<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" encoding="UTF-8" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/" xmlns:atom="http://www.w3.org/2005/Atom/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:googleplay="http://www.google.com/schemas/play-podcasts/1.0" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:fireside="http://fireside.fm/modules/rss/fireside">
  <channel>
    <fireside:hostname>web02.fireside.fm</fireside:hostname>
    <fireside:genDate>Fri, 27 Mar 2026 16:00:07 -0500</fireside:genDate>
    <generator>Fireside (https://fireside.fm)</generator>
    <title>On Wisdom - Episodes Tagged with “Alignment”</title>
    <link>https://onwisdompodcast.fireside.fm/tags/alignment</link>
    <pubDate>Sun, 23 Feb 2025 16:00:00 -0500</pubDate>
    <description>On Wisdom features a social and cognitive scientist in Toronto and an educator in London discussing the latest empirical science regarding the nature of wisdom. Igor Grossmann runs the Wisdom &amp; Culture Lab at the University of Waterloo in Canada. Charles Cassidy runs the Evidence-Based Wisdom project in London, UK. The podcast thrives on a diet of freewheeling conversation on wisdom, decision-making, wellbeing, and society and includes regular guests spots with leading behavioral scientists from the field of wisdom research and beyond. Welcome to The On Wisdom Podcast.
</description>
    <language>en-us</language>
    <itunes:type>episodic</itunes:type>
    <itunes:subtitle>What does science tell us about wisdom?</itunes:subtitle>
    <itunes:author>Charles Cassidy and Igor Grossmann</itunes:author>
    <itunes:summary>On Wisdom features a social and cognitive scientist in Toronto and an educator in London discussing the latest empirical science regarding the nature of wisdom. Igor Grossmann runs the Wisdom &amp; Culture Lab at the University of Waterloo in Canada. Charles Cassidy runs the Evidence-Based Wisdom project in London, UK. The podcast thrives on a diet of freewheeling conversation on wisdom, decision-making, wellbeing, and society and includes regular guests spots with leading behavioral scientists from the field of wisdom research and beyond. Welcome to The On Wisdom Podcast.
</itunes:summary>
    <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/6/6e7bd116-2782-4422-a140-42f329164842/cover.jpg?v=1"/>
    <itunes:explicit>no</itunes:explicit>
    <itunes:keywords>psychology, science, happiness, philosophy, wisdom, decision-making, reasoning, society</itunes:keywords>
    <itunes:owner>
      <itunes:name>Charles Cassidy and Igor Grossmann</itunes:name>
      <itunes:email>charlesdavidcassidy@gmail.com</itunes:email>
    </itunes:owner>
<itunes:category text="Science">
  <itunes:category text="Social Sciences"/>
</itunes:category>
<itunes:category text="Society &amp; Culture"/>
<itunes:category text="Society &amp; Culture">
  <itunes:category text="Philosophy"/>
</itunes:category>
<item>
  <title>63: The AI Mirror: Why Machines Reflect Us More Than They Think (with Shannon Vallor)</title>
  <link>https://onwisdompodcast.fireside.fm/63</link>
  <guid isPermaLink="false">640978be-f5ac-46b0-aa66-28b102f0904d</guid>
  <pubDate>Sun, 23 Feb 2025 16:00:00 -0500</pubDate>
  <author>Charles Cassidy and Igor Grossmann</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/6e7bd116-2782-4422-a140-42f329164842/640978be-f5ac-46b0-aa66-28b102f0904d.mp3" length="26704634" type="audio/mpeg"/>
  <itunes:episode>63</itunes:episode>
  <itunes:title>The AI Mirror: Why Machines Reflect Us More Than They Think (with Shannon Vallor)</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Charles Cassidy and Igor Grossmann</itunes:author>
  <itunes:subtitle>Can AI ever be truly wise, or are we just seeing reflections of ourselves? Philosopher Shannon Vallor joins Igor and Charles to explore how technology shapes human wisdom, why we’ve been thinking about AI all wrong, and what it really means to align machines with our values. Shannon unpacks the AI Mirror metaphor, suggesting that today’s AI isn’t a thinking mind but a reflection of human data, Igor considers whether technology could ever help us become wiser rather than just more efficient, and Charles wonders if philosophy can guide better decisions in a world increasingly shaped by algorithms. Welcome to Episode 63.</itunes:subtitle>
  <itunes:duration>44:30</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/6/6e7bd116-2782-4422-a140-42f329164842/cover.jpg?v=1"/>
  <description>Can AI ever be truly wise, or are we just seeing reflections of ourselves? Philosophy Professor Shannon Vallor joins Igor and Charles to explore how technology shapes human wisdom, why we’ve been thinking about AI all wrong, and what it really means to align machines with our values. Shannon unpacks the AI Mirror metaphor, suggesting that today’s AI isn’t a thinking mind but a reflection of human data, Igor considers whether technology could ever help us become wiser rather than just more efficient, and Charles wonders if philosophy can guide better decisions in a world increasingly shaped by algorithms. Welcome to Episode 63. Special Guest: Shannon Vallor.
