ArticleNature communications2018
Cooperating with machines.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed.
- Group formation on a small-world: experiment and modelling.Journal of the Royal Society, Interface · 2019Trial
- Applications of human-machine collaborative decision-making: A review of research with recent developments.iScience · 2026Review
- When Wholes Resist Decomposition: A Spectral Measure of Epistemic Emergence.Entropy (Basel, Switzerland) · 2026Article
- Human-AI collaboration: trade-offs between performance and preferences.Cognitive research: principles and implications · 2026Article
- Testing for completions that simulate altruism in early language models.Nature human behaviour · 2025Article
- The science fiction science method.Nature · 2025Review
- Rewards and punishments help humans overcome biases against cooperation partners assumed to be machines.iScience · 2025Article
- Irrational herding persists in human-bot interactions.Scientific reports · 2025Article
- Evolving general cooperation with a Bayesian theory of mind.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Human cooperation with artificial agents varies across countries.Scientific reports · 2025Article
- Evolution of indirect reciprocity under emotion expression.Scientific reports · 2025Article
- Social Preferences Toward Humans and Machines: A Systematic Experiment on the Role of Machine Payoffs.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025Article
- Cooperative bots exhibit nuanced effects on cooperation across strategic frameworks.Journal of the Royal Society, Interface · 2025Article
- AI-enhanced collective intelligence.Patterns (New York, N.Y.) · 2024Review
- GPT-3.5 altruistic advice is sensitive to reciprocal concerns but not to strategic risk.Scientific reports · 2024Article
- Enhancing social cohesion with cooperative bots in societies of greedy, mobile individuals.PNAS nexus · 2024Article
- Article
- Facilitating cooperation in human-agent hybrid populations through autonomous agents.iScience · 2023Article
- Exploring the World of Membrane Proteins: Techniques and Methods for Understanding Structure, Function, and Dynamics.Molecules (Basel, Switzerland) · 2023Review
- The effects of social presence on cooperative trust with algorithms.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultural norms, emotions, signals, and pre-evolved dispositions. Here, we develop an algorithm that combines a state-of-the-art reinforcement-learning algorithm with mechanisms for signaling. We show that this algorithm can cooperate with people and other algorithms at levels that rival human cooperation in a variety of two-player repeated stochastic games. These results indicate that general human-machine cooperation is achievable using a non-trivial, but ultimately simple, set of algorithmic mechanisms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.