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Éthique de l'IA : tout comprendre aux avantages et aux risques de l'intelligence artificielle

Éthique de l'IA : tout comprendre aux avantages et aux risques de l'intelligence artificielle
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'60 Minutes' Segment Excludes Black Women Who Led Racial Bias Research

By Ryan Shepard
May 18, 2021
60 Minutes is facing intense scrutiny after it ran a story examining racial bias in facial recognition software. The segment highlighted the stories of two Black men in Detroit who were wrongly accused of committing crimes due to racial bias within facial recognition systems.
To dive further into this subject, the CBS program interviewed the two Detroit residents, a lawyer at Georgetown University and a representative from the National Institute of Standards and Technology. Interviewing the two Detroit residents and discussing the legal ramifications with an attorney is necessary for the segment. Meanwhile,
60 Minutes interviewed a computer scientist from NIST because the organization introduced a landmark study on racial bias in facial recognition two years ago. However, experts in the field were quick to point out that a trio of Black female researchers issued studies on the same topic prior to the landmark study from NIST in 2 ....

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Meaning in mayhem: COVID death counts and a Black Lives Matter reckoning

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Numbers have taken on a whole different meaning during this pandemic, and we ve all been pinned to their rise and fall with a voyeuristic sense of horror.
Daily case counts. A global death toll.
But the faceless and nameless spectre of numbers masks the mourning.and stories of love, loss, and injustice.
As the Black Lives Matter protests spilled onto the streets after the death of George Floyd in the USA, Black lives are being taken by COVID-19 in disproportionate numbers.
Something about the datafication of lives dehumanizes them , argues A.I ethics scholar and robotics engineer Inioluwa Deborah Raji. ....

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Can auditing eliminate bias from algorithms?

Can auditing eliminate bias from algorithms?
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For more than a decade, journalists and researchers have been writing about the dangers of relying on algorithms to make weighty decisions: who gets locked up, who gets a job, who gets a loan â even who has priority for COVID-19 vaccines.
Rather than remove bias, one algorithm after another has codified and perpetuated it, as companies have simultaneously continued to more or less shield their algorithms from public scrutiny.
The big question ever since: How do we solve this problem? Lawmakers and researchers have advocated for algorithmic audits, which would dissect and stress-test algorithms to see how they work and whether theyâre performing their stated goals or producing biased outcomes. And there is a growing field of private auditing firms that purport to do just that. Increasingly, companies are turning to these firms to review their algorithms, particularly when theyâve faced criticism for ....

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Medicine's Machine Learning Problem

As Big Data tools reshape health care, biased datasets and unaccountable algorithms threaten to further disempower patients.
Data science is remaking countless aspects of society, and medicine is no exception. The range of potential applications is already large and only growing by the day. Machine learning is now being used to determine which patients are at high risk of disease and need greater support (sometimes with racial bias), to discover which molecules may lead to promising new drugs, to search for cancer in X-rays (sometimes with gender bias), and to classify tissue on pathology slides. Last year MIT researchers trained an algorithm that was more accurate at predicting the presence of cancer within five years of a mammogram than techniques typically used in clinics, and a 2018 survey found that 84 percent of radiology clinics in the United States are using or plan to use machine learning software. The sense of excitement has been captured in popular books such as Eri ....

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