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Incident 264: AI-Based Vehicle Speed Estimation App Denounced by UK Drivers as Surveillance Technology

Description: Speedcam Anywhere, an app allowing users to document and report traffic violations via AI-based videographic speed estimation of a vehicle, raised concerns for UK drivers about its capabilities for surveillance and abuse.

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Alleged: Speedcam Anywhere developed and deployed an AI system, which harmed UK drivers.

Incident Stats

Incident ID
264
Report Count
1
Incident Date
2022-03-01
Editors
Khoa Lam
Applied Taxonomies
GMF, 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
 

5.1. Overreliance and unsafe use

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. Human-Computer Interaction

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
 

Unintentional

Incident Reports

Reports Timeline

Incident OccurrenceSpeed camera app developers face abuse from UK drivers
Speed camera app developers face abuse from UK drivers

Speed camera app developers face abuse from UK drivers

theguardian.com

Speed camera app developers face abuse from UK drivers
theguardian.com · 2022

The developers of a new app that uses AI to estimate the speed of a passing car say they have been forced into anonymity by the vicious response from drivers.

The app, Speedcam Anywhere, is the product of a team of AI scientists with backgr…

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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