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How to Make Responsible AI Happen: A Historical View

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Manage episode 427309679 series 3279398
Content provided by Domino Data Labs. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Labs 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.
How do you deliver value with responsible AI, who is responsible for it, how do you put it into practice, and could we use AI to make our organizations more ethical?
This episode comes to you from the RevX conference in London, where we asked these questions of Chris Wiggins, Chief Data Scientist at the New York Times. He is also Professor of Applied Mathematics at Columbia University and author of the books “How Data Happened: A History from the Age of Reason to the Age of Algorithms” and “Data Science in Context”.
Join us as we discuss:
  • What we can learn from the history of research ethics and data legislation
  • The need for clear principles and defined ownership to ensure ethical AI
  • The translation of ethical principles into checklists, standards, and product decisions
  • The importance of benchmarking AI against human performance and addressing how human biases in data lead to biased AI outcomes
To see all of the sessions at the RevX conferences go to domino.ai/revx.
  continue reading

78 episodes

Artwork
iconShare
 
Manage episode 427309679 series 3279398
Content provided by Domino Data Labs. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Labs 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.
How do you deliver value with responsible AI, who is responsible for it, how do you put it into practice, and could we use AI to make our organizations more ethical?
This episode comes to you from the RevX conference in London, where we asked these questions of Chris Wiggins, Chief Data Scientist at the New York Times. He is also Professor of Applied Mathematics at Columbia University and author of the books “How Data Happened: A History from the Age of Reason to the Age of Algorithms” and “Data Science in Context”.
Join us as we discuss:
  • What we can learn from the history of research ethics and data legislation
  • The need for clear principles and defined ownership to ensure ethical AI
  • The translation of ethical principles into checklists, standards, and product decisions
  • The importance of benchmarking AI against human performance and addressing how human biases in data lead to biased AI outcomes
To see all of the sessions at the RevX conferences go to domino.ai/revx.
  continue reading

78 episodes

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