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Trustworthy AI: A Conversation with NIST's Chuck Romine

Artificial Intelligence (AI) promises to grow the economy and improve our lives, but with these benefits, it also brings new risks that society is grappling with.

That said, we’re using a narrow working definition specifically for the satisfaction of the Executive Order on Maintaining American Leadership in Artificial Intelligence, which makes us responsible for providing guidance to the federal government on how it should engage in the standards arena for AI.

We acknowledge that there are multiple definitions out there, but from our perspective, an AI system is one that exhibits reasoning and performs some sort of automated decision-making without the interference of a human.

If systems are going to operate in life-or-death type of environments, whether it's in medicine or transportation, people need to be able to trust AI will make the right decisions and not jeopardize their health or well-being.

So, if the AI is outside of the boundaries of its nominal operating environment, can it fail in such a way that it doesn't cause a disaster, and can it recover from that in a way that allows it to continue to operate?

Ultimately, I think there's a risk of a consumer backlash where people may start saying these things are too easy to compromise and they’re betraying too much of my personal information, so get them out of my house.

What we can do to help, and the reason that we've prioritized trustworthy AI, is we can provide that foundational work that people in the consumer space need to manage those risks overall.

A fascinating thing we learned recently, and published in a report, is that if you take two trained human face recognizers and put them together, the dual system doesn't perform appreciably better than either one of them alone.

think one of the things that is going to be necessary for us is pulling out the desirable characteristics like usability, interoperability, resilience, security, privacy and all the things that will require a certain amount of care to build into the systems, and get innovators to start incorporating them.

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Jia Li: Machine learning and artificial intelligence could transform health care and education

Developing machine learning capabilities will require heavy investment and the cultivation of a generation of developers with a background in data science.

The Promise of AI

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Past, Present and Future of AI / Machine Learning (Google I/O '17)

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Artificial Intelligence for Military Use and National Security

Courtney Bowman (Privacy and Civil Liberties Team Lead, Palantir), Avril Haines (Former White House Deputy National Security Advisor; Former Deputy ...