AI is full of promise, with the potential to revolutionize so many different areas of modern society.

In order to realize its true potential, our field needs to be welcoming to all people. As it stands today, it is definitely not.

Our field has a problem with inclusiveness.
Too many in the field see those who are different as people to be belittled, demeaned, harassed, gaslit, or otherwise made to feel unwelcome or question whether they “belong”.
(And yes, when the bad behavior is disproportionately exhibited by those who are white and the people to whom it is directed are not, we need to call this what it is: racism.)
This is especially troubling when our field already is far too short of diverse voices. We should use the urge to combat racism in general in our society to improve our own field and make a welcoming path for everyone who wants to contribute.
We need people from different backgrounds, races, socioeconomic statuses, countries, genders, and areas of expertise to all come together to work on our most challenging problems.
In the U.S. the number of Black PhD graduates in 2019 was… *13*. About 1% of the total. https://twitter.com/vj_chidambaram/status/1270039158342418435?s=20
The lack of diversity in AI and computer science often means that critical issues that affect different communities are ignored, downplayed, or not even considered, rather than being given the serious attention they deserve.
For example, many companies in the last few years launched public general-purpose face recognition APIs.
The Gender Shades project by @jovialjoy, @timnitGebru, @rajiinio et al. examined many of these commercial APIs and identified harmful gender & race biases.
Many of these APIs have now been discontinued because of their potential for harm. https://twitter.com/ACLU/status/1271840717514686465
To improve our field, let’s all work to be inclusive, to call out bad behavior when we see it, and to actively encourage the diversity that our field needs.

This means not just being quietly tolerant of diverse voices, but actively supporting & uplifting these voices.
If you want to listen to wise people in this area, here are a few that I have learned from:

@timnitGebru @jovialjoy @mmitchellai @rajiinio @red_abebe @sguada @abebab @osazuwa @ruha9 @emilymbender @hannawallach @JordanBHarrod @robotsmarts
Organizations like @black_in_ai @_LXAI @QueerinAI @WiMLworkshop @AiDisability @DeepIndaba @Khipu_AI @seamlschool & others are doing great work in bringing new voices into our community, by encouraging people to pursue AI and machine learning as careers.
They need the support of all of us, not just of those most closely identified with these great organizations.
Look around at the people in your institution, at your network of collaborators and colleagues.

Are they diverse?

Reflect on why that might be.
At @GoogleAI (and more broadly @Google), we definitely have room to improve and it’s something I & many others in our organization are working on and care deeply about.
What improvements will you advocate for in your institution?
. @databoydg has written up an excellent paper on “Combating Anti-Blackness in the AI Community”

PDF: http://www.devinguillory.com/files/AI_Anti_Blackness.pdf

Tweet: https://twitter.com/databoydg/status/1275236482190434304?s=20
It was heartening to see many people volunteer to help give feedback/suggestions on @NeurIPS submissions by @black_in_ai members just before the paper deadline: https://twitter.com/le_roux_nicolas/status/1267896907621433344?s=20
I also recommend these threads written by others.
(Feel free to add comments pointing at other threads you have enjoyed or learned from!)

This thread written by @le_roux_nicolas on how to be a good ally: https://twitter.com/le_roux_nicolas/status/1275485736259792898?s=20
. @nando highlights the lack of diversity in AI: https://twitter.com/NandoDF/status/1277192419595911168?s=20
Let’s not demean, discourage, or attack. Instead, let’s see more of the encouragement, mentoring, and welcoming outreach that our field so desperately needs.

I know that many people in our field agree with much of what I wrote above.

Thank you for listening.
(Addendum: as @robertoprs pointed out in a comment, I meant to note @NandoDF in pointing at his thread, not '<@>nando'. My apologies).
You can follow @JeffDean.
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