</description>
  <itunes:keywords>wisdom, psychology, philosophy, social science, happiness, well being, meaning, reasoning, emotions, purpose, artificial intelligence, AI, alignment, The AI Mirror, Shannon Vallor, Value Alignment, Virtue Embodiment, Moral Machines, Technomoral Virtues, Technomoral Wisdom</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>Can AI ever be truly wise, or are we just seeing reflections of ourselves? Philosophy Professor Shannon Vallor joins Igor and Charles to explore how technology shapes human wisdom, why we’ve been thinking about AI all wrong, and what it really means to align machines with our values. Shannon unpacks the AI Mirror metaphor, suggesting that today’s AI isn’t a thinking mind but a reflection of human data, Igor considers whether technology could ever help us become wiser rather than just more efficient, and Charles wonders if philosophy can guide better decisions in a world increasingly shaped by algorithms. Welcome to Episode 63.</p><p>Special Guest: Shannon Vallor.</p><p>Links:</p><ul><li><a title="Shannon Vallor | University of Edinburgh" rel="nofollow" href="https://edwebprofiles.ed.ac.uk/profile/shannon-vallor">Shannon Vallor | University of Edinburgh</a></li><li><a title="Shannon Vallor | Edinburgh Futures Institute, The University of Edinburgh" rel="nofollow" href="https://efi.ed.ac.uk/people/shannon-vallor/">Shannon Vallor | Edinburgh Futures Institute, The University of Edinburgh</a></li><li><a title="The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking - Shannon Vallor (2024)" rel="nofollow" href="https://global.oup.com/academic/product/the-ai-mirror-9780197759066?cc=gb&amp;lang=en&amp;">The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking - Shannon Vallor (2024)</a></li><li><a title="How philosopher Shannon Vallor delivered the year’s best critique of AI - Fast Company (2024)" rel="nofollow" href="https://www.fastcompany.com/91240425/how-philosopher-shannon-vallor-delivered-the-years-best-critique-of-ai">How philosopher Shannon Vallor delivered the year’s best critique of AI - Fast Company (2024)</a></li><li><a title="The Turing Lectures: Can we live with AI? - Shannon Vallor" rel="nofollow" href="https://www.youtube.com/watch?v=7iX-wiKvYHs">The Turing Lectures: Can we live with AI? - Shannon Vallor</a></li><li><a title="The Danger Of Superhuman AI Is Not What You Think | Noema - Shannon Vallor" rel="nofollow" href="https://www.noemamag.com/the-danger-of-superhuman-ai-is-not-what-you-think/">The Danger Of Superhuman AI Is Not What You Think | Noema - Shannon Vallor</a></li><li><a title="The Thoughts The Civilized Keep | Noema - Shannon Vallor" rel="nofollow" href="https://www.noemamag.com/the-thoughts-the-civilized-keep/">The Thoughts The Civilized Keep | Noema - Shannon Vallor</a></li><li><a title="AI Is the Black Mirror | Nautilus - Philip Ball" rel="nofollow" href="https://nautil.us/ai-is-the-black-mirror-1169121/">AI Is the Black Mirror | Nautilus - Philip Ball</a></li><li><a title="Technology and the Virtues A Philosophical Guide to a Future Worth Wanting - Shannon Vallor (Book)" rel="nofollow" href="https://www.google.com/books/edition/Technology_and_the_Virtues/RaCkDAAAQBAJ?hl=en&amp;gbpv=0">Technology and the Virtues A Philosophical Guide to a Future Worth Wanting - Shannon Vallor (Book)</a></li><li><a title="Moral Machines: From Value Alignment to Embodied Virtue - Wendell Wallach, Shannon Vallor (2020)" rel="nofollow" href="https://academic.oup.com/book/33540/chapter-abstract/287906775?redirectedFrom=fulltext&amp;login=false">Moral Machines: From Value Alignment to Embodied Virtue - Wendell Wallach, Shannon Vallor (2020)</a></li><li><a title="AI and the Automation of Wisdom - Shannon Vallor (2017)" rel="nofollow" href="https://link.springer.com/chapter/10.1007/978-3-319-61043-6_8">AI and the Automation of Wisdom - Shannon Vallor (2017)</a></li><li><a title="The AI Mirror — how technology blocks human potential | FT (Subscription Required)" rel="nofollow" href="https://www.ft.com/content/67d38081-82d3-4979-806a-eba0099f8011">The AI Mirror — how technology blocks human potential | FT (Subscription Required)</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>Can AI ever be truly wise, or are we just seeing reflections of ourselves? Philosophy Professor Shannon Vallor joins Igor and Charles to explore how technology shapes human wisdom, why we’ve been thinking about AI all wrong, and what it really means to align machines with our values. Shannon unpacks the AI Mirror metaphor, suggesting that today’s AI isn’t a thinking mind but a reflection of human data, Igor considers whether technology could ever help us become wiser rather than just more efficient, and Charles wonders if philosophy can guide better decisions in a world increasingly shaped by algorithms. Welcome to Episode 63.</p><p>Special Guest: Shannon Vallor.</p><p>Links:</p><ul><li><a title="Shannon Vallor | University of Edinburgh" rel="nofollow" href="https://edwebprofiles.ed.ac.uk/profile/shannon-vallor">Shannon Vallor | University of Edinburgh</a></li><li><a title="Shannon Vallor | Edinburgh Futures Institute, The University of Edinburgh" rel="nofollow" href="https://efi.ed.ac.uk/people/shannon-vallor/">Shannon Vallor | Edinburgh Futures Institute, The University of Edinburgh</a></li><li><a title="The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking - Shannon Vallor (2024)" rel="nofollow" href="https://global.oup.com/academic/product/the-ai-mirror-9780197759066?cc=gb&amp;lang=en&amp;">The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking - Shannon Vallor (2024)</a></li><li><a title="How philosopher Shannon Vallor delivered the year’s best critique of AI - Fast Company (2024)" rel="nofollow" href="https://www.fastcompany.com/91240425/how-philosopher-shannon-vallor-delivered-the-years-best-critique-of-ai">How philosopher Shannon Vallor delivered the year’s best critique of AI - Fast Company (2024)</a></li><li><a title="The Turing Lectures: Can we live with AI? - Shannon Vallor" rel="nofollow" href="https://www.youtube.com/watch?v=7iX-wiKvYHs">The Turing Lectures: Can we live with AI? - Shannon Vallor</a></li><li><a title="The Danger Of Superhuman AI Is Not What You Think | Noema - Shannon Vallor" rel="nofollow" href="https://www.noemamag.com/the-danger-of-superhuman-ai-is-not-what-you-think/">The Danger Of Superhuman AI Is Not What You Think | Noema - Shannon Vallor</a></li><li><a title="The Thoughts The Civilized Keep | Noema - Shannon Vallor" rel="nofollow" href="https://www.noemamag.com/the-thoughts-the-civilized-keep/">The Thoughts The Civilized Keep | Noema - Shannon Vallor</a></li><li><a title="AI Is the Black Mirror | Nautilus - Philip Ball" rel="nofollow" href="https://nautil.us/ai-is-the-black-mirror-1169121/">AI Is the Black Mirror | Nautilus - Philip Ball</a></li><li><a title="Technology and the Virtues A Philosophical Guide to a Future Worth Wanting - Shannon Vallor (Book)" rel="nofollow" href="https://www.google.com/books/edition/Technology_and_the_Virtues/RaCkDAAAQBAJ?hl=en&amp;gbpv=0">Technology and the Virtues A Philosophical Guide to a Future Worth Wanting - Shannon Vallor (Book)</a></li><li><a title="Moral Machines: From Value Alignment to Embodied Virtue - Wendell Wallach, Shannon Vallor (2020)" rel="nofollow" href="https://academic.oup.com/book/33540/chapter-abstract/287906775?redirectedFrom=fulltext&amp;login=false">Moral Machines: From Value Alignment to Embodied Virtue - Wendell Wallach, Shannon Vallor (2020)</a></li><li><a title="AI and the Automation of Wisdom - Shannon Vallor (2017)" rel="nofollow" href="https://link.springer.com/chapter/10.1007/978-3-319-61043-6_8">AI and the Automation of Wisdom - Shannon Vallor (2017)</a></li><li><a title="The AI Mirror — how technology blocks human potential | FT (Subscription Required)" rel="nofollow" href="https://www.ft.com/content/67d38081-82d3-4979-806a-eba0099f8011">The AI Mirror — how technology blocks human potential | FT (Subscription Required)</a></li></ul>]]>
  </itunes:summary>
</item>
<item>
  <title>55: Wise of the Machines (with Sina Fazelpour)</title>
  <link>https://onwisdompodcast.fireside.fm/55</link>
  <guid isPermaLink="false">fdc73ee1-e7d8-47ad-9d27-9ff1aadc7f2e</guid>
  <pubDate>Sat, 05 Aug 2023 12:00:00 -0400</pubDate>
  <author>Charles Cassidy and Igor Grossmann</author>
  <enclosure url="https://aphid.fireside.fm/d/1437767933/6e7bd116-2782-4422-a140-42f329164842/fdc73ee1-e7d8-47ad-9d27-9ff1aadc7f2e.mp3" length="38604716" type="audio/mpeg"/>
  <itunes:episode>55</itunes:episode>
  <itunes:title>Wise of the Machines (with Sina Fazelpour)</itunes:title>
  <itunes:episodeType>full</itunes:episodeType>
  <itunes:author>Charles Cassidy and Igor Grossmann</itunes:author>
  <itunes:subtitle>How can we make AI wiser? And could AI make us wiser in return? Sina Fazelpour joins Igor and Charles to discuss the problem of bias in algorithms, how we might make machine learning systems more diverse, and the thorny challenge of alignment. Igor considers whether interacting with AIs might help us achieve higher levels of understanding, Sina suggests that setting up AIs to promote certain values may be problematic in a pluralistic society, and Charles is intrigued to learn about the opportunities offered by teaming up with our machine friends. Welcome to Episode 55.</itunes:subtitle>
  <itunes:duration>1:04:20</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
  <itunes:image href="https://media24.fireside.fm/file/fireside-images-2024/podcasts/images/6/6e7bd116-2782-4422-a140-42f329164842/cover.jpg?v=1"/>
  <description>How can we make AI wiser? And could AI make us wiser in return? Sina Fazelpour joins Igor and Charles to discuss the problem of bias in algorithms, how we might make machine learning systems more diverse, and the thorny challenge of alignment. Igor considers whether interacting with AIs might help us achieve higher levels of understanding, Sina suggests that setting up AIs to promote certain values may be problematic in a pluralistic society, and Charles is intrigued to learn about the opportunities offered by teaming up with our machine friends. Welcome to Episode 55. Special Guest: Sina Fazelpour.
