Human-AI cooperation research

Exploring how Humans and Technology Interact

I study human–AI interaction and cooperation through experimental methods. Below is an overview of my work, working papers, teaching and selected projects.

View Publications Email

About Me

I am a PhD student in Sociology at the University of Zurich studying Human–AI cooperation in social dilemmas and group decision-making. My work combines behavioral experiments with sociological concepts. I teach about AI’s impact on social structures and methods for using AI in research, including synthetic replications.

Human–AI Cooperation AI Agents Behavioural Experiments Mixed Methods

Featured Article

Cover image for 'Evading the Algorithm' article

Evading the Algorithm: Increased Propensity for Tax Evasion and Norm Violations in Human–Computer Interactions

2023 Frontiers in Behavioral Economics Open Access

People cheat more when they believe oversight is algorithmic rather than human. Framing the system as a simple automation exacerbates violations, while complex AI framing pulls behavior closer to human inspection. Design & presentation of automated inspectors directly shape compliance.

Read article GitHub Code

Publications

Cover or thematic image for Individualism paper

Individualism: The end of social cohesion? The effects of inequality and group identity on cooperation

Senn, S., Mutzner, N., Oberhauser, V., & Rauhut, H. (2025). Frontiers in Behavioral Economics, 4.

Cover or thematic image for Urban Drones survey paper

‘We Need Time…’: An Expert Survey on Societal Acceptance of Urban Drones

Wang, N., Mutzner, N., & Blanchet, K. (2025). Science and Public Policy, 52(3), 356–374.

Cover or thematic image for Urban Drones review paper

Societal acceptance of urban drones: A scoping literature review

Wang, N., Mutzner, N., & Blanchet, K. (2023). Technology in Society, 75, 102377.

Cover or thematic image for CHI Future Cities paper

AI beyond Deus ex Machina – Reimagining Intelligence in Future Cities with Urban Experts

Mlynar, J., Bahrami, F., Ourednik, A., Mutzner, N., Verma, H., & Alavi, H. (2022). Proceedings of CHI 2022, 1–13.

Cover or thematic image for Deep City imaginaire contribution

A topology of the imaginaire: Urban experts’ vision of AI — Deep City: Climate crisis, democracy and the digital

Ourednik, A., Mlynář, J., Bahrami, F., Mutzner, N., & Alavi, H. (2021, March). Conference contribution.

Cover or thematic image for Interactions essay

Social media platforms are failed cities

Ourednik, A., Mlynář, J., Mutzner, N., & Alavi, H. (2021). Interactions, 28(6), 62–66.

Working Papers

Behavioural Sociology of Humans and Machines

Yasseri, T., Cui, H., Mutzner, N. (2026). In Handbook of Hybrid Intelligence (forthcoming).

Pre-Print

Illustration for Human–AI Cooperation public goods working paper

Bounded Normative Equivalence in Human-AI Cooperation: Group Behaviour, Not Partner Labels, Predicts Cooperation under Anonymous Aggregate Feedback

Mutzner, N., Yasseri, T., Rauhut, H. (2026).

Pre-Print

Illustration for Synthetic Replication working paper

Read the Instrument, Not the Model: Four Preconditions for Synthetic Replication of Behavioural Experiments

Mutzner, N.

Under Review

Illustration for Scientific Misconduct case study working paper

Science Became Pure Fantasy – A Case Study on Neutralization Techniques in Scientific Misconduct

Mutzner, N., Velicu, A., Rauhut, H.

Under Review

Illustration for AI Anomie working paper

AI-Induced Anomie: Shifting Goals and Means in the Age of AI Agents

Mutzner, N.

In Preparation

Human–AI Triangle Negotiation

Godazgar, T., Mutzner, N., Yasseri, T.

In Preparation

Labs & Projects

Society of Human and Machines (SOHAM)

Joint research centre dedicated to understanding how AI and automation are reshaping society.

BRIDGE Lab (DSI)

Bridging the «Wisdom Gap» through research and innovation across sectors and cultures.

Reimagining Artificial Intelligence

SNSF Spark Grant 2019 towards establishing a sociological conception of AI.

Teaching

Data Analysis (Master)

Instruction

Teaches applied quantitative data analysis in R, from data management and visualisation to programming constructs for reproducible work.
Covers the regression models at the core of quantitative social research: linear, generalised linear, and multilevel.
Closes with machine learning, contrasting explaining a relationship with predicting an outcome.
Trains students to read and critically review code, including LLM-generated analyses, so they can use AI tools without using them blindly.

Beyond Algorithms: How AI Reshapes Society (Bachelor & Master)

Original Course Design & Instruction

Critically examines the evolving relationship between humans and AI, focusing on how it reconfigures social structures, agency, and identity.
Analyzes real-world applications across areas such as work, education, and research to understand AI as a transformative social phenomenon rather than just a technical tool.
Evaluates the risks of integration such as bias, inequality, and surveillance while exploring frameworks for AI ethics and human-centered design.
Bridges theoretical concepts with contemporary case studies to envision pathways for a responsible and equitable technological future.

Experimental Design in the Age of Artificial Intelligence (Bachelor & Master)

Original Course Design & Instruction

Explores how AI is transforming social science experimentation from study design and data generation to analysis.
Teaches students to integrate AI tools across the research process.
Includes hands-on replication of an experiment using LLM synthetic participants.
Bridges experimental methods with innovation to rethink how we study human behavior in the age of Artificial Intelligence.

Introduction to Social Norms and Cooperation (Master)

Teaching Assistant

Introduces the study of social norms and experimental methods for cooperation, trust, and norm enforcement.
Engages students through discussions, presentations, and critical readings of landmark studies.
Examines how norms emerge, change, and sustain collective behavior in modern societies.
Combines conceptual insight with practical training to design and evaluate behavioral experiments.

Scientific Methods (Bachelor)

Tutor

Supported students in mastering core techniques of scientific work from literature and data research to the critical discussion of academic texts.
Guided the interpretation of empirical results and effective presentation of scientific findings.
Provided feedback and graded written assignments, fostering analytical and methodological competence.

Get in touch

I’m always happy to connect about research, collaborations, or teaching ideas. Drop me a message or find me on the platforms below.

Email: nico.mutzner@uzh.ch

Office: University of Zurich, Department of Sociology

University of Zurich LinkedIn Google Scholar