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enforceability more than aspirational. Likewise,
existing antidiscrimination laws stand ready as protections
against biased and discriminatory implementations
and uses of AI. To successfully do that,
those laws need to be interpreted for application to
AI matters. This translational and contextualization
will be well- and crucially informed by soft law as
to unbiased and nondiscriminatory AI and through
the deep engagement of data scientists, software
engineers, statisticians, and other relevant technology
professionals in collaboration with lawyers and
public policymakers.

Acknowledgment
Thanks to Professor Gary Marchant for the opportunity
to collaborate in the Artificial Intelligence
and Soft Law project. Thanks also to Marc Canellas,
Ricardo Chavarriaga, Carlos Gutiérrez, and other
esteemed IEEE colleagues. A special shout-out to
Erica Wissolik for her superb work on behalf of the
IEEE Artificial
Artificial Intelligence and Autonomous
Systems Policy Committee.
 References
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December 2021
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http://www.implicit.harvard.edu/implicit/iatdetails.html http://www.implicit.harvard.edu/implicit/iatdetails.html https://www.aipulse.org/soft-law-governance-of-artificial-intelligence/ https://www.aipulse.org/soft-law-governance-of-artificial-intelligence/ http://www-cgi.cs.cmu.edu/~tom/pubs/NeedForBias_1980.pdf http://www-cgi.cs.cmu.edu/~tom/pubs/NeedForBias_1980.pdf https://www.ainowinstitute.org/disabilitybiasai-2019.pdf

IEEE Technology and Society Magazine - December 2021

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