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Incident 219: Poachers Evaded AI Cameras and Killed Four Rhinos

Description: AI cameras installed by Ezemvelo KZN Wildlife failed to detect poachers when four dehorned rhino carcasses were found.

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Alleged: unknown developed an AI system deployed by Ezemvelo KZN Wildlife, which harmed rhinos in conservation.

Incident Stats

Incident ID
219
Report Count
1
Incident Date
2020-11-15
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
 

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 OccurrencePoachers evade KZN park’s high-tech security and kill four rhinos for their horns
Poachers evade KZN park’s high-tech security and kill four rhinos for their horns

Poachers evade KZN park’s high-tech security and kill four rhinos for their horns

iol.co.za

Poachers evade KZN park’s high-tech security and kill four rhinos for their horns
iol.co.za · 2020

Durban - THE artificial intelligence (AI) cameras installed in Hluhluwe-iMfolozi Park failed to detect poachers after four dehorned rhinos were found last week.

The carcasses were found on different days and appeared to have been killed a f…

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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