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Incident 593: AI Photo Filter Lightens Skin, Changes Eye Color in Student's 'Professional' Image

Description: An AI application modified an MIT student's photo to appear 'professional' by lightening her skin and changing her eye color to blue, highlighting the racial bias in the training data of the program.

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Alleged: Playground AI developed and deployed an AI system, which harmed Rona Wang and Racial minorities who may have experienced the same result.

Incident Stats

Incident ID
593
Report Count
1
Incident Date
2023-07-21
Editors
Applied Taxonomies
MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

1.1. Unfair discrimination and misrepresentation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Discrimination and Toxicity

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

Incident Reports

Reports Timeline

+1
An MIT student asked AI to make her headshot more ‘professional.’ It gave her lighter skin and blue eyes.
An MIT student asked AI to make her headshot more ‘professional.’ It gave her lighter skin and blue eyes.

An MIT student asked AI to make her headshot more ‘professional.’ It gave her lighter skin and blue eyes.

boston.com

An MIT student asked AI to make her headshot more ‘professional.’ It gave her lighter skin and blue eyes.
boston.com · 2023

Rona Wang is no stranger to using artificial intelligence.

A recent MIT graduate, Wang, 24, has been experimenting with the variety of new AI language and image tools that have emerged in the past few years, and is intrigued by the ways the…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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