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❄️Emily M. Bender❄️ Profile picture
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11 Jan, 4 tweets, 1 min read
Quick! Think of an example of word sense ambiguity in English other than bank/river bank/financial institution!
(Mostly this is just commentary on how over-used that one example is, but I'm also kind of curious what people come up with.)
And if you want to read more about the ways in which words can have multiple senses, check out Ch 4 of Bender & Lascarides 2019:

morganclaypoolpublishers.com/catalog_Orig/p…
We do, in fact, discuss bank (among other examples) --- including the surprising claim that historically the senses are actually related!

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More from @emilymbender

❄️Emily M. Bender❄️ Profile picture
2 Dec 21
“I’ve been frustrated for a long time about the incentive structures that we have in place and how none of them seem to be appropriate for the kind of work I want to do,” -- @timnitGebru on the founding of @DAIRInstitute

washingtonpost.com/technology/202…
@timnitGebru @DAIRInstitute “how to make a large corporation the most amount of money possible and how do we kill more people more efficiently,” Gebru said. “Those are […] goals under which we’ve organized all of the funding for AI research. So can we actually have an alternative?”
bloomberg.com/news/articles/…
“AI needs to be brought back down to earth,” said Gebru, founder of DAIR. “It has been elevated to a superhuman level that leads us to believe it is both inevitable and beyond our control. >>
Read 5 tweets
❄️Emily M. Bender❄️ Profile picture
2 Dec 21
A few thoughts on citational practice and scams in the #ethicalAI space, inspired by something we discovered during my #ethNLP class today:

>>
Today's topic was "language variation and emergent bias", i.e. what happens when the training data isn't representative of the language varieties the system will be used with.

The course syllabus is here, for those following along:
faculty.washington.edu/ebender/2021_5…

>>
Week by week, we've been setting our reading questions/discussion points for the following week as we go, so that's where the questions listed for this week come from.

>>
Read 14 tweets
❄️Emily M. Bender❄️ Profile picture
4 Nov 21
"Bender notes that Microsoft’s introduction of GPT-3 fails to meet the company’s own AI ethics guidelines, which include a principle of transparency" from @jjvincent on the @verge:

theverge.com/2021/11/2/2275…
@jjvincent @verge In a bit more detail, here's what Microsoft says in their blog:

blogs.microsoft.com/ai/new-azure-o…

>> Screen cap of Microsoft blog reading: "That’s why Mic
@jjvincent @verge The principles are well researched and sensible, and working with their customers to ensure compliance is a laudable goal. However, it is not clear to me how GPT-3 can be used in accordance with them.

>>
Read 9 tweets
❄️Emily M. Bender❄️ Profile picture
3 Nov 21
About once a week, I get email from someone who'd like me to take the time to personally, individually, argue with them about the contents of Bender & Koller 2020. (Or, I gather, just agree that they are right and we were wrong.)

>>
I don't answer these emails. To do so would be a disservice to, at the very least, the students to whom I do owe my time, as well as my own research and my various other professional commitments.

>>
It's not that I object to people disagreeing with me! While I am committed to my own ideas, I don't have the hubris to believe I can't be wrong.

>>
Read 10 tweets
❄️Emily M. Bender❄️ Profile picture
28 Aug 21
@TaliaRinger Okay, so 1st some history. There was a big statistical revolution in the 90s, coming out of earlier work on ASR & statistical MT. By about 2003, Bob Moore (of MSR) was going around with a talk gloating about how over ~10yrs ACL papers went from mostly symbolic to mostly stats.
1/
@TaliaRinger That statistical NLP work was still closely coupled with understanding the shape of the problem being solved, specifically in feature engineering. Then (2010s) we got the next "invasion" from ML land (deep learning) where the idea was the computer would learn the features!

2/
@TaliaRinger Aside: As a (computational) linguist who saw both of these waves (though I really joined when the first was fully here), it was fun, in a way, to watch the established stats NLP folks be grumpy about the DL newcomers.

3/
Read 24 tweets
❄️Emily M. Bender❄️ Profile picture
26 Aug 21
Talking with students & others the past few days has brought some clarity to the ways in which the LLMs & associated overpromises suck the oxygen out of the room for all other kinds of research.

1/
(To be super clear: the conversations I was having with students about this were of the form of "how do I navigate wanting to work on X and get it published, when the whole field seems to expect that I must use LLMs?")

2/
We seem to be in a situation where people building & promoting LLMs are vastly overclaiming what they can do:

"This understands natural language!"
"This can do open-ended conversation!"

3/
Read 11 tweets

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