People do not necessarily accept every positive outcome when they perceive the allocation as unfair or illegitimate.
In the Ultimatum Game, one player proposes a division and the other can accept or reject it. If rejected, neither receives any of the amount being divided. Behaviour also depends on preferences, expectations and context.
People do not necessarily accept every positive outcome when they perceive the allocation as unfair or illegitimate.
A proposer divides a sum of money; the responder may accept or eliminate the entire payoff by refusing. Very low offers are regularly rejected in experiments, despite the loss of a positive payoff.
The paradigm is highly mature, with cultural and contextual variation. No single fairness mechanism explains all rejection behaviour.
Costly veto power combined with social preferences, expectations and norm enforcement may constrain unequal offers.
AI transfer to investigate: Human–algorithm framing, perceived agency and training consequences may influence acceptance. The fairness mechanism itself is old.
Proposed test, not yet conducted: Hold the allocation constant and vary agency (human/AI), the beneficiary, and whether rejection is framed as a training signal for AI. Measure acceptance, fairness and legitimacy.
Descriptive rejection preferences do not constitute a complete normative theory, but they are important evidence about legitimacy and acceptance.
Rejection means neither player receives anything from the amount being divided. Observed rejection can have several motives and does not establish a universal fairness norm.
The full text of Güth et al. (1982) was not available for this account. Henrich et al. (2005, author manuscript pp. 5–6 and 14–17) serves as an additional primary study of game rules and cultural variation. The proposed AI application has not been independently tested.
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