On professional societies not giving academic awards to harassers, "problematic faves", or bigots, a thread: /1
Context: I was a grad student at Stanford (in linguistics) in the 1990s, but I was clueless about Ullman. I think I knew of his textbook, but didn't know whether he was still faculty, let alone where. /2
I hadn't heard about his racist web page until this week. /3
But here in 2021, I've learned about his views, his publicization of them, and their impact, from the brave writing of scholars like @niloufar_s and @_alialkhatib /4
I don't feel like the ACM is my scholarly organization (I only joined this year, for the first time for FAccT), but I have a few things to say about academic awards. /5
First, it's clear that when a society like the ACM gives a big award to someone who has done harm, that again harms the victims of the awardee. /6
When the original harm impacted a lot of people, so does the new harm of giving the award. /7
Therefore, scholarly societies awarding honors have a responsibility to their membership to do their due diligence before selecting awardees. /8
Second, to the idea that the awards are only about "advancements to the field" and thus personal opinions/actions aren't relevant, I say: /9
Someone who has systematically made the field hostile to a whole group of people has thereby harmed the advancement of the field. Those actions are extremely relevant. /10
Third, it's worth grounding any discussion in what the purpose of the award is. /11
To serve as a carrot to inspire academics to work hard? Awards given regularly to harassers, racists and assholes aren't going to inspire hard work by community builders. /12
To serve as a way to lift up the achievements (and thus voices) of scholars within a field to those outside it? Yet another reason to think carefully about who the field wants to represent it. /13
I'm not currently involved in any award selection committees, etc, but I hope those who are (including future me) take some lessons from this: /14
1. Before even creating a short list, examine both the purpose & likely additional impacts of the award, with a view towards valuing inclusivity in the academic community. /15
2. The process for considering candidate awardees should include a due diligence phase that answers the question: has this person engaged in activities which pushed others (esp. whole groups of people) out of the field? /16
3. Keep in mind no one "has to" get any award. "Dr. XYZ is renowned for their work on (whatevs) but did far too much damage to the field to get the big award" is a perfectly sensible narrative. /17
4. As a corollary, if the culture of the field was just awful for a whole generation, and no awards are given to the 'leading lights' of that group, that's fine too! /18
5. Nobody's perfect: The ask isn't to find awardees who have never made a mistake, nor ever angered anyone that they have power over. Better not best. /19
6. Nobody's perfect II: This also isn't about creating and implementing a perfect process, just one good enough to e.g. not give the Turing Award to someone who for decades maintained a webpage explicitly denigrating Iranians and Indigenous people. /fin
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Better late than never, I suppose, but as one of the targets of his harassment, I could have wished that you didn't embolden him and his like in the first place, nor sit by for two months while this went on.
And it's not just about "people who don't want to be contacted" FWIW. He's been spamming all kinds of folks with derogatory remarks about @timnitGebru, me, and others who stand up for us.
@timnitGebru I should have kept a tally of how much time I've spent over the last two months dealing with this crap because it pleased @JeffDean to say in a public post that our paper "didn't meet the bar" for publication.
@timnitGebru He sent it to me this morning too. I just archived it without reading it, because I figured there would be nothing of value there. (I wasn't wrong.) What is it with this guy? As you say, @sibinmohan why does he think Google needs his defense?
@timnitGebru@sibinmohan And more to the point: @timnitGebru and @mmitchell_ai (and @RealAbril and others) your shedding light on this and continuing to do so brings great value. How can we get to better corporate (& other) practices if the injustices are not widely known?
1. Process: The camera ready is done, and approved by all of the authors. If I make any changes past this point it will be literally only fixing typos/citations. No changes to content let alone the title.
2. Content: I stand by the title and the question we are asking. The question is motivated because the field has been dominated by "bigger bigger bigger!" (yes in terms of both training data and model size), with most* of the discourse only fawning over the results. >>
First, some guesses about system components, based on current tech: it will include a very large language model (akin to GPT-3) trained on huge amounts of web text, including Reddit and the like.
It will also likely be trained on sample input/output pairs, where they asked crowdworkers to create the bulleted summaries for news articles.