On *reviewability* of automated decision making (ADM), rather than *explainability*
Reviewability does not necessarily involve explanations. It is about exposing the decision-making process, including human processes, structures, & systems around a model
Explanations focused on how a model has arrived at an output may miss much of what is important. A more holistic view could include information on testing & auditing procedures, training data, effects of decisions on protected characteristics, & more. 2/ @jennifercobbe
Judicial review of public sector decision-making does not simply assess the decision itself, but the decision-making process as a whole
An understanding of human decision-making as a process that begins before the decision and that has consequences that resonate afterwards 3/
Above quotes are from "Reviewable Automated Decision Making", by @jennifercobbe and Jatinder Singh 4/
There has been more focus on whether the public trusts institutions (governments, medicine, public health orgs) than on how those institutions could better earn our trust. 1/
Western leaders have expressed confidence even when they were completely wrong, and have been unwilling to express uncertainty, even when it would have been more honest 2/
We've seen politicians upgrade parliament to have excellent air ventilation, as school children & essential workers are forced into poorly ventilated buildings with insufficient mitigations #COVIDisAirborne 3/
Flaws of countering disinfo w/ appeal to authority:
"Worrying about whether we trust institutions without asking if these institutions deserve trust... A program of infantalization – trust that the adults know what is right – will provoke equally infantile resistance." @Aelkus
Failure of legacy institutions to respond appropriately to the pandemic, from March 2020 @aelkus, h/t @RSButner
A society that cares more about declining trust in institutions than what institutions have done to deserve trust – and which devotes far more effort towards managing the behavioral psychology of risk than actually reducing risk – is engaged in narrative-making above all else.
Compared to ethics principles in medicine, AI ethics principles lack: 1. common aims & fiduciary duties 2. professional history & norms 3. proven methods to translate principles into practice 4. robust legal & professional accountability mechanisms
"The truly difficult part of ethics—actually translating theories, concepts & values into good practices AI practitioners can adopt—is kicked down the road like the proverbial can." @b_mittelstadt 2/
"Ethics has a cost. AI is often developed behind closed doors without public representation... It cannot be assumed that value-conscious frameworks will be meaningfully implemented in commercial processes that value efficiency, speed and profit." 3/
Australia's competition regulator found:
- Google engages in anti-competitive behavior in digital advertising, which harms consumers & businesses accc.gov.au/media-release/…
Many people have a false dichotomy that you are either FOR or AGAINST covid restrictions, with no nuance about the TYPE of restrictions or level of effectiveness, much less that eschewing all restrictions → hospitals collapse & lockdown more likely. 1/
There has been a lot of terrible public health messaging & contradictory government policies in the West, from the start of the pandemic, continuing now, and these erode public trust, create false expectations, & contribute to “pandemic fatigue” 2/
The “only elderly & chronically ill are at risk” was both false AND ineffective messaging. This has been clear from the VERY START of the pandemic. (I RTed @jenbrea at the time) 3/