Important work is happening in *Participatory ML* and in recognizing that AI ethics is about the *distribution of power*. I want to create a thread linking to some of this work 1/
Don’t ask if artificial intelligence is good or fair, ask how it shifts power. @radical_ai_'s essay in Nature is a great place to start: 2/
Also check out @radical_ai_'s talk from @QueerinAI #NeurIPS2019 on how ML shifts power, and on the questions we should be asking ourselves: 3/
The Participatory Approaches to ML workshop at #ICML2020 was fantastic. I will share several talks & papers from it below 4/
Beyond Fairness & Ethics: Towards Agency & Shifting Power by @JamelleWD of @Data4BlackLives, on the power imbalances in ML 5/
*Recourse* is a more useful idea than *explainability*, for giving people options to change the outcomes that impact them @berkustun 6/
*Contestability* is more useful than *transparency*, for giving people a way to critically engage with ML systems & to challenge them @cephaloponderer @alexhanna 7/
High predictive accuracy is often the focus of ML, yet it is rarely equivalent to good decision-making in complex, real world problems @achould 8/
Even when creators of recommendation systems try to address problems like harassment & disinfo, they do not offer much in the way of participation or control for users or communities that are impacted: @jonathanstray 9/
Machine learning systems need to be developed in concert together with complementary policy changes @achould 10/
The relationship between surveillance technologies & power is clear. 11/
