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Keeping Science in Data Science with Patrick Hall
Manage episode 393677199 series 3546664
Content provided by SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Patrick Hall is the Principal Scientist at bnh.ai.
Patrick artfully illustrates how data science has become divorced from scientific rigor. At least, that is, in popular conceptions of the practice. Kimberly and Patrick discuss the pernicious influence of the McNamara Fallacy, applying the scientific method to algorithmic development and keeping an open mind without sacrificing concept validity. Patrick addresses the recent hubbub around AI sentience, cautions against using AI in social contexts and identifies the problems AI algorithms are best suited to solve. Noting AI is no different than any other mission-critical software, he outlines the investment and oversight required for AI programs to deliver value. Patrick promotes managing AI systems like products and makes the case for why performance in the lab should not be the first priority.
A transcript of this episode can be found here.
54 episodes
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Manage episode 393677199 series 3546664
Content provided by SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Patrick Hall is the Principal Scientist at bnh.ai.
Patrick artfully illustrates how data science has become divorced from scientific rigor. At least, that is, in popular conceptions of the practice. Kimberly and Patrick discuss the pernicious influence of the McNamara Fallacy, applying the scientific method to algorithmic development and keeping an open mind without sacrificing concept validity. Patrick addresses the recent hubbub around AI sentience, cautions against using AI in social contexts and identifies the problems AI algorithms are best suited to solve. Noting AI is no different than any other mission-critical software, he outlines the investment and oversight required for AI programs to deliver value. Patrick promotes managing AI systems like products and makes the case for why performance in the lab should not be the first priority.
A transcript of this episode can be found here.
54 episodes
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Similar to Pondering AI
Discover a whole new take on Artificial Intelligence with Squirro's educational podcast! Join host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and their incredible impact on society, and y ...
…
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continue reading
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…
continue reading
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…
continue reading
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continue reading
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continue reading
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…
continue reading
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continue reading
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