There are growing discontinuities between the research practices of data science and established
tools of research ethics regulation. Some of the core commitments of existing research …

Algorithmic impact assessments (AIAs) are an emergent form of accountability for organizations
that build and deploy automated decision-support systems. They are modeled after …

… Jacob Metcalf jacob metcalf studies research ethics in data science, machine learning, and
artificial intelligence. He is a researcher at Data & Society, where he is co-project leader on …

When algorithmic harms emerge, a reasonable response is to stop using the algorithm to
resolve concerns related to fairness, accountability, transparency, and ethics (FATE). However, …

The Algorithmic Impact Assessment is a new concept for regulating algorithmic systems and
protecting the public interest. Assembling Accountability: Algorithmic Impact Assessment for …

The use of big data research methods has grown tremendously over the past five years in
both academia and industry. As the size and complexity of available datasets has grown, so …

In widely used sociological descriptions of how accountability is structured through
institutions, an “actor” (eg, the developer) is accountable to a “forum” (eg, regulatory agencies) …

Frequent public uproar over forms of data science that rely on information about people
demonstrates the challenges of defining and demonstrating trustworthy digital data research …

In July 2023, New York City (NYC) implemented the first attempt to create an algorithm auditing
regime for commercial machine-learning systems. Local Law 144 (LL 144), requires NYC…

In July 2023, New York City became the first jurisdiction globally to mandate bias audits for
commercial algorithmic systems, specifically for automated employment decisions systems (…