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コンテンツは Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal
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Responsible AI: Does it help or hurt innovation? With Anthony Habayeb

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コンテンツは Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

Artificial Intelligence (AI) stands at a unique intersection of technology, ethics, and regulation. The complexities of responsible AI are brought into sharp focus in this episode featuring Anthony Habayeb, CEO and co-founder of Monitaur, As responsible AI is scrutinized for its role in profitability and innovation, Anthony and our hosts discuss the imperatives of safe and unbiased modeling systems, the role of regulations, and the importance of ethics in shaping AI.
Show notes

Prologue: Why responsible AI? Why now? (00:00:00)

  • Deviating from our normal topics about modeling best practices
  • Context about where regulation plays a role in industries besides big tech
  • Can we learn from other industries about the role of "responsibility" in products?

Special guest, Anthony Habayeb (00:02:59)

  • Introductions and start of the discussion
  • Of all the companies you could build around AI, why governance?

Is responsible AI the right phrase? (00:11:20)

  • Should we even call good modeling and business practices "responsible AI"?
  • Is having responsible AI a “want to have?” or a “need to have?”

Importance of AI regulation and responsibility (00:14:49)

  • People in the AI and regulation worlds have started pushing back on Responsible AI.
  • Do regulations impede freedom?
  • Discussing the big picture of responsibility and governance: Explainability, repeatability, records, and audit

What about bias and fairness? (00:22:40)

  • You can have fair models that operate with bias
  • Bias in practice identifies inequities that models have learned
  • Fairness is correcting for societal biases to level the playing field for safer business and modeling practices to prevail.

Responsible deployment and business management (00:35:10)

  • Discussion about what organizations get right about responsible AI
  • And what organizations can get completely wrong if they aren't careful.

Embracing responsible AI practices (00:41:15)

  • Getting your teams, companies, and individuals involved in the movement towards building AI responsibly

What did you think? Let us know.

Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics:

  • LinkedIn - Episode summaries, shares of cited articles, and more.
  • YouTube - Was it something that we said? Good. Share your favorite quotes.
  • Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.
  continue reading

18 つのエピソード

Artwork
iconシェア
 
Manage episode 416901919 series 3475282
コンテンツは Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、Dr. Andrew Clark & Sid Mangalik, Dr. Andrew Clark, and Sid Mangalik またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

Artificial Intelligence (AI) stands at a unique intersection of technology, ethics, and regulation. The complexities of responsible AI are brought into sharp focus in this episode featuring Anthony Habayeb, CEO and co-founder of Monitaur, As responsible AI is scrutinized for its role in profitability and innovation, Anthony and our hosts discuss the imperatives of safe and unbiased modeling systems, the role of regulations, and the importance of ethics in shaping AI.
Show notes

Prologue: Why responsible AI? Why now? (00:00:00)

  • Deviating from our normal topics about modeling best practices
  • Context about where regulation plays a role in industries besides big tech
  • Can we learn from other industries about the role of "responsibility" in products?

Special guest, Anthony Habayeb (00:02:59)

  • Introductions and start of the discussion
  • Of all the companies you could build around AI, why governance?

Is responsible AI the right phrase? (00:11:20)

  • Should we even call good modeling and business practices "responsible AI"?
  • Is having responsible AI a “want to have?” or a “need to have?”

Importance of AI regulation and responsibility (00:14:49)

  • People in the AI and regulation worlds have started pushing back on Responsible AI.
  • Do regulations impede freedom?
  • Discussing the big picture of responsibility and governance: Explainability, repeatability, records, and audit

What about bias and fairness? (00:22:40)

  • You can have fair models that operate with bias
  • Bias in practice identifies inequities that models have learned
  • Fairness is correcting for societal biases to level the playing field for safer business and modeling practices to prevail.

Responsible deployment and business management (00:35:10)

  • Discussion about what organizations get right about responsible AI
  • And what organizations can get completely wrong if they aren't careful.

Embracing responsible AI practices (00:41:15)

  • Getting your teams, companies, and individuals involved in the movement towards building AI responsibly

What did you think? Let us know.

Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics:

  • LinkedIn - Episode summaries, shares of cited articles, and more.
  • YouTube - Was it something that we said? Good. Share your favorite quotes.
  • Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.
  continue reading

18 つのエピソード

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