Workshop 1 — Foundations and Research Frameworks for AI Sentence
3 July 2026
3 July 2026 
Online (Zoom) | ⏱ 90-120 minutes
Online (Zoom) | ⏱ 90-120 minutes The Zoom link will be shared with participants ahead of the session.
Overview
This workshop introduces the foundational concepts and research frameworks used to study consciousness, sentience, and related phenomena in AI systems.
Participants will engage with key debates in philosophy and cognitive science, examine leading theories of consciousness, and explore how these frameworks are applied — and challenged — in the context of digital minds.
The session bridges conceptual analysis and empirical research, providing a structured foundation for engaging with questions of AI sentience across scientific, ethical, and policy contexts.
Learning Outcomes (Draft)
By the end of the workshop, participants will be able to:
- Define key concepts including consciousness, sentience, agency, moral standing, and other morally relevant states
- Understand different philosophical positions
- Identify key routes to attributing moral standing and their implications
- Recognise risks of over-attribution and under-attribution in the context of AI
- Describe the current state of scientific understanding of consciousness
- Compare leading theories of consciousness and their potential application to digital systems
- Distinguish between families of theories
- Understand computational functionalism and evaluate arguments for and against its application to AI
- Analyse methods used to assess consciousness and other mental states in AI systems
- Evaluate empirical research relevant to AI sentience and related capacities
- Identify challenges in detecting, interpreting, and individuating potential digital minds
Topics (Draft)
Conceptual Foundations
- Key terms: consciousness, sentience, agency, moral standing
- Competing philosophical perspectives on subjective experience
- Moral relevance and attribution frameworks
Theories of Consciousness
- Overview of leading theories and their assumptions
- Applicability (and limits) in digital systems
- Distinguishing theory families and background frameworks
Computational Functionalism
- Core claims and motivations
- Arguments for and against its application to AI
Evaluating AI Systems
- Methods for assessing consciousness and related mental states
- Behavioural vs theory-driven approaches
- Practical challenges
Empirical Research & Open Questions
- Current research landscape
- Limits of existing evidence
- Challenges in identifying and individuating digital minds
Format
- Lecture and conceptual framing
- Discussion of key theories and research approaches
- Interactive elements and guided reflection