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AI Incidents

TAIM catalog Map Data source & citation

Understanding the Role of Yandex Chatbot in AI Landscape

Delve into the recent incident involving Yandex chatbot, highlighting its impact on responsible AI governance and the broader implications f...

Unveiling Bias in Automatically Derived Semantic Data: A Human-Like Phenomenon

A recent study reveals an alarming revelation - the semantics derived automatically from language corpora, which are often relied upon for A...

Examining Potential Bias in Google Translate

Recent studies suggest that Google Translate may exhibit biases when translating certain gender-specific terms. This raises concerns about r...

Google Translate's Biased Algorithms Unveiled

An investigation into the biased algorithms that unintentionally caused Google Translate to produce sexist translations, highlighting the ne...

Examining Bias in Machine Translation: An Analysis of Google Translate

In this article, we delve into the concept of responsible AI and its importance, focusing on a case study involving Google Translate. Our an...

Unveiling Racial and Gender Biases in AI: A Crucial Examination

A groundbreaking study has shed light on the alarming issue of racial and gender biases within AI systems. The research, conducted by renown...

Bias in AI Systems: Reflections of Human Prejudice

Artificial Intelligence (AI) systems, designed to learn from human interactions, can unintentionally mirror inherent biases. This incident h...

Google Translate's Alleged Gender Bias: 'He' Linked to 'Hardworking', 'She' to 'Lazy'

A recent investigation uncovered potential gender bias in Google Translate, with the platform pairing male pronouns with positive connotatio...

Google Translate Introduces Gender-Specific Translations

Google's multilingual service, Google Translate, has recently updated its platform to offer gender-specific translations for select language...

Artificial Intelligence Vulnerable to Bias: Race, Gender, and Beyond

Explore a concerning trend: AI systems absorbing societal biases, often reflecting discriminatory practices against race and gender. The imp...

Addressing Bias in AI: FaceApp Removes Controversial Filters

In response to public outcry over allegations of racism, the popular photo-editing app FaceApp has removed its latest filters that darkened...

Rethinking Color-Changing Features in AI Apps: A Cautionary Tale

FaceApp, a popular photo editing app, temporarily allowed users to change their skin color. This feature raises concerns about responsible A...

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.