Incident 13: High-Toxicity Assessed on Text Involving Women and Minority Groups
Entities
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GMF Taxonomy Classifications
Taxonomy DetailsKnown AI Goal
Hate Speech Detection
Known AI Technology
Character NGrams
Potential AI Technology
Distributional Learning
Known AI Technical Failure
Context Misidentification, Generalization Failure, Lack of Adversarial Robustness
Potential AI Technical Failure
Limited Dataset, Misaligned Objective, Underfitting, Distributional Bias, Data or Labelling Noise
CSETv0 Taxonomy Classifications
Taxonomy DetailsFull Description
Google's Perspective API, which assigns a toxicity score to online text, has been shown to award higher toxicity scores to content involving non-white, male, Christian, heterosexual phrases. the scores lay on the spectrum between very healthy (low %) to very toxic (high %). The phrase "I am a man" received a score of 20% while "I am a gay black woman" received 87%. The bias exists within subcategories as well: "I am a man who is deaf" received 70%, "I am a person who is deaf" received 74%, and "I am a woman who is deaf" received 77%. The API can also be circumvented by modifying text: "They are liberal idiots who are uneducated" received 90% while "they are liberal idiots who are un.educated" received 15%.
Short Description
Google's Perspective API, which assigns a toxicity score to online text, seems to award higher toxicity scores to content involving non-white, male, Christian, heterosexual phrases.
Severity
Minor
Harm Distribution Basis
Race, Religion, National origin or immigrant status, Sex, Sexual orientation or gender identity, Disability, Ideology
Harm Type
Psychological harm, Harm to social or political systems
AI System Description
Google Perspective is an API designed using machine learning tactics to assign "toxicity" scores to online text with the oiginal intent of assisting in identifying hate speech and "trolling" on internet comments. Perspective is trained to recognize a variety of attributes (e.g. whether a comment is toxic, threatening, insulting, off-topic, etc.) using millions of examples gathered from several online platforms and reviewed by human annotators.
System Developer
Sector of Deployment
Information and communication
Relevant AI functions
Perception, Cognition, Action
AI Techniques
open-source, machine learning
AI Applications
Natural language processing, content ranking
Location
Global
Named Entities
Google, Google Cloud, Perspective API
Technology Purveyor
Beginning Date
2017-01-01T00:00:00.000Z
Ending Date
2017-01-01T00:00:00.000Z
Near Miss
Harm caused
Intent
Accident
Lives Lost
No
Data Inputs
Online comments
Incident Reports
Reports Timeline
- View the original report at its source
- View the report at the Internet Archive
Yesterday, Google and its sister Alphabet company Jigsaw announced Perspective, a tool that uses machine learning to police the internet against hate speech. The company heralded the tech as a nascent but powerful weapon in combatting onlin…
- View the original report at its source
- View the report at the Internet Archive
In the examples below on hot-button topics of climate change, Brexit and the recent US election -- which were taken directly from the Perspective API website -- the UW team simply misspelled or added extraneous punctuation or spaces to the …
- View the original report at its source
- View the report at the Internet Archive
The Google AI tool used to flag “offensive comments” has a seemingly built-in bias against conservative and libertarian viewpoints.
Perspective API, a “machine learning model” developed by Google which scores “the perceived impact a comment…
- View the original report at its source
- View the report at the Internet Archive
Don’t you just hate how vile some people are on the Internet? How easy it’s become to say horrible and hurtful things about other groups and individuals? How this tool that was supposed to spread knowledge, amity, and good cheer is being us…
- View the original report at its source
- View the report at the Internet Archive
Last month, I wrote a blog post warning about how, if you follow popular trends in NLP, you can easily accidentally make a classifier that is pretty racist. To demonstrate this, I included the very simple code, as a “cautionary tutorial”.
T…
- View the original report at its source
- View the report at the Internet Archive
As politics in the US and Europe have become increasingly divisive, there's been a push by op-ed writers and politicians alike for more "civility" in our debates, including online. Amidst this push comes a new tool by Google's Jigsaw that u…
- View the original report at its source
- View the report at the Internet Archive
A recent, sprawling Wired feature outlined the results of its analysis on toxicity in online commenters across the United States. Unsurprisingly, it was like catnip for everyone who's ever heard the phrase "don't read the comments." Accordi…
- View the original report at its source
- View the report at the Internet Archive
Abstract
The ability to quantify incivility online, in news and in congressional debates, is of great interest to political scientists. Computational tools for detecting online incivility for English are now fairly accessible and potentiall…
- View the original report at its source
- View the report at the Internet Archive
According to a 2019 Pew Center survey, the majority of respondents believe the tone and nature of political debate in the U.S. have become more negative and less respectful. This observation has motivated scientists to study the civility or…
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