Book contents
- The Cambridge Handbook of Behavioural Data Science
- Cambridge Handbooks in Psychology
- Reviews
- The Cambridge Handbook of Behavioural Data Science
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Introduction
- Part IIntroduction to Behavioural Data Science
- Part IIHuman Behaviour
- Part IIIAlgorithmic Behaviour
- Part IVSystems and Culture
- 19Systems, Culture and Human–Machine Teaming
- 20Cognitive Networks as Models of Cognition and Behaviour
- 21Agent-Based Modelling in Social Networks
- 22Modelling Context-Dependent Behaviour
- 23A Short Primer on Historical Natural Language Processing
- 24Behavioural Data in Complex Economic and Business Systems
- 25Applications of Statistical Mechanics and Cyber-Physical Systems to Behaviour
- 26Systems Behaviour for Sustainable AI
- 27Systems Behaviour and Experimentation
- 28Quantum Mechanics of Human Perception, Behaviour and Decision-Making
- Part VApplications
- Part VIConcluding Remarks
- Main Abbreviations and Acronyms
- Glossary
- References
27 - Systems Behaviour and Experimentation
from Part IV - Systems and Culture
Published online by Cambridge University Press: 29 May 2026
Book contents
- The Cambridge Handbook of Behavioural Data Science
- Cambridge Handbooks in Psychology
- Reviews
- The Cambridge Handbook of Behavioural Data Science
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Introduction
- Part IIntroduction to Behavioural Data Science
- Part IIHuman Behaviour
- Part IIIAlgorithmic Behaviour
- Part IVSystems and Culture
- 19Systems, Culture and Human–Machine Teaming
- 20Cognitive Networks as Models of Cognition and Behaviour
- 21Agent-Based Modelling in Social Networks
- 22Modelling Context-Dependent Behaviour
- 23A Short Primer on Historical Natural Language Processing
- 24Behavioural Data in Complex Economic and Business Systems
- 25Applications of Statistical Mechanics and Cyber-Physical Systems to Behaviour
- 26Systems Behaviour for Sustainable AI
- 27Systems Behaviour and Experimentation
- 28Quantum Mechanics of Human Perception, Behaviour and Decision-Making
- Part VApplications
- Part VIConcluding Remarks
- Main Abbreviations and Acronyms
- Glossary
- References
Summary
Understanding systems behaviour through experimentation is at the heart of modern Behavioural Data Science. While earlier chapters have explored the analysis of human and algorithmic behaviour, this chapter centres on the dynamic and often non-linear processes that emerge when individual components – human agents, algorithms, environments – interact within a system. These systems can span sectors, from health and mobility to climate and governance, and are characterised by emergent properties that defy reductionist interpretations. This chapter elaborates on how experimental paradigms, including in silico simulations, real-world interventions and digital twin testbeds, facilitate insight into the adaptive behaviour of complex systems. Anchored in the frameworks of complex adaptive systems, cybernetics and socio-technical experimentation, we articulate the distinct role of Behavioural Data Science in producing actionable knowledge through systems-level interventions. The chapter also interrogates the ethical, epistemological and methodological dilemmas associated with manipulating complex systems and proposes principles for the responsible design of system-wide experiments.
Information
- Type
- Chapter
- Information
- The Cambridge Handbook of Behavioural Data Science , pp. 474 - 487Publisher: Cambridge University PressPrint publication year: 2026
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