Strive to live in your own imagination, not someone else's. Ruha Benjamin speaks about "The New Jim Code?"
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6 posts5 participants0 posts today
The speech police: Chairman Brendan Carr & the FCC’s news #distortion policy
#FCC Chairman Brendan Carr is taking a hard line against #broadcastTV stations accused of #bias against #Republicans & Pres #Trump. To pressure broadcasters, Carr is invoking the rarely enforced #news distortion policy that was developed starting in the late 1960s & says the FCC should consider revoking #broadcast licenses.
#tv #takedown #freespeech
> #maga definition is disagreement
Ars Technica · The speech police: Chairman Brendan Carr and the FCC’s news distortion policy
I am reading a peer-reviewed article that describes a study that featured 5 drivers; 4 male, 1 female. It includes the following analysis:
"It shows that male is more impulsive and daring in operating their vehicles by 22% than a female who is more hesitant and less daring, which is consistent with the physiological nature of women."
Do I reject all further findings or?
Mit dem Islamwissenschaftler und Journalisten Fabian Goldmann
zur derzeitigen #Diskursverengung, #Framing #Medien #Meinung #Berichterstattung #Bias #SelektiveEmpörung #gaza #israel
A new study finds that people tend to overestimate the size of small demographic groups because of cognitive errors in estimation of small proportions, not necessarily because of misinformation, ignorance, or animus. The authors emphasize that their findings do not negate the existence of those effects.
https://www.pnas.org/doi/abs/10.1073/pnas.2413064122 (not open access)
Preprint at https://www.brianguay.com/files/guay_2024_misperceptions.pdf
Really interesting essay today by Caroline Criado Perez (if you haven’t read her book, Invisible Women, I highly recommend) on why she doesn’t think imposter “syndrome” exists, but rather that women feeling like imposters is a very rational response to a culture that treats women in many roles as imposters. There’s a perfection trap.
https://open.substack.com/pub/carolinecriadoperez/p/the-perfection-trap?r=18451&utm_medium=ios
#women #bias #data
Invisible Women · The Perfection Trap
Continued thread
"Buried in the messages between National Security Adviser Mike Waltz, Defence Secretary Pete Hegseth, and other cabinet members is a horrible demonstration of narrative engineering.
"While the legacy media fixates on ‘classified information’, the real story is actually not the incompetence of these people but instead how they casually discussed spinning the bombing of Yemen—an already battered and famine-ravaged nation—into a palatable story for the American and global public. Let’s have a look":
https://thespectaclemag.substack.com/p/how-to-sell-a-massacre by Deaglan O'Mulrooney 
the spectacle · how the Empire sells its massacres.
(27 Mar) Study of Lyft rideshare data confirms minorities get more tickets
Researchers ascribe it to “animus or prejudice against minority drivers.”…
https://s.faithcollapsing.com/erx1l
Archive: ia: https://s.faithcollapsing.com/swf2q
#bias #minorities #science #speeding-tickets #structural-racism #tickets #traffic-violations
(27 Mar) Study of Lyft rideshare data confirms minorities get more tickets https://s.faithcollapsing.com/erx1l Archive: ia: https://s.faithcollapsing.com/swf2q #bias #minorities #science #speeding-tickets #structural-racism #tickets #traffic-violations
Automating Injustice: “Predictive” policing in #Germany - https://algorithmwatch.org/en/automating-injustice-predictive-policing-germany/ #bias
AlgorithmWatchAutomating Injustice: “Predictive” policing in Germany - AlgorithmWatchThe police, criminal justice authorities, and prisons in Germany are increasingly exploring digital possibilities for "predicting" and "preventing" crimes. The report Automating Injustice gives an overview of such systems being developed and deployed in Germany.
Algorithmic Policing: When #Predicting Means Presuming Guilty - https://algorithmwatch.org/en/algorithmic-policing-explained/ #bias #ux #paper
AlgorithmWatchAlgorithmic Policing: When Predicting Means Presuming Guilty - AlgorithmWatchAlgorithmic policing refers to practices with which it is allegedly possible to “predict” future crimes and detect future perpetrators by using algorithms and historic crime data. We explain why such practices are often discriminatory, do not hold up to what they promise, and lack a legal justification.
Continued thread
"In terms of racial identity, white Americans have had the choice of being something vague, something unraced and separate from race. A capitalized "White" challenges that freedom, by unmasking Whiteness as an American racial identity as historically important as "Blackness" — which it certainly is."
~ Nell Irvin Painter: https://www.wctrib.com/opinion/nell-irvin-painter-why-white-should-be-capitalized-too via @breton
West Central Tribune · Nell Irvin Painter: Why 'White' should be capitalized, too
People saw fresh #fruits and #vegetables as healthier than frozen or canned.
- Similar #health ratings helped people realize canned (but not frozen) could be as healthy (Study 1).
- Implicit association tests revealed indirect #bias for fresh over frozen and canned (Study 2).
![9.2. IAT canned versus fresh food condition
There was a significantly slower categorization rate (MDifference-Score = 0.81, SD = 0.30; t(44) = 19.17; p < 0.00001, 95 % CIDScore[0.73, 0.90], r = 0.71) for images of canned items when paired with ‘good’ words, compared to fresh food images. This effect had a large effect size (Cohen's d = 2.74), suggest a strong implicit bias against canned foods.
9.3. IAT frozen versus fresh food condition
There was a significantly slower categorization rate (MDifference-Score = 0.92, SD = 0.25; (t(44) = 24.66; p < 0.00001, 95 % CIDScore[0.85, 0.99], r = 0.72) for images of frozen items when paired with ‘good’ words compared to fresh food images. This effect had a large effect size (Cohen's d = 3.68), indicating a robust implicit bias favouring fresh foods over frozen options.](https://nerdculture.de/system/media_attachments/files/114/239/593/645/760/300/original/e458d02ee43aa41f.jpeg "9.2. IAT canned versus fresh food condition
There was a significantly slower categorization rate (MDifference-Score = 0.81, SD = 0.30; t(44) = 19.17; p < 0.00001, 95 % CIDScore[0.73, 0.90], r = 0.71) for images of canned items when paired with ‘good’ words, compared to fresh food images. This effect had a large effect size (Cohen's d = 2.74), suggest a strong implicit bias against canned foods.
9.3. IAT frozen versus fresh food condition
There was a significantly slower categorization rate (MDifference-Score = 0.92, SD = 0.25; (t(44) = 24.66; p < 0.00001, 95 % CIDScore[0.85, 0.99], r = 0.72) for images of frozen items when paired with ‘good’ words compared to fresh food images. This effect had a large effect size (Cohen's d = 3.68), indicating a robust implicit bias favouring fresh foods over frozen options.")
Surprise surprise:
“AI models miss disease in Black and female patients
Analysis of chest x-rays underscores need for monitoring artificial intelligence tools for bias, experts say”
https://www.science.org/content/article/ai-models-miss-disease-black-female-patients
Liberated from Paywall: https://archive.is/jEcbH
Corruption represents one of the most significant threats to democracy and respect for human rights, undermining not only the executive and legislative branches but often also the judiciary, military, and police. #Corruption #Felony #Bias
Published at #IRRJ: "On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration" by Savvina Daniil, Manel Slokom, Mirjam Cuper, Cynthia Liem, Jacco van Ossenbruggen, and Laura Hollink. #RecSys #Bias #DataSynthesis #Reproducibility
doi.orgOn the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration
| Information Retrieval Research