Performance
AI algorithms that ingest real-world data and preferences as inputs run a risk of learning and imitating our biases and prejudices.
Performance risks include:
- Risk of errors
- Risk of bias
- Risk of opaqueness
- Risk of instability of performance
- Lack of feedback process
Security
For as long as automated systems have existed, humans have tried to circumvent them. This is no different with AI.
Security risks include:
- Cyber intrusion risks
- Privacy risks
- Open source software risks
- Adversarial attacks
Control
Similar to any other technology, AI should have organisation-wide oversight with clearly-identified risks and controls.
Control risks include:
- Risk of AI going “rogue”
- Inability to control malevolent AI
Economic
The widespread adoption of automation across all areas of the economy may impact jobs and shift demand to different skills.
Economic risks include:
- Risk of job displacement
- Risk of concentration of power within 1 or a few companies
- Liability risk
Societal
The widespread adoption of complex and autonomous AI systems could result in “echo-chambers” developing between machines, and have broader impacts on human-human interaction.
Societal risks include:
- Risk of autonomous weapons proliferation
- Risk of an intelligence divide
Ethical
AI solutions are designed with specific objectives in mind which may compete with overarching organisational and societal values within which they operate.
Ethical risks include:
- Values misalignment risk
