Government's Algorithm Performance in Question: An Examination of Responsible AI

A recent incident involving the use of algorithms by the government has sparked debate over their implementation, safety, and transparency. The incident underscores the need for robust governance, management, and guardrails for AI systems to ensure safe and secure operations. This discussion highlights the importance of Trustworthy Artificial Intelligence Management (TAIM) in preventing harm and promoting trustworthiness.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

GOVERN 3.1 — similarity 0.570, rank 1. TAIM detail and related incidents →
GOVERN 1.7 — similarity 0.566, rank 2. TAIM detail and related incidents →
GOVERN 2.1 — similarity 0.562, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/86

Data source

Incident data is from the AI Incident Database (AIID).

When citing the database as a whole, please use:

McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.

Pre-print on arXiv · Database snapshots & citation guide

We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.