MIT AI Risk Repository · Risk Category · 56.17.00
Single point of failure
Description
"Intense competition leads to one company gaining a technical edge, exploiting this to the point its model controls, or is the basis for other models controlling, multiple key systems. Lack of safety, controllability, and misuse cause these systems to fail in unexpected ways."
From Future Risks of Frontier AI (GOS2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- Human
- Intent
- Unintentional
- Timing
- Other
Subdomain definition: AI-driven concentration of power and resources within certain entities or groups, especially those with access to or ownership of powerful AI systems, leading to inequitable distribution of benefits and increased societal inequality.
Real-world incidents in this subdomain
- LLM Scrapers Allegedly Target Multiple Open Source Projects Disrupting the FOSS Ecosystem
- Coupang Allegedly Tweaked Search Algorithms to Boost Own Products
- Amazon Allegedly Tweaked Search Algorithm to Boost Its Own Products
- Gmail’s Inbox Sorting System Reportedly Reduced Visibility of Political Emails and Campaign Calls-to-Action
- Google Fined for Changing Shopping Algorithms in EU to Favor Own Service
- Amazon India Allegedly Rigged Search Results to Promote Own Products
How other frameworks describe this risk
Other entries from GOS2023
- Discrimination
- Inequality
- Environmental impacts
- Amplification of biases
- Harmful responses
- Lack of transparency and interpretability
- Intellectual property rights
- Providing new capabilities to a malicious actor
- Misapplication by a non-malicious actor
- Poor performance of a model used for its intended purpose, for example leading to biased decisions
- Unintended outcomes from interactions with other AI systems
- Impacts resulting from interactions with external societal, political, and economic systems