Every year, NYU's nonprofit, critical activist group AI Now releases a report on the state of AI, with ten recommendations for making machine learning systems equitable, transparent and fail-safe (2016, 2017); this year's report just published, written by a fantastic panel, including Meredith Whittaker (previously -- one of the leaders of the successful googler uprising over the company's contract to supply AI tools to the Pentagon's drone project); Kate Crawford (previously -- one of the most incisive critics of AI); Jason Schultz (previously -- a former EFF attorney now at NYU) and many others.
This year's recommendations come in the wake of a string of worsening scandals for AI tools, including their implication in genocidal violence in Myanmar.
They include: sector-by-sector regulation of AI by appropriate regulators; strong regulation of facial recognition; broad, accountable oversight for AI development incorporating a cross-section of stakeholders; limits on trade secrecy and other barriers to auditability and transparency for AI systems that impact public service provision; corporate whistleblower protection for AI researchers in the tech sector; a "truth-in-advertising" standard for AI products; a much deeper approach to inclusivity and diversity in the tech sector; "full stack" evaluations of AI that incorporate everything from labor displacement to energy consumption and beyond; funding for community litigation for AI accountability; and an expansion of university AI programs beyond Computer Science departments.
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4. AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
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