@DrDesmondPatton Yeah, I think this is a classic text on this (by @aylin_cim, @j2bryson & @random_walker): https://t.co/rwoMVjhelj
Semantics derived automatically from language corpora contain human-like biases.
Mentions
Extended reach
Total likes
Video views
Mentions per month
Oct 2021 – Nov 2024Where it's discussed
-
News125 articles
-
Blogs45 articles
-
X / Twitter30 posts
-
Facebook12 posts
-
Reddit4 posts
-
YouTube2 videos
AI synopsis
What people are saying
The discussions reflect a recognition of the article’s significance by referencing related studies, such as designings of bias research or the reflection of societal prejudices in AI models. Words like 'classic,' 'demonstrated,' and mentions of methodology emphasize the analytical tone, while engaging examples like autonomous cars and word embeddings highlight real-world relevance.
Most discussions acknowledge the validity of the publication's findings, emphasizing the existence of human-like biases in language models.
Participants show moderate curiosity, engaging with topics like implicit bias and implications for AI systems without deep emotional investment.
The discourse includes references to studies, methodologies, and personal experiences, indicating a reasonable level of thoughtful engagement.
Multiple comments suggest the article's importance in shaping understanding of AI biases and influencing future research or application, signaling moderate impact.
Abstract in brief
- Machine learning models that analyze language can automatically uncover humanlike biases present in large text datasets from the internet.
- These biases include neutral ones, like those related to insects or flowers, as well as problematic prejudices related to race, gender, or societal roles.
- The findings suggest that language data reflects historical and cultural biases, offering a way to identify and possibly address these biases in technology and society.]
Top posts
Most liked on X and Bluesky@GaryMarcus I guess this is yet another thing that my paper with @aylin_cim & @random_walker showed – mining language doesn't give you just any experience, it gives you the lived experience of those who produced it, expressed as knowledge including implicit biases. https://t.co/xShhDfDMcI
@SteveStuWill @jonathanstray I designed our 2017 #aibias study knowing #implicitBias was one of the largest effects discovered in psychology. We now demonstrated its reality with an entirely different methodology, yet it’s STILL under attack. https://t.co/xShhDfDMcI
@DrDesmondPatton @teemu_roos @emilymbender @moinnadeem https://t.co/CegvzedVPZ from 2017.
@j2bryson Yes, I was thinking of that paper too. For those who haven't read it, see https://t.co/wXgprOF8px Looking forward to @j2bryson's talk at #HHAI2022 tomorrow!
@kokkonutter @jpskeete I don't know if this makes it less uncomfortable, but after doing my work on the implicit biases and seeing their scale, I think this is not necessarily all explicit, intentional beliefs. So double blinding helps us be our best selves. https://t.co/xShhDfDMcI
All mentions
Debunking Myths About Bias in Autonomous Vehicle Training Processes
Recently the headlines have been filled with concerns about whether machine learning used in autonomous vehicles may be putting some groups of pedestrians at risk. This video explores how training methods influence…
Ethical and Privacy Challenges in Wearable Health Research
This lecture explores the growing role of wearable devices in health research, highlighting opportunities for real-time diagnostics and personalized care, as well as addressing data privacy, regulatory challenges, and…
https://t.co/itzEhnga5O
https://t.co/l1e4DKMhIn
RT @j2bryson: @SteveStuWill @jonathanstray I designed our 2017 #aibias study knowing #implicitBias was one of the largest effects discovere…
@kokkonutter @jpskeete I don't know if this makes it less uncomfortable, but after doing my work on the implicit biases and seeing their scale, I think this is not necessarily all explicit, intentional beliefs. So double blinding helps us be our best selves. https://t.co/xShhDfDMcI
