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Incident 868: Portland Water Bureau SERVUS Algorithm Reportedly Allocates Utility Bill Discount to High-Wealth Consumer

Description: The Portland Water Bureau's AI-driven pilot program for water bill discounts is reported to have randomly selected Tim Boyle, a wealthy high-water consumer, for a 40% discount intended for financially struggling customers. The program, developed by SERVUS, is meant to identify underserved individuals by using machine learning.

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Alleged: Portland Water Bureau and SERVUS developed and deployed an AI system, which harmed Portland Water Bureau , Tim Boyle , Low-income Portland residents and City of Portland.
Alleged implicated AI system: SERVUS

Incident Stats

Incident ID
868
Report Count
1
Incident Date
2024-10-14
Editors
Daniel Atherton
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
 

7.3. Lack of capability or robustness

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. AI system safety, failures, and limitations

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

Incident OccurrenceMachine Learning Offers a Water Bill Discount to Wealthy Portlander
Machine Learning Offers a Water Bill Discount to Wealthy Portlander

Machine Learning Offers a Water Bill Discount to Wealthy Portlander

wweek.com

Machine Learning Offers a Water Bill Discount to Wealthy Portlander
wweek.com · 2024

Tim Boyle could not quite believe his eyes. The Columbia Sportswear CEO pays a lot of bills, personally and for his company. It’s unusual for a supplier to offer him a big discount on something for which he pays full price.

But there it was…

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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