The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other?

Jakob Mökander · Prathm Juneja · David Watson · Luciano Floridi

88 citations0/0 files storedMinds and Machines

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Ethics and Social Impacts of AI Digitalization, Law, and Regulation Legal and Labor Studies

Abstract

Abstract On the whole, the US Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic approach to balancing the benefits and risks of automated decision systems. Yet there is still room for improvement. This commentary highlights how the US AAA can both inform and learn from the European Artificial Intelligence Act (EU AIA).

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 88 citations exist upstream.

References

2019The Brussels Effect 2017Algorithmic Bias in Autonomous Systems 2017Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness 2019The Role and Limits of Principles in AI Ethics 2021The ethics of algorithms: key problems and solutions 2021Judgment 2021Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation 2018Inherent Trade-Offs in Algorithmic Fairness

Cited by

2023Algorithmic Accountability 2024The ALTAI checklist as a tool to assess ethical and legal implications for a trustworthy AI development in education 2025Biases in AI: acknowledging and addressing the inevitable ethical issues 2023Keep trusting! A plea for the notion of Trustworthy AI 2023The E.U.’s artificial intelligence act: an ordoliberal assessment 2023When facial recognition does not ‘recognise’: erroneous identifications and resulting liabilities

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.