AI and Technology Ethics Podcast

About AI and Technology Ethics Podcast

Welcome to AITEC Podcast, where we explore the ethical side of AI and emerging tech. We call our little group the AI and Technology Ethics Circle (AITEC). Visit ethicscircle.org (https://www.ethicscircle.org/) for more info.

Publisher

AITEC

Category

science · society & culture · technology

Language

en

Explicit

No

First episode

16 Oct 2023

Latest episode

30 Sept 2026

Latest episodes

37 episodes in the feed.

1. 

   30 Sept 2026

   #36 Daniel J. Solove: Privacy, Power, and the Failure of the Law

   What if the biggest threat to privacy isn't technology itself—but the laws that let powerful institutions use it without meaningful accountability? In this episode of the AITEC Philosophy Podcast, Roberto speaks with privacy scholar Daniel J. Solove [https://www.law.gwu.edu/daniel-justin-solove] about his book On Privacy and Technology [https://global.oup.com/academic/product/on-privacy-and-technology-9780197771686?cc=us&lang=en&]. They explore why privacy is a social good rather than merely an individual preference, why the familiar "notice and consent" model places an impossible burden on ordinary people, and how AI makes modern data collection even harder to understand or control. The conversation also turns to algorithmic prediction, Wisconsin v. Loomis, the illusion of meaningful human oversight, and the ways biased data can shape decisions about sentencing, hiring, lending, and other consequential areas of life. Solove argues that technology itself is not the enemy. The deeper problem is a legal system that often fails to hold companies accountable for the risks they create. The solution, he suggests, is to change the incentives: make organizations bear more of the risk, require greater care before technologies are deployed, and impose meaningful consequences when things go wrong. Link to Daniel Solove's Substack: https://danielsolove.substack.com/ Link to Daniel Solove's Website: https://www.danielsolove.com/

2. 

   28 Aug 2026

   #35 Jiayin Zhi: When AI Helps Thinking—and When It Replaces It

   AI can speed up your work flow. But does it make you any smarter? In this episode of the AITEC Philosophy Podcast, Roberto and Sam talk with Jiayin Zhi, a PhD student in computer science at the University of Chicago, about what large language models are doing to our thinking. Her research asks a question that is becoming harder to avoid: when we use AI to interpret, write, and reason, are we extending our minds—or outsourcing them? The conversation begins with human-centered computing, the idea that technology should be designed around human needs, values, and real cognitive habits. From there, Jiayin shares findings from her research on AI-assisted close reading. One surprising result: AI-generated interpretations can improve the final written product, but too much AI can crowd out the pleasure of discovery and leave people feeling like there is little room for their own interpretation. The episode then turns to critical thinking. Here, timing matters. Using AI from the start—especially under time pressure—can produce polished work without deep understanding. But using AI later, after doing independent thinking first, may help reduce myside bias by introducing counterarguments and alternative perspectives. Along the way, we discuss poetry, interpretation, cognitive offloading, copy-and-paste learning, time pressure, myside bias, and the difference between using AI as a shortcut and using it as a genuine thinking partner. This episode is for anyone who wants to use AI well without surrendering the struggle that makes learning real. For more info, go to ethicscircle.org [https://www.ethicscircle.org/].

3. 

   26 May 2026

   #34 John MacCormick: Can Machines Think Like Us?

   When an AI tells a joke, writes an essay, or solves a complex programming problem, is it just performing a statistical magic trick—or is there something deeper happening under the hood? On this episode of The AITEC Philosophy Podcast, Roberto and Sam sit down with computer scientist John McCormick [https://www.dickinson.edu/johnmaccormick], author of Thinking AI: How Artificial Intelligence Emulates Human Understanding [https://press.princeton.edu/books/hardcover/9780691191737/thinking-ai?srsltid=AfmBOopJYY_0axygWMGMBpJ8HkF98UBLTvOtU54DSAMIexSDTxysIZj8] (Princeton University Press). For over 70 years, we've been asking Alan Turing's classic question: Can a machine think?. John reframes this debate by taking us past the polished, fluent surface of modern Large Language Models to look directly at the underlying code. We discuss whether AI merely mirrors human output or if its internal structures have begun to replicate pockets of human cognition. Despite the existential dread surrounding superintelligence, John shares a surprisingly optimistic perspective: even if we build entities that exceed human intellect, they will never replace the deeply rooted, biological fulfillment of our shared humanity. Uncover the machinery behind the curtain and join the conversation at ethicscircle.org [https://www.ethicscircle.org/].

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Apple Podcasts (US)

5.0 / 5

3 ratings

Spotify

5.0 / 5

9 ratings

Podcast Authority Score: 17 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

11

Social presence

0

YouTube

0

Engagement

60

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Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.