</description>
  <itunes:keywords>wisdom, psychology, philosophy, social science, happiness, well being, meaning, reasoning, emotions, purpose, Sina Fazelpour, Artificial Intelligence, AI, Machine Learning, Bias, Algorithms, Alignment, Diversity, Constitutional AI, AlphaGo, Lee Sedols, God’s touch, ChatGPT, LLM, large language model</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>How can we make AI wiser? And could AI make us wiser in return? Sina Fazelpour joins Igor and Charles to discuss the problem of bias in algorithms, how we might make machine learning systems more diverse, and the thorny challenge of alignment. Igor considers whether interacting with AIs might help us achieve higher levels of understanding, Sina suggests that setting up AIs to promote certain values may be problematic in a pluralistic society, and Charles is intrigued to learn about the opportunities offered by teaming up with our machine friends. Welcome to Episode 55.</p><p>Special Guest: Sina Fazelpour.</p><p>Links:</p><ul><li><a title="Sina Fazelpour&#39;s Website" rel="nofollow" href="https://sinafazelpour.com/">Sina Fazelpour's Website</a></li><li><a title="AI and the transformation of social science research | Science - Igor Grossmann, Matthew Feinberg, Dawn C. Parker, Nicholas A. Christakis, Philip E. Tetlock,  Willian A. Cunningham (2023)" rel="nofollow" href="https://www.science.org/stoken/author-tokens/ST-1256/full">AI and the transformation of social science research | Science - Igor Grossmann, Matthew Feinberg, Dawn C. Parker, Nicholas A. Christakis, Philip E. Tetlock,  Willian A. Cunningham (2023)</a></li><li><a title="Algorithmic Fairness from a Non-ideal Perspective - Sina Fazelpour, ZacharyC.Lipton (2020" rel="nofollow" href="https://dl.acm.org/doi/pdf/10.1145/3375627.3375828">Algorithmic Fairness from a Non-ideal Perspective - Sina Fazelpour, ZacharyC.Lipton (2020</a></li><li><a title="Diversity in sociotechnical machine learning systems - Sina Fazelpour, Maria De-Arteaga (2022)" rel="nofollow" href="https://journals.sagepub.com/doi/10.1177/20539517221082027">Diversity in sociotechnical machine learning systems - Sina Fazelpour, Maria De-Arteaga (2022)</a></li><li><a title="Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? - Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang (2022)" rel="nofollow" href="https://arxiv.org/abs/2211.13972">Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? - Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang (2022)</a></li><li><a title="Algorithmic bias: Senses, sources, solutions - Sina Fazelpour, David Danks (2021)" rel="nofollow" href="https://compass.onlinelibrary.wiley.com/doi/full/10.1111/phc3.12760">Algorithmic bias: Senses, sources, solutions - Sina Fazelpour, David Danks (2021)</a></li><li><a title="Constitutional AI: Harmlessness from AI Feedback - Yuntao Bai et al (2022)" rel="nofollow" href="https://arxiv.org/abs/2212.08073">Constitutional AI: Harmlessness from AI Feedback - Yuntao Bai et al (2022)</a></li><li><a title="Taxonomy of Risks posed by Language Models - Laura Weidinger at Al (2022)" rel="nofollow" href="https://dl.acm.org/doi/10.1145/3531146.3533088">Taxonomy of Risks posed by Language Models - Laura Weidinger at Al (2022)</a></li><li><a title="Large pre-trained language models contain human-like biases of what is right and wrong to do - Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf &amp; Kristian Kersting (2022)" rel="nofollow" href="https://www.nature.com/articles/s42256-022-00458-8">Large pre-trained language models contain human-like biases of what is right and wrong to do - Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf &amp; Kristian Kersting (2022)</a></li><li><a title="On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Emily M. Bender  ,  Timnit Gebru  ,  Angelina McMillan-Major  ,  Shmargaret Shmitchell (2021)  " rel="nofollow" href="https://dl.acm.org/doi/10.1145/3442188.3445922">On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Emily M. Bender  ,  Timnit Gebru  ,  Angelina McMillan-Major  ,  Shmargaret Shmitchell (2021)  </a></li><li><a title="In Two Moves, AlphaGo and Lee Sedol Redefined the Future | Wired Magazine (2016)" rel="nofollow" href="https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/">In Two Moves, AlphaGo and Lee Sedol Redefined the Future | Wired Magazine (2016)</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>How can we make AI wiser? And could AI make us wiser in return? Sina Fazelpour joins Igor and Charles to discuss the problem of bias in algorithms, how we might make machine learning systems more diverse, and the thorny challenge of alignment. Igor considers whether interacting with AIs might help us achieve higher levels of understanding, Sina suggests that setting up AIs to promote certain values may be problematic in a pluralistic society, and Charles is intrigued to learn about the opportunities offered by teaming up with our machine friends. Welcome to Episode 55.</p><p>Special Guest: Sina Fazelpour.</p><p>Links:</p><ul><li><a title="Sina Fazelpour&#39;s Website" rel="nofollow" href="https://sinafazelpour.com/">Sina Fazelpour's Website</a></li><li><a title="AI and the transformation of social science research | Science - Igor Grossmann, Matthew Feinberg, Dawn C. Parker, Nicholas A. Christakis, Philip E. Tetlock,  Willian A. Cunningham (2023)" rel="nofollow" href="https://www.science.org/stoken/author-tokens/ST-1256/full">AI and the transformation of social science research | Science - Igor Grossmann, Matthew Feinberg, Dawn C. Parker, Nicholas A. Christakis, Philip E. Tetlock,  Willian A. Cunningham (2023)</a></li><li><a title="Algorithmic Fairness from a Non-ideal Perspective - Sina Fazelpour, ZacharyC.Lipton (2020" rel="nofollow" href="https://dl.acm.org/doi/pdf/10.1145/3375627.3375828">Algorithmic Fairness from a Non-ideal Perspective - Sina Fazelpour, ZacharyC.Lipton (2020</a></li><li><a title="Diversity in sociotechnical machine learning systems - Sina Fazelpour, Maria De-Arteaga (2022)" rel="nofollow" href="https://journals.sagepub.com/doi/10.1177/20539517221082027">Diversity in sociotechnical machine learning systems - Sina Fazelpour, Maria De-Arteaga (2022)</a></li><li><a title="Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? - Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang (2022)" rel="nofollow" href="https://arxiv.org/abs/2211.13972">Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? - Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang (2022)</a></li><li><a title="Algorithmic bias: Senses, sources, solutions - Sina Fazelpour, David Danks (2021)" rel="nofollow" href="https://compass.onlinelibrary.wiley.com/doi/full/10.1111/phc3.12760">Algorithmic bias: Senses, sources, solutions - Sina Fazelpour, David Danks (2021)</a></li><li><a title="Constitutional AI: Harmlessness from AI Feedback - Yuntao Bai et al (2022)" rel="nofollow" href="https://arxiv.org/abs/2212.08073">Constitutional AI: Harmlessness from AI Feedback - Yuntao Bai et al (2022)</a></li><li><a title="Taxonomy of Risks posed by Language Models - Laura Weidinger at Al (2022)" rel="nofollow" href="https://dl.acm.org/doi/10.1145/3531146.3533088">Taxonomy of Risks posed by Language Models - Laura Weidinger at Al (2022)</a></li><li><a title="Large pre-trained language models contain human-like biases of what is right and wrong to do - Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf &amp; Kristian Kersting (2022)" rel="nofollow" href="https://www.nature.com/articles/s42256-022-00458-8">Large pre-trained language models contain human-like biases of what is right and wrong to do - Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A. Rothkopf &amp; Kristian Kersting (2022)</a></li><li><a title="On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Emily M. Bender  ,  Timnit Gebru  ,  Angelina McMillan-Major  ,  Shmargaret Shmitchell (2021)  " rel="nofollow" href="https://dl.acm.org/doi/10.1145/3442188.3445922">On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? - Emily M. Bender  ,  Timnit Gebru  ,  Angelina McMillan-Major  ,  Shmargaret Shmitchell (2021)  </a></li><li><a title="In Two Moves, AlphaGo and Lee Sedol Redefined the Future | Wired Magazine (2016)" rel="nofollow" href="https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/">In Two Moves, AlphaGo and Lee Sedol Redefined the Future | Wired Magazine (2016)</a></li></ul>]]>
  </itunes:summary>
</item>
  </channel>
</rss>
