The Shared Discovery Paradox: How a One-Answer Rule... | AI Research

The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search
This paper investigates a common organizational failure: when a group pools its information to make a decision, it often ends up less likely to find what it is looking for. While pooling dispersed clues can improve the accuracy of a single recommendation, it often leads organizations to assign all their resources to that one "best" answer. This converts a diverse portfolio of search attempts into a single, repeated bet, effectively wasting the group's collective capacity to cover different possibilities. The author develops a mathematical benchmark to show that this is not a failure of information, but a failure of the protocol used to act on that information.

The Sixteen-Box Benchmark

To isolate this mechanism, the paper uses a simple model: sixteen boxes, one of which contains a jackpot, and eight searchers who each hold a noisy clue about the target's location. If every searcher follows their own clue independently, the group has a high probability of finding the target. However, if the group pools their clues to identify the most likely box and everyone searches there, the group’s success rate drops significantly. Even a coordinator who ignores the clues entirely and simply assigns the eight searchers to eight different boxes will outperform the "informed" consensus. The information is valuable, but the protocol of forcing everyone to agree on one answer destroys the group's ability to cover ground.

Protocol Loss and Coordination

The paper introduces an accounting method to separate the value of information from the efficiency of the action protocol. By comparing the performance of a group to an "attainable frontier"—the best possible outcome given the available information—the author measures "protocol loss." In the canonical model, the gap between the consensus approach and a coordinated portfolio is entirely due to this loss. The research demonstrates that a coordinator only needs seven distinct, well-chosen actions to match the performance of eight decentralized searchers, proving that the primary issue is the compression of a diverse search strategy into a single, redundant choice.

Incentives and Market Behavior

The study also examines what happens when searchers are self-interested and compete for a prize. In this scenario, the group's behavior follows a "water-filling" rule, where searchers balance the probability of a box containing the target against the risk of competing with others for the same prize. While this market-based approach performs better than simple consensus, it still falls short of the ideal, coordinated search. The author identifies a potential fix: a "sole-rescue" reward, which pays only the individual who finds the target alone. This incentive structure encourages searchers to spread out, effectively turning the group into a perfectly coordinated team that achieves the best possible discovery rate.

The Impact of Correlated Information

Finally, the paper explores how "copying"—where searchers rely on the same unobserved sources rather than independent clues—collapses the group's discovery channels. As the probability of copying increases, the advantage of a centralized planner grows, while the effectiveness of decentralized, private search diminishes. In large-scale markets, the research confirms that consensus-based discovery eventually vanishes, while the gap between different protocols remains consistent. The findings suggest that as information becomes more correlated, the need for formal coordination becomes increasingly critical to prevent the group from collapsing into a herd that ignores the breadth of available possibilities.