Can your phone make you a safer driver? Or is it part of the problem?

MIT CSAIL Professor Sam Madden shares the origin story of Cambridge Mobile Telematics, a CSAIL spinout using smartphones and AI to prevent car crashes and save lives. In this episode, Professor Madden joins host Kara Miller to explore how accelerometers, algorithms, and well-timed incentives are transforming how we understand and improve driver behavior.

Professor Madden reflects on surprising data trends, like why crash rates haven’t fallen despite better car tech, and how the ubiquitous smartphone became a key tool for reducing risk on the road. He also dives into how generative AI is reshaping software development, what it means for education and programming skills, and why trust and privacy remain top concerns when deploying AI across sensitive industries.

Covering distracted driving, autonomous vehicles, behavioral nudges, and business infrastructure, Professor Madden reveals what’s working and where the road ahead leads.

Topics include:

The history of Cambridge Mobile Telematics

The realities of traffic accidents

How your phone can track your driving safety

Turning your data into a narrative

The corrosive effects of phones

Learn more about Professor Madden on his website: https://db.csail.mit.edu/madden/

Or his CSAIL page: https://www.csail.mit.edu/person/sam-madden

Read our case study on Cambridge Mobile Telematics: https://cap.csail.mit.edu/sites/default/files/2023-05/CMT_Case%20Study%20Template_2022.pdf

Connect with CSAIL Alliances:

On our site: https://cap.csail.mit.edu/about-us/meet-our-team

On X: https://x.com/csail_alliances

On LinkedIn: https://linkedin.com/company/mit-csail

Finches, zebras, Darwin... and AI? 🧠🌍

Two centuries after Darwin explored the Galápagos, artificial intelligence is transforming how we study and protect the natural world, rapidly expanding what’s possible in biodiversity and ecology research. In this episode, MIT CSAIL Assistant Professor Sara Beery explains how AI is unlocking new possibilities in conservation, from identifying endangered species to analyzing ecosystem health at scale. AI can help biologists collect, process, and interpret enormous volumes of data, unlocking patterns and offering insights that were simply not possible without modern technology.

Beery shares her journey, from tagging snow leopards in college to leading global research at the intersection of computer vision and ecology. But she sounds a note of caution: AI has no values of its own and must be paired with human values to tackle the complex tradeoffs behind biodiversity decisions. As these tools become more powerful, it’s up to us to decide how they’re used, and what (or who) we prioritize.

🎧 Topics include:

Using AI to analyze millions of wildlife images

Why computer vision is revolutionizing species identification

The ethical dilemmas behind conservation decisions

How researchers are using AI to inform policy and protect ecosystems

🔗Learn more about Professor Beery:

🌐 Website: https://beerys.github.io/ or her CSAIL page https://www.csail.mit.edu/person/sara-beery

Connect with CSAIL Alliances:

On our site: https://cap.csail.mit.edu/about-us/meet-our-team

On X: https://x.com/csail_alliances

On LinkedIn: https://linkedin.com/company/mit-csail

#MITCSAIL #AI #Conservation #Biology #Technology #CSAILPodcast

What happens when every company becomes a tech company—and the geeks take the wheel?

Renowned economist, bestselling author, and MIT Principal Research Scientist Andrew McAfee unpacks how AI is transforming corporate strategy—from cement makers to software engineers. Drawing on insights from his book The Geek Way and his startup Workhelix, McAfee shares what he’s hearing from executives around the world, where AI is delivering real ROI, and why understanding how we measure impact is just as important as what we measure.

From call centers to material science labs, from spreadsheet power users to the future of education, McAfee examines how generative AI is changing who wins—and how people can avoid getting left behind. He also weighs in on the biggest AI misconceptions, the risks that actually matter, and why Silicon Valley still holds the crown in the age of innovation.

