Research to date aimed at the fairness, accountability, and transparency of algorithmic
systems has largely focused on topics such as identifying failures of current systems and on …

Conventional algorithmic fairness is West-centric, as seen in its subgroups, values, and
methods. In this paper, we de-center algorithmic fairness and analyse AI power in India …

Algorithmic systems increasingly shape information people are exposed to as well as
influence decisions about employment, finances, and other opportunities. In some cases …

Research in Fairness, Accountability, Transparency, and Ethics (FATE) 1 has established
many sources and forms of algorithmic harm, in domains as diverse as health care, finance …

Much of the debate on the impact of algorithms is concerned with fairness, defined as the
absence of discrimination for individuals with the same" merit." Drawing on the theory of …

As algorithms have become ubiquitous in consequential domains, societal concerns about
the potential for discriminatory outcomes have prompted urgent calls to address algorithmic …

Understanding the landscape of potential harms from algorithmic systems enables
practitioners to better anticipate consequences of the systems they build. It also supports the …

These are legitimate long-term worries. But they are not all we have to worry about, and
placing them center stage distracts from ethical questions that AI is raising here and now …

Decision-making systems increasingly orchestrate our world: how to intervene on the
algorithmic components to build fair and equitable systems is therefore a question of utmost …

As research on algorithms and their impact proliferates, so do calls for scrutiny/accountability
of algorithms. A systematic review of the work that has been done in the field of'algorithmic …