02 09

This first wave of the movement focused on ethics over the law, neglected questions related to systemic injustice and control of infrastructures, and was unwilling to deal with what Michael Veale, Lecturer in Digital Rights and Regulation at University College London, calls “the question of problem framing”.

Those who believed big tech companies were controlling the discourse around ethical AI saw the movement as “ethics washing.”

This focus on technical mechanisms for addressing questions of fairness, bias, and discrimination addressed clear concerns about how AI and algorithmic systems were inaccurately and unfairly treating people of color or ethnic minorities.

Second-wave ethical AI narrowed in on these questions of bias and fairness and explored technical interventions to solve them.

The efforts of tech companies to champion fairness-related codes illustrate this point: In January 2018, Microsoft published its “ethical principles” for AI, starting with “fairness;” in May 2018, Facebook announced a tool to “search for bias” called “Fairness Flow;” and in September 2018, IBM announced a tool called “AI Fairness 360,” designed to “check for unwanted bias in datasets and machine learning models.”

The narrow focus on technical fairness is insufficient to help us grapple with all the complex tradeoffs, opportunities, and risks of an AI-driven future.

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