Goodness highness! Nature has discovered causality https://t.co/WmiX2Rk2kL
We should soon expect a flood of machine learning folks asking: What is it?
BTW, I didn't tell them, but the book I'm holding in the picture is the first printing (1763) of Bayes paper on Bayes Rule.
A lot of organisations talk outside-in (vs inside-out), they aim to be #agile, #lean and customer centric.But the reality is that their systems are not designed outside-in because the primary controls are concerned with serving the hierarchy and meeting the budget. ~ @JohnWSeddon
A buddy who's interested in end-to-end encryption (E2EE) but hasn't done one of these projects in the very messy place which is the real world happened to ask me this morning about pitfalls which might not be obvious. So here's a partial list in the hopes that it's helpful. 🧵
“People’s opinions are mainly designed to make them feel comfortable; truth, for most people is a secondary consideration.” (Bertrand Russell)
Hence the need for: https://t.co/yq2McRaOrb
"The problem isn't any particular technology, but the use of technology to manipulate people, to concentrate power in a way that is so nuts and creepy that it becomes a threat to the survival of civilisation." — Jaron Lanier.
This really does feel like it could only be a parody: "We recognise that including real people in research is important, so we're trying to find a way to do it without needing real people"
It is beyond time for the ML community to drop this idea that ethical considerations are somehow at odds with "technical merit" and that ethical review is somehow hampering "scientific progress". (As. If.)
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“IBM actually tried to collect all of its songbooks in an apparent effort to deny that it had ever advocated group singing as part of its corporate socialization.” https://t.co/Uhh4nTQIRF
Design can harm. Do you wonder if your product or service causes harm to people? There is a way to measure if a solution harms one or several thinking styles. Listen, see the patterns, track improvement, and make many solutions. Support people. https://t.co/Ze3VNxY4tW
The Degrowth Paradox: It's growing.
The last few years have seen immense...growth...in degrowth. It feels like degrowth is beginning to be significantly broached in culture, politics and economics, and certainly now more than ever.
the most insightful knowledge about a field comes from experts in the field that hold a healthy skeptical view on the topic and not from those experts that evangelize it. this holds whether it is AI, mathematics, social sciences or anything in between
Potential Harms Caused by AI Systems:
1) Bias & discrimination
2) Denial of individual autonomic rights
3) Non-transparent, unexplainable or unjustifiable outcomes
4) Invasions of privacy
5) Unreliable, unsafe or poor quality outcomes
@carlaprvieira#LeadDevSanFrancisco
Read "Digitization, Surveillance, Colonialism" in which @CarissaVeliz warns ominously that the threat of total social surveillance begins the moment anything is digitized https://t.co/7GrDbne4im