#AI#AIEthics#ResponsibleAI: "If we train artificial intelligence (AI) systems on biased data, they can in turn make biased judgments that affect hiring decisions, loan applications and welfare benefits — to name just a few real-world implications. With this fast-developing technology potentially causing life-changing consequences, how can we make sure that humans train AI systems on data that reflects sound ethical principles?
A multidisciplinary team of researchers at the National Institute of Standards and Technology (NIST) is suggesting that we already have a workable answer to this question: We should apply the same basic principles that scientists have used for decades to safeguard human subjects research. These three principles — summarized as “respect for persons, beneficence and justice” — are the core ideas of 1979’s watershed Belmont Report, a document that has influenced U.S. government policy on conducting research on human subjects.
The team has published its work in the February issue of IEEE’s Computer magazine, a peer-reviewed journal. While the paper is the authors’ own work and is not official NIST guidance, it dovetails with NIST’s larger effort to support the development of trustworthy and responsible AI.
“We looked at existing principles of human subjects research and explored how they could apply to AI,” said Kristen Greene, a NIST social scientist and one of the paper’s authors. “There’s no need to reinvent the wheel. We can apply an established paradigm to make sure we are being transparent with research participants, as their data may be used to train AI.”"
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