LOCAL CONNECTION

Migrants from Africa and Haiti reportedly cannot use app to accept their photos, which is now required to apply for asylum

When it comes to evaluating COVID treatments, MDs are only human.

Another study adds to the litany of concerns about student evaluations of faculty teaching. It says men and women are both at risk from bias in gender-lopsided departments, but women more so.

On the sources of datasets AI uses for training.

Researchers from Ireland, the UK and the US have warned that the growth in hyperscale AI training datasets threaten to propagate the worst aspects of their internet sources, contending that a recently-released academic dataset features ‘troublesome and explicit images and text pairs of rape, pornography, malign stereotypes, racist and ethnic slurs, and other extremely problematic […]

Professionalism has become coded language for white favoritism in workplace practices that more often than not leave behind people of color. This is the fourth of 10 articles in a special series about diversity, equity, and inclusion.

The reanimation of the pseudosciences of physiognomy and phrenology at scale through computer vision and machine learning is a matter of urgent concern. This Ar

The development and deployment of artificial intelligence (AI) in all areas of public life have raised many concerns about the harmful consequences on society, in particular the impact on marginalised communities. EDRi's latest report "Beyond Debiasing: Regulating AI and its Inequalities", authored by Agathe Balayn and Dr. Seda Gürses,* argues that policymakers must tackle the root causes of the power imbalances caused by the pervasive use of AI systems. In promoting technical ‘debiasing’ as the main solution to AI driven structural inequality, we risk vastly underestimating the scale of the social, economic and political problems AI systems can inflict.

n.b. leads directly to fewer scholarships

Platform rules often subject marginalized communities to heightened scrutiny while providing them with too little protection from harm.

In a sea of data, the use of student success analytics may unintentionally result in consequences that benefit some students while harming others.