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Incident 312: Startup's Accent Translation AI Denounced as Reinforcing Racial Bias

Description: A startup’s use of AI voice technology to alter or remove accents for call center agents was scrutinized by critics as reaffirming bias, despite the company’s claim.

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Alleged: Sanas developed and deployed an AI system, which harmed call center agents having non-Midwestern-American accent and people having non-Midwestern-American accent.

Incident Stats

Incident ID
312
Report Count
4
Incident Date
2021-08-15
Editors
Khoa Lam
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
 

Human

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
 

Intentional

Incident Reports

Reports Timeline

Incident Occurrence+3
Buzzy Silicon Valley startup wants to make the world sound whiter
Buzzy Silicon Valley startup wants to make the world sound whiter

Buzzy Silicon Valley startup wants to make the world sound whiter

sfgate.com

Silicon Valley Startup Sparks Controversy Over What Critics Call ‘Racist Software'

Silicon Valley Startup Sparks Controversy Over What Critics Call ‘Racist Software'

nbcbayarea.com

Startup uses AI to transform call center workers' accents into "white voice"

Startup uses AI to transform call center workers' accents into "white voice"

boingboing.net

This startup will make you sound whiter and it sees nothing wrong with that

This startup will make you sound whiter and it sees nothing wrong with that

inputmag.com

Buzzy Silicon Valley startup wants to make the world sound whiter
sfgate.com · 2022

Silicon Valley startup Sanas has a lofty goal: to make call center workers sound white and American, no matter the country they're from. And that's just the beginning of their grand plan.

The voice tech company’s website features a photo of…

Silicon Valley Startup Sparks Controversy Over What Critics Call ‘Racist Software'
nbcbayarea.com · 2022

A Silicon Valley startup is sparking controversy for its, what critics call, “racist software.”

Palo Alto's Sanas uses artificial intelligence to alter or remove accents that you may hear when calling into a tech helpline. 

"And to get the …

Startup uses AI to transform call center workers' accents into "white voice"
boingboing.net · 2022

Have you seen the 2018 movie Sorry to Bother You? It's about a young black man who gets a job at a call center and has trouble making sales until he adopts a "white voice."

A new company called Sanas seems to have based its business plan on…

This startup will make you sound whiter and it sees nothing wrong with that
inputmag.com · 2022

The premise of Sanas is pretty simple: remove your accent in real-time. It’s created with businesses like call centers in mind, where callers deal with racial biases based purely on their voice profiles. But Sanas doesn’t just want to make …

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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