An Examination of FaceApp's Controversial Photo Filters: The Need for Responsible AI
FaceApp, a popular photo-editing application, has been under fire due to its questionable ethnicity filters. These filters, particularly the...
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TAIM catalog Map Data source & citationExamining the Impact of Smartphone Filters on Skin Tone Perception
An analysis of how popular smartphone selfie filters can subtly alter skin tones, leading to a perceived 'whitening' effect.
Read moreRevisiting Concerns over FaceApp's Controversial Filters: A Responsible AI Perspective
FaceApp, the popular photo-editing app, has once again sparked controversy with its filters, being labeled as 'racist.' In this article, we...
Read moreRethinking FaceApp: A Discussion on Responsible AI and Diversity
The viral app, FaceApp, has raised concerns about its algorithmic bias towards whitening users' faces. This incident underscores the importa...
Read moreFacial Age Progression App Introduces Ethnicity-based Filters
A widely-used face-aging app has recently added filters for ethnicities such as Black, Indian, and Asian to its application. This move raise...
Read moreQuestionable Practices in FaceApp's Racial Filtering
Recent concerns have been raised about the ethnicity filters used by FaceApp, a popular photo-editing app. Critics argue that these filters...
Read moreAI Incident: FaceApp's Temporary Use of Controversial Ethnicity-Based Filters
FaceApp, a popular photo editing app, introduced selfie filters that simulated blackface and yellowface, sparking immediate backlash. The fi...
Read moreFaceApp's Controversial Photo Filters: A Lesson in Responsible AI
A recent incident involving FaceApp's photo filters has raised concerns over the use of AI in a responsible manner. The filters, which disto...
Read morePersistent Conflicts Among Wiki Bots Signal Challenges in Shaping Responsible AI
Recent disputes between wiki bots, lasting for years, have underscored the complexities and potential pitfalls of AI governance. These incid...
Read moreUnveiling the Battlefields of Automated Content Modification: Bot-on-Bot Wars on Wikipedia
A recent study sheds light on a lesser-known phenomenon occurring within Wikipedia's pages - bot-on-bot editing wars. These conflicts, drive...
Read moreThe Human-Like Behavior of Internet Bots Leading to Mutual Conflict
An examination of a recent incident where internet bots, programmed to act autonomously, entered into a conflict due to their human-like dec...
Read moreDecade-long Conflicts Between Automated Wikipedia Edit-Bots
Over the past decade, automated edit-bots have been deployed on Wikipedia to maintain consistency and accuracy of content. However, these bo...
Read moreData 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.