Showing posts with label potential bias. Show all posts
Showing posts with label potential bias. Show all posts

Tuesday, April 8, 2025

Justice Barrett has set a new judicial ethics standard — and it’s about time; The Hill, April 8, 2025

 CAROLINE CICCONE, The Hill; Justice Barrett has set a new judicial ethics standard — and it’s about time

"Unlike every other federal court, the Supreme Court operates without mandatory ethics rules. The justices alone decide if their conflicts merit recusal, with no obligation to explain their reasoning. This self-policing system creates an accountability void that would be unacceptable in any other branch of government.

However, a recent decision by a member of the court’s conservative supermajority shows us that it doesn’t have to be this way.

Justice Amy Coney Barrett bucked this trend with her recent recusal from Oklahoma Statewide Charter School Board v. Drummond. Although Barrett provided no public explanation, it’s plausible if not likely that her decision stemmed from her close ties to Notre Dame’s Religious Liberty Clinic and personal friendship with one of the case’s legal adviser, Notre Dame law Professor and Federalist Society Director Nicole Stelle Garnett. 

This choice reflects the longstanding principle, mostly abandoned by the Roberts Supreme Court, that judges should step aside when personal relationships might bias them, or even create the appearance of impropriety."

Friday, June 30, 2023

AI ethics toolkit updated to include more assessment components; ZDNet, June 27, 2023

 Eileen Yu, ZDNet ; AI ethics toolkit updated to include more assessment components

"A software toolkit has been updated to help financial institutions cover more areas in evaluating their "responsible" use of artificial intelligence (AI). 

First launched in February last year, the assessment toolkit focuses on four key principles around fairness, ethics, accountability, and transparency -- collectively called FEAT. It offers a checklist and methodologies for businesses in the financial sector to define the objectives of their AI and data analytics use and identify potential bias.

The toolkit was developed by a consortium led by the Monetary Authority of Singapore (MAS) that compromises 31 industry players, including Bank of China, BNY Mellon, Google Cloud, Microsoft, Goldman Sachs, Visa, OCBC Bank, Amazon Web Services, IBM, and Citibank."