Topics include:

The management playbook of the future

Real-world studies on AI’s impact in the workplace

Why AI helps some workers more than others

The “credibility revolution” in measuring ROI

What companies get wrong about scaling AI

Whether writing—and even coding—will still matter in 10 years

Andrew McAfee is the Co-Director of the IDE and a Principal Research Scientist at the MIT Sloan School of Management. His research investigates how information technology changes the way companies perform, organize themselves, and compete. He is a NYT bestselling author and writes a widely read blog, which is at times one of the 10,000 most popular in the world. Prior to joining MIT Sloan, McAfee was a professor at Harvard Business School.

Connect with CSAIL Alliances:

On our site: https://cap.csail.mit.edu/about-us/meet-our-team

On X: https://x.com/csail_alliances

On LinkedIn: https://linkedin.com/company/mit-csail

#MITCSAIL #AI #GenerativeAI #Leadership #Technology #CSAILPodcast

For a full, uncut video version of this show (shot in Professor Andreas' MIT CSAIL office!), watch here: https://www.youtube.com/watch?v=QBV5Bj_NnbA

MIT CSAIL Associate Professor Jacob Andreas walks listeners through how LLMs like ChatGPT evolved from academic curiosities to industry-disrupting technologies.

Reflecting on the transformations he has observed in AI research, Professor Andreas discusses how some ideas—like linking NLP research to cognitive science—have taken a backseat, while others—like the importance of large-scale training data—remain central.

He offers insights on AI use cases, the emergence of models like DeepSeek, and the critical role of human oversight in AI deployment. Acknowledging both the excitement and concerns surrounding AI, Professor Andreas believes that educators and industry alike face a challenge in keeping pace with the ‘moving target’ of AI progress.

Plus: learn how AI can be used to decode the language of sperm whales!

About the guest: Professor Andreas is an MIT EECS Associate Professor and CSAIL PI. Before joining MIT, he earned his PhD at Berkeley. His group's research focuses on three themes: building machine learning models that learn language in human-like ways, enabling the use of language as a general-purpose tool for building intelligent systems, and developing techniques for understanding machine learning models using language. His group envisions a future built around training, explaining, and interacting with intelligent systems for users of all the world's languages.

Learn more about Professor Jacob Andreas and his research here: https://www.mit.edu/~jda/

Want to know more about Professor Andreas' work on the language of sperm whales? Read here: https://news.mit.edu/2024/csail-ceti-explores-sperm-whale-alphabet-0507

MIT's CSAIL Alliances Podcast is your guide to how AI & computer science research impact how we live, work, play, and learn. Listener discounts, meet the host, and more: csail.mit.edu/podcast

The MIT CSAIL Alliances Podcast is collaborating with MIT Sloan’s Me, Myself, and AI podcast to share a special bonus episode this month.

Paul Romer once considered himself the most optimistic economist. He rightfully predicted that technology would blow up as an economic driver coming out of the inflation of the 1970s, but acknowledges he did not foresee the inequality that technology advances would lead to.

On this episode of the Me, Myself, and AI podcast, Paul shares his views on AI advances and their implications for society. Rather than pave the way for full automation, he is a proponent of keeping humans in the loop and believes that technology can be pointed in a direction for more meaningful and beneficial use, citing education as an area ripe to benefit from AI.

More about CSAIL Alliances and our podcasts: csail.mit.edu/podcast

For more episodes from Me, Myself, and AI: https://sloanreview.mit.edu/audio-series/me-myself-and-ai/

How AI will Change Your Job with MIT Economics Professor David Autor & The Potential of Self-Supervised Learning with CSAIL PhD Student Sharut Gupta

Host: Kara Miller

Part One: MIT Economics Professor David Autor says that AI is “not like a calculator where you just punch in the numbers and get the right answer. It's much harder to figure out how to be effective with it.” Offering unique insights into the future of work in an AI-powered world, Professor Autor explains his biggest worries, the greatest upside scenarios, and how he believes we should be approaching AI as a tool, and addresses how AI will impact jobs like nursing and skilled trades.

