BackComplexity
Complexity
Risk Domain
AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.
Nowadays, we are faced with systems that utilize numerous learning models in their modules for their perception and decision-making processes... One aspect of an AI-based system that leads to increasing the complexity of the system is the parameter space that may result from multiplications of parameters of the internal parts of the system
Entity— Who or what caused the harm
Intent— Whether the harm was intentional or accidental
Timing— Whether the risk is pre- or post-deployment
Other risks from Saghiri et al. (2022) (15)
Energy Consumption
6.6 Environmental harmAI systemUnintentionalPre-deployment
Data Issues
1.1 Unfair discrimination and misrepresentationAI systemUnintentionalOther
Robustness and Reliability
7.3 Lack of capability or robustnessAI systemUnintentionalPost-deployment
Cheating and Deception
7.2 AI possessing dangerous capabilitiesAI systemUnintentionalPost-deployment
Security
2.2 AI system security vulnerabilities and attacksHumanIntentionalOther
Privacy
2.1 Compromise of privacy by leaking or correctly inferring sensitive informationAI systemOtherPre-deployment