GCRI · Artificial Intelligence and Autonomous Systems
STEM foundation of Artificial Intelligence and Autonomous Systems
The science, technology, engineering and mathematics Artificial Intelligence and Autonomous Systems rests on. Each method has a canonical page in the STEM Commons, hosted by the Global Centre for Risk and Innovation (GCRI), and a page here on how it is applied in this field.
STEM foundation of Artificial Intelligence and Autonomous Systems in four parts.
The methods behind the field.
- 01Artificial intelligence and machine learningDistribution shift analysis · Fine-tuning for a specific use · Interpretability methodsSteward · Artificial Intelligence and Autonomous SystemsApplied here
- 02AI evaluation and assurance engineeringAssurance cases for AI systems · Structured red teaming · Post-deployment monitoringSteward · Artificial Intelligence and Autonomous SystemsApplied here
- 03High-performance, cloud and edge computingCompute access for public research · Energy measurement of workloadsSteward · Data and ComputeApplied here
- 04Probability and statisticsUncertainty on benchmark scores · Calibration assessment · Audit samplingSteward · Systems Science and ModellingApplied here
- 05Cybersecurity and cryptographyThreat modelling AI applications · Model supply chain integrity · Injection defence testingSteward · Cybersecurity and Digital ResilienceApplied here
- 06Social and behavioural scienceHuman oversight studies · Affected community research · Workplace adoption studiesSteward · Society and Human DevelopmentApplied here
- 07Robotics and automationScenario-based testing · Collaborative robot safety · Operating domain monitoringSteward · Advanced Industry and RoboticsApplied here
Why AI needs this combination of methods.
AI risk work combines AI and machine learning with AI assurance, computing, probability and statistics, cybersecurity, social science and robotics.
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Pages in STEM foundation of Artificial Intelligence and Autonomous Systems.
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