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Social Loafing01:37

Social Loafing

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Another way in which a group presence can affect performance is social loafing—the exertion of less effort by a person working together with a group. Social loafing occurs when our individual performance cannot be evaluated separately from the group. Thus, group performance declines on easy tasks (Karau & Williams, 1993). Essentially individual group members loaf and let other group members pick up the slack. Because each individual’s efforts cannot be evaluated,...
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Updated: Jun 12, 2025

Artificial Intelligence Approaches to Assessing Primary Cilia
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Bringing AI participation down to scale.

David Moats1,2, Chandrima Ganguly3

  • 1University of Helsinki, P.O. Box 3, 00014 Helsinki, Finland.

Patterns (New York, N.Y.)
|June 9, 2025
PubMed
Summary

OpenAI funded teams to explore public participation in generative artificial intelligence (AI). The project revealed unspoken assumptions, suggesting broader, external input for future AI development.

Keywords:
AILLMsOpenAIconsensusdemocracyparticipationscalevalue alignmentvalues

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Area of Science:

  • Artificial Intelligence
  • Public Policy
  • Technology Ethics

Background:

  • OpenAI's Democratic Inputs program initiated a project in 2023.
  • Ten teams were funded to develop public participation procedures for generative AI.
  • This study offers a perspective on the project's outcomes.

Purpose of the Study:

  • To review the results of OpenAI's Democratic Inputs program.
  • To identify shared, implicit assumptions within the funded participation projects.
  • To advocate for diverse and external participation models in AI development.

Main Methods:

  • Review of project outcomes from OpenAI's Democratic Inputs program.
  • Interviews with participating teams.
  • Analysis of conducted participation exercises.

Main Results:

  • Identification of several common, unstated assumptions across the 10 teams.
  • Insights into the practical challenges and successes