A Practical Guide to Building Ethical AI - Deepstash

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A Practical Guide to Building Ethical AI

hbr.org

Companies are leveraging data and artificial intelligence to create scalable solutions — but they’re also scaling their reputational, regulatory, and legal risks. 

  • Los Angeles is suing IBM for allegedly misappropriating data it collected with its ubiquitous weather app.

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Just a few years ago discussions of “data ethics” and “AI ethics” were reserved for nonprofit organizations and academics. Today the biggest tech companies in the world are putting together fast-growing teams to tackle the ethical problems that arise from the widespread collection, analys...

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  • The academic approach: this means spotting ethical problems, their sources, and how to think through them. But it unfortunately tends to ask different questions than businesses. The result is academic treatments that do not speak to the highly particular, concrete uses of da...

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  • Identify existing infrastructure that a data and AI ethics program can leverage. 
  • Create a data and AI ethical risk framework that is tailored to your industry.
  • Change how you think about ethics by taking cues from the successes in health care. Leaders should take inspiration...

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