RT @j2bryson: @GaryMarcus I guess this is yet another thing that my paper with @aylin_cim & @random_walker showed – mining language doesn't…
RT @j2bryson: @GaryMarcus I guess this is yet another thing that my paper with @aylin_cim & @random_walker showed – mining language doesn't…
@GaryMarcus I guess this is yet another thing that my paper with @aylin_cim & @random_walker showed – mining language doesn't give you just any experience, it gives you the lived experience of those who produced it, expressed as knowledge including implicit biases. https://t.co/xShhDfDMcI
@HadasKotek I was also thinking you could try using the same approach as with word embeddings but then using sentence embeddings. But that sounds so simple someone must have done it already. (So similar to https://t.co/K3OiLgn3bh)
@Tesla @elonmusk This is 1st principles woke. It's a good perspective. If you care about safety you'll pay attention to this. https://t.co/8b98v47F4R
Are autonomous cars putting people's lives at risk? https://t.co/oomSSibyvM via @YouTube
@marksongs22 @lizweil More history: my most cited article, allegedly on #AIBias, actually came from that semantics, cognitive science, & evolution-of-cognition research stream, NOT from my #AIEthics research stream. I was glad @ScienceMagazine spotted that & called it cog sci! https://t.co/xShhDfDMcI
RT @j2bryson: @SteveStuWill @jonathanstray I designed our 2017 #aibias study knowing #implicitBias was one of the largest effects discovere…
@SteveStuWill @jonathanstray I designed our 2017 #aibias study knowing #implicitBias was one of the largest effects discovered in psychology. We now demonstrated its reality with an entirely different methodology, yet it’s STILL under attack. https://t.co/xShhDfDMcI
@jadelgador https://t.co/xShhDfDMcI
@mlamons1 @1Br0wn No, it's just from our society. AI trained on the open Internet matches human implicit biases. https://t.co/xShhDfDMcI or for the blog version https://t.co/MOOkByetcA
@MCoeckelbergh @Google @cajundiscordian @Floridi @David_Gunkel sorry, this should read “speaking of ‘bias’” or “speaking of prejudice”, to be consistent with one of my just earlier tweets to it, and the definitions we learnt about from reviewers & then explained here: https://t.co/xShhDfDMcI https://t.co/irjj4kGj3f
@j2bryson Yes, I was thinking of that paper too. For those who haven't read it, see https://t.co/wXgprOF8px Looking forward to @j2bryson's talk at #HHAI2022 tomorrow!
@DrDesmondPatton Yeah, I think this is a classic text on this (by @aylin_cim, @j2bryson & @random_walker): https://t.co/rwoMVjhelj
@DrDesmondPatton @teemu_roos @emilymbender @moinnadeem https://t.co/CegvzedVPZ from 2017.
https://t.co/L1Xf3OrmQ9
@acerbialberto OK, yeah, it looks more along the lines of this paper that found that algorithms reflect the biases in human-produced content. https://t.co/hioziA0YtE
@vlasceanu_mada @david_m_amodio This by @j2bryson and colleagues seems relevant. https://t.co/hioziA0YtE
Semantics derived automatically from language corpora contain human-like biases https://t.co/FzuAtTZsbT
@AutoArtMachine @tweetycami @johnchavens @StanfordHAI @StanfordSML @Stanford No, just perfectly replicating them is common https://t.co/stFG5l0KDU
@ShannonVallor Not from 2020, but it got me into AI Ethics: https://t.co/2CTZrsFIq2
RT @Andrea_ilsergio: Semantics derived automatically from language corpora contain human-like biases https://t.co/4xoe1A8jgu
RT @Andrea_ilsergio: Semantics derived automatically from language corpora contain human-like biases https://t.co/4xoe1A8jgu
Semantics derived automatically from language corpora contain human-like biases https://t.co/4xoe1A8jgu
RT @EvilAICartoons: Note that using representative data is not always a good idea, as shown by @aylin_cim @j2bryson @random_walker in the…
Note that using representative data is not always a good idea, as shown by @aylin_cim @j2bryson @random_walker in the context of language models—used in chatbots and language translation tools— https://t.co/1TAsNdUatC
DR
JB
TS
RV
MN
S
K
R
RW
EM
A
TM
PS
YM
JB
JK
I
SD
AS
OK
EC