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Incident 100: How French welfare services are creating ‘robo-debt’

Description: A French welfare office using software to automatically evaluate cases incorrectly notified a woman receiving benefits that she owed €542.

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Alleged: unknown developed an AI system deployed by French Welfare Offices, which harmed Lucie Inland.

Incident Stats

Incident ID
100
Report Count
1
Incident Date
2021-03-17
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv0, CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

100

AI Tangible Harm Level Notes

Notes about the AI tangible harm level assessment
 

No financial harm because the money was given back

AI was not involved in the robo-debt algorithms. Statistics and risk categories were used instead of AI.

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

yes

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2021

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 OccurrenceHow French welfare services are creating ‘robo-debt’
How French welfare services are creating ‘robo-debt’

How French welfare services are creating ‘robo-debt’

algorithmwatch.org

How French welfare services are creating ‘robo-debt’
algorithmwatch.org · 2021

I live alone and, like many of my generation, I am part of the precariat. As such, I receive several social benefits. The welfare office pays part of my rent and gives me a monthly stipend, which totals about 500€ a month. I’ve been working…

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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