GCRI · Artificial Intelligence and Autonomous Systems

Spatial intelligenceObservations, models and their uncertainty in one view

Field overview

AI and autonomous systems as a risk field studies how learned models, software agents and robots behave in the real world, how their behaviour can be measured and how their failures propagate into the institutions, infrastructures and lives that depend on them. This page defines the field, explains why it matters for society, sets out what experts study and shows how it connects to other risks.

STEM methods
7
Canonical methods this field applies
Topics
8
Subject pages in the field
Counterparts
3
Platforms in shared fields across the network
Report series
2
Nexus Reports series it contributes to
01Definition

From algorithms to deployed systems.

Learning

Models and data

How training data, objectives and architectures shape behaviour, including failure modes.

Assurance

Evaluation and oversight

How systems are tested, monitored and kept under meaningful human control.

Embodiment

Autonomy in the world

How sensing, planning and control interact in robots and vehicles.

The field combines artificial intelligence and machine learning, the methods by which systems learn from data, with AI evaluation and assurance engineering, the engineering discipline of testing and assuring them. It extends to robotics and automation, where AI controls physical machines, and to high-performance, cloud and edge computing, the infrastructure that trains and runs models.

As a risk field it is defined by consequences: what happens when a model generalizes badly, when an agent misuses a tool, when a robot misreads its environment, or when many systems share the same flaw. social and behavioural science is part of the field because the effects of AI depend on how people use, trust and contest it.

02Canvas

One field, three institutions.

Canvas · one field, three institutionsDesign, not a record
One field, three institutions: Artificial Intelligence and Autonomous Systems and its counterpartsGCRI studies the field as science, GRF governs and convenes it, GRA builds shared financial understanding; the Nexus Universe tests work across them and the competent authorities decide. Design of the arrangement, not a record.

Fig.How GCRI, GRF and GRA share one field while the authorities decide. Design, not a record.

03Why it matters

AI is becoming infrastructure.

  • AI is moving from advisory tools to systems that act, through software agents and physical autonomy.
  • Public services increasingly use automated systems in decisions about people's rights and access.
  • A small number of model providers, cloud platforms and chip supply chains underpin many applications.
  • Evaluation science lags capability, so claims about safety and performance are often hard to check.
04Console

Field overview, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Field overview: the screen's structure, terms and states for AI and autonomous systems.Placeholder names and illustrative values; a design, not a record or a live system.
05What experts study

The core questions.

  1. 01

    Measurement

    Do evaluations measure what they claim, and do results generalize? See Model evaluation.

  2. 02

    Action

    How should authority be delegated to systems that act? See Agentic systems and Autonomous physical systems.

  3. 03

    Security

    How can models be attacked, and how can AI change cyber offence and defence? See AI and cyber security.

  4. 04

    Use

    How does AI change science and public services? See AI in science and AI and public services.

  5. 05

    Foundations and effects

    What does AI depend on, and whom does it affect? See Compute and energy and Labour and social effects.

06Connections

How AI touches other risks.

AI connects to cybersecurity, energy, labour markets, finance and public trust. Dependencies and consequences explains those links. Governance is convened through AI and Digital Governance at The Global Risk Forum (GRF), and financial-sector model risk is studied through AI and Financial Model Risk at The Global Risk Alliance (GRA).

07Pages

Pages in Field overview.

08Questions

Questions and answers.

Is this field the same as AI ethics?
It overlaps, but its focus is measurable behaviour and failure: validity, robustness, security, reliability and effects, studied with scientific methods.
Which methods does the field rely on?
Machine learning, AI assurance engineering, computing, probability and statistics, cybersecurity, social science and robotics. Each is described on the STEM foundation page.
Does the field cover military AI?
The platform's scope is civilian systems and their public effects. It does not work on weapons development.
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