GCRI · Artificial Intelligence and Autonomous Systems
Innovation and practical technology
Technology relevant to artificial intelligence and data and compute: what it can do, the constraints it faces and its consequences for people and institutions.
The order things happen in.
- 01Draftsources cited, labels attached
- 02Evidence checkevery value traced
- 03Independent reviewconflicts declared
- 04Editionpublished with its limits
- 05Correctiona new version, never a silent edit
Evaluate before adopting.
- 01
Need
Which problem does the technology address, and for whom?
- 02
Evidence
What has been demonstrated, under what conditions, and what remains untested?
- 03
Constraints
Cost, skills, infrastructure, data and governance requirements.
- 04
Consequences
Effects on safety, rights, equity and the environment.
What could change AI practice, and what it still has to show.
| Technology | What it could change | What remains to be shown |
|---|---|---|
| Automated red teaming | Broader coverage of failure modes | Coverage of novel failures; evaluator reliability |
| Interpretability methods | Understanding why models fail | Scale and faithfulness of explanations |
| Content provenance standards | Labelling synthetic media | Adoption and robustness to removal |
| AI for scientific discovery | Faster hypotheses and simulation | Validation and reproducibility |
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