Wrongfully Accused by an Algorithm; The New York Times, June 24, 2020

Kashmir Hill, The New York Times; Wrongfully Accused by an Algorithm

In what may be the first known case of its kind, a faulty facial recognition match led to a Michigan man’s arrest for a crime he did not commit.

"Clare Garvie, a lawyer at Georgetown University’s Center on Privacy and Technology, has written about problems with the government’s use of facial recognition. She argues that low-quality search images — such as a still image from a grainy surveillance video — should be banned, and that the systems currently in use should be tested rigorously for accuracy and bias.

“There are mediocre algorithms and there are good ones, and law enforcement should only buy the good ones,” Ms. Garvie said.

About Mr. Williams’s experience in Michigan, she added: “I strongly suspect this is not the first case to misidentify someone to arrest them for a crime they didn’t commit. This is just the first time we know about it.”"

NYC wants a chief algorithm officer to counter bias, build transparency; Ars Technica, November 25, 2019

Kate Cox, Ars Technica; NYC wants a chief algorithm officer to counter bias, build transparency

"It takes a lot of automation to make the nation's largest city run, but it's easy for that kind of automation to perpetuate existing problems and fall unevenly on the residents it's supposed to serve. So to mitigate the harms and ideally increase the benefits, New York City has created a high-level city government position essentially to manage algorithms."

Student tracking, secret scores: How college admissions offices rank prospects before they apply; The Washington Post, October 14, 2019

Douglas MacMillan and Nick Anderson, The Washington Post; Student tracking, secret scores: How college admissions offices rank prospects before they apply

"Admissions officers say behavioral tracking helps them serve students in the application process. When a college sees that a qualified student is serious about applying based on the student’s Web behavior, it can dedicate more staffers to follow up...

But Web tracking may unfairly provide an advantage to students with better access to technology, said Bradley Shear, a Maryland lawyer who has pushed for better regulation of students’ online privacy. A low-income student may be a strong academic candidate but receive less attention from recruiters because the student does not own a smartphone or have high-speed Internet access at home, he said.

“I don’t think the algorithm should run the admissions department,” Shear said."

'Bias deep inside the code': the problem with AI 'ethics' in Silicon Valley; The Guardian, March 29, 2019

Sam Levin, The Guardian; 'Bias deep inside the code': the problem with AI 'ethics' in Silicon Valley

"“Algorithms determine who gets housing loans and who doesn’t, who goes to jail and who doesn’t, who gets to go to what school,” said Malkia Devich Cyril, the executive director of the Center for Media Justice. “There is a real risk and real danger to people’s lives and people’s freedom.”

Universities and ethics boards could play a vital role in counteracting these trends. But they rarely work with people who are affected by the tech, said Laura Montoya, the cofounder and president of the Latinx in AI Coalition: “It’s one thing to really observe bias and recognize it, but it’s a completely different thing to really understand it from a personal perspective and to have experienced it yourself throughout your life.”

It’s not hard to find AI ethics groups that replicate power structures and inequality in society – and altogether exclude marginalized groups.

The Partnership on AI, an ethics-focused industry group launched by Google, Facebook, Amazon, IBM and Microsoft, does not appear to have black board members or staff listed on its site, and has a board dominated by men. A separate Microsoft research group dedicated to “fairness, accountability, transparency, and ethics in AI” also excludes black voices."