author of the book The Doctor and the Algorithm: Promise, Peril and the Future of Health AI. He uses artificial intelligence and machine learning to study communication in bioscience and health policy, with special attention to bioethics, conflicts of interest and health AI.

Dig Deeper

ChatGPT Rated as Better Than Real Doctors for Empathy, Advice, USA Today

AI in healthcare: The future of patient care and health management, Mayo Clinic

Opinion: It’s not just hype. AI could revolutionize diagnosis in medicine, Los Angeles Times

Episode Credits

Our 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.

Elements of the cover image for this episode were generated using Photoshop’s generative AI tools.

About AI for the Rest of Us

AI 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 

Researchers in fields as diverse as astronomy, chemistry, neuroscience, biotechnology and public health are now using AI tools to look for patterns in their data, write code, find and summarize existing scientific literature, and even design experiments. Someday, scientific discoveries might even be made entirely by AI.

We sat down with two guests for a bird’s eye view of how AI tools and approaches are boosting scientific discovery. Adam Klivans is a professor of computer science and the director of the Machine Learning Lab (MLL), which is a kind of umbrella organization for interdisciplinary AI research across the university. He also co-leads the Institute for Foundations of Machine Learning (IFML), which focuses on the fundamental theories behind AI. And Alex Dimakis is a professor of computer and electrical engineering. Along with Adam, he co-directs both the MLL and IFML and leads the new Center for Generative AI.

Dig Deeper

Peering in a Stellar Nursery, Texas Scientist Magazine

How New Machine Learning Techniques Could Improve MRI Scans, Amazon Science

Lululemon is experimenting with the first fabric made from recycled carbon emissions, Fast Company (this is the story referred to by Adam Klivans about Lanzatech turning carbon monoxide emissions into yoga pants to fight climate change)

From Chatbots to Antibiotics, Texas Scientist Magazine

Plastic-eating Enzyme Could Eliminate Billions of Tons of Landfill Waste, UT News

Brain Activity Decoder Can Reveal Stories in People’s Minds, Point of Discovery podcast

Alzheimer’s Drug Fermented With Help From AI and Bacteria Moves Closer to Reality, UT News

AlphaFold, Wikipedia (the AI model from Deep Mind that Adam Klivans mentioned that has made great strides in predicting the shapes that proteins take)

DataComp LM (UT’s open access dataset for training large language models)

Episode Credits

Our 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.

Elements of the cover image for this episode were generated using Midjourney and Photoshop’s generative AI tools.

About AI for the Rest of Us

AI 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 

Who will ultimately benefit from having more of our work done by AI—employees or employers? What about potential harms, like forcing us to spend time cleaning up mediocre products—pushing down wages—or eliminating jobs altogether? And how can we best prepare for working in an AI-powered future?

Today on the show we have Maytal Saar-Tsechansky— a professor in the McCombs School of Business, who has been developing AI algorithms especially around improved decision making and achieving societal, business, organizational and personal goals. And we also have Samantha Shorey, an assistant professor in the Department of Communication Studies. She studies the contributions of people who are often overlooked in our dominant cultural narratives about technology innovation—paying close attention to all the creativity and ingenuity of workers (especially women).

Looking for more great podcasts about AI? Then check out Generation AI. It’s produced by our friends over at The Drag Audio, a student-run podcast production house at UT Austin. They cover topics like making cities smarter, autonomous vehicles, election disinformation, and more.

Dig Deeper

Automating Essential Work (Samantha Shorey documented how integrating AI into the workflows of essential workers during the COVID-19 pandemic increased their workload and made their daily duties more complex and technical.)

AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity. International Monetary Fund (An IMF study predicts that in advanced economies, about 60 percent of jobs may be impacted by AI; about half of which might see lower wages or disappear.)

What jobs are safe from AI? Here are 4 career fields to consider, Desert News (Jobs in healthcare, education, law and creative fields might see fewer jobs eliminated by AI than others.)

Navigating the Jagged Technological Frontier, Harvard Business School. (Study finds that the capabilities of AI create a “jagged technological frontier” where some tasks are easily done by AI, while others, though seemingly similar in difficulty level, are outside the current capability of AI.)

Will AI be an economic blessing or curse? History offers clues, Reuters (Technological advances through the ages have often ended up benefiting the wealthy, but doing little to help workers.)

Episode Credits

Our 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.

Elements of the cover image for this episode were generated with Photoshop’s generative AI tools.

About AI for the Rest of Us

AI 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 

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 Deeper

A 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 Credits

Our 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 Us

AI 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 Deeper

A jargon-free explanation of how AI large language models work, Ars Technica

Video: 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 Review

Algorithms are pushing AI-generated falsehoods at an alarming rate. How do we stop this?, The Conversation

Episode Credits

Our 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 Us

AI 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