Studies and papers referenced in conversation:

AI and Product Innovation: https://aidantr.github.io/files/AI_innovation.p

AI and the Gender Gap: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4759218

Robotics and Nursing Homes:

https://www.nber.org/papers/w33116

Part Two: CSAIL PhD student Sharut Gutpa describes how self-supervised learning might bring about truly adaptable models which can respond to fast-changing environments, like consumer preferences.

CSAIL Alliances connects business and industry to the people and research of MIT's Computer Science and Artificial Intelligence Labs. Learn more about CSAIL Alliances here.

Each month, the CSAIL podcast features cutting-edge MIT and CSAIL experts discussing their current research, challenges and successes, as well as the potential impact of emerging tech. Learn more and listen to past episodes.

Connect with CSAIL Alliances:

On our site: https://cap.csail.mit.edu/about-us/meet-our-team

On X: x.com/csail_alliances

On LinkedIn: linkedIn.com/mit-CSAIL

Have we achieved Artificial General Intelligence? MIT CSAIL Professor Manolis Kellis argues yes. Computers can do nearly every intellectual task that humans are capable of and are rapidly tackling the physical tasks. What does this mean for the future of AI integration, regulation, and development? Hear Professor Kellis’ ideas about how businesses can incorporate LLMs (large language models) to minimize silos, why we shouldn’t put up too many guardrails on AI technology, and how human-AI collaboration can lead to broader societal benefit, including healthcare. Professor Kellis is working toward a future where AI transforms healthcare through a deeper understanding of our individual genetics and targeted treatment development.

Visit Professor Kellis’s website to learn more about his work on AI and computational biology: https://www.csail.mit.edu/person/manolis-kellis

Associate Professor Marzyeh Ghassemi discusses why, despite its tremendous potential for good, AI must be approached with caution, especially in high risk areas like healthcare. Biases in training data can perpetuate real-world inequalities, providers might rely too much on potentially faulty AI, and tools created for one demographic might not necessarily translate to a different population. However, considering the incredible potential of AI to tackle challenges in transformative ways, it’s worth approaching these considerations with rigorous academic insight. Learn more about her work here: https://www.csail.mit.edu/person/marzyeh-ghassemi

This month’s podcast is a double feature. First up, Associate Professor and Chief Health AI Officer at the University of California San Diego Karandeep Singh explains the reality of using artificial intelligence for medicine. Professor Singh extrapolates on what works, what doesn’t, and how some challenges are social rather than technical.

Plus, MIT CSAIL’s Assistant Professor Andreea Bobu explains how large language models are advancing the field of robotics. Thanks to LLMs, giving directions to robots might soon look more like a conversation, without the need for step-by-step commands.

You can learn more about CSAIL research and access a full transcript of this podcast at https://cap.csail.mit.edu/.

To learn about CSAIL's Professional Development Courses, including the upcoming Cybersecurity for Technical Leaders and Deploying AI courses, visit here: cap.csail.mit.edu/events-professional-programs. Podcast listeners save 10% on courses with code MITXPOD10.

Founding Director of the MIT Internet Policy Research Initiative CSAIL Senior Research Scientist Daniel Weitzner says a lack of visibility about how personal data is being used is leading to an erosion of customer trust. However, companies increasingly need to leverage data for analytic advantage, generative AI applications, and more. His research focuses on solutions which would empower consumers with visibility and control of their data, facilitating a future of accountability and trust. Hear more about his work here: https://www.csail.mit.edu/person/daniel-weitzner

Find out more about CSAIL Alliances, as well as a full transcript of this podcast, at: https://cap.csail.mit.edu/podcasts/how-companies-can-rebuild-trust-around-data-danny-weitzner?utm_source=alliancesmembers&utm_medium=pardot&utm_campaign=dannypod24

If you would like to learn more about CSAIL's Professional Development Courses, including the upcoming Driving Innovation with Generative AI, visit here: cap.csail.mit.edu/events-professional-programs. Podcast listeners save 10% on courses with code MITXPOD10.