AI industrial policies increasingly shape the relationship of govts to the AI industry, committing public $ to R&D and procurement.

Today, we publish “AI Nationalism(s)”: an essay collection surveying this consequential wave of global policymaking:

1/🧵ainowinstitute.org/ai-nationalisms Our key findings? In a global climate where austerity is the norm in many sectors, AI has nonetheless garnered rich govt investment. This is often justified by high-level claims of benefit across various domains, from healthcare, to climate, to education, and beyond. 2/6

Last week, we published 10 key insights from a rapid deliberation we hosted with experts on an ‘FDA for AI’.

A 🧵with some highlights from our interim memo:
ainowinstitute.org/publication/wh… The FDA offers lessons in optimizing regulatory design for information production useful for AI given structural opacity in development and deployment.

For more read @akapczynski on the FDA's role in info production:


2/ openyls.law.yale.edu/bitstream/hand…

In response to the @Europarl_EN request, @theodorajewell tackles the question: "How can AI be deployed to benefit society, advance research, and accelerate our climate transition?" –– Here are some takeaways (1/7): We must ask questions: Who is developing this technology, for whom, for what, and with what data? Who profits? And then as a corollary: Who holds sovereignty and ownership rights to the data; what is at stake, and for whom, in the resulting applications? (2/7)

The next few years will see wide ranging regulation of biometrics. Our new compendium highlights lessons learned from the last decade of regulatory attempts. This summary by @ambaonadventure ainowinstitute.org/regulatingbiom… captures themes & questions for the future of biometric tech: How should biometric data be defined? Do emotion recognition systems fall within the definition of biometrics in the law?

Many algorithmic systems continue to exhibit bias and errors, yet governments still use them to make life-changing decisions. Our new report with @RaceNYU looks at those taking the fight to court—what’s working, what’s not, and where we need to focus next: ainowinstitute.org/litigatingalgo… @RaceNYU Recommendation 1: Assess the success of litigation by measuring structural change within government agencies and their programs, rather than through isolated or narrow changes to specific ADS.

We’re starting off our #AINow2018 Symposium with a year in review by @katecrawford @mer__edith hitting on some key questions—How do we ensure ethics in tech? How do we create accountability over our tools? And how do we organize for it all? “We’re gonna give you a tour of what happened this year” says @katecrawford, presenting visualization of data breaches from Cambridge Analytics to Facebook, organizing against Amazon’s Rekognition & Google’s Maven, tool supporting ICE from Palantir, & more.