Examining AI Incident #165: Unintended Bias in Autocomplete Function
Recently, an unforeseen case of bias was detected in the autocomplete function of a popular search engine. This incident underscores the need for continuous monitoring and maintenance to ensure fairness and unbiased results in AI applications. By analyzing this instance, we can gain insights into the importance of responsible AI governance and the role of guardrails in mitigating potential harm.
The HISPI Project Cerebellum TAIM offers valuable resources for understanding and addressing such incidents. As a community of experts and enthusiasts, we strive to foster trustworthy AI practices through collaboration and knowledge sharing—JOIN US.
The HISPI Project Cerebellum TAIM offers valuable resources for understanding and addressing such incidents. As a community of experts and enthusiasts, we strive to foster trustworthy AI practices through collaboration and knowledge sharing—JOIN US.
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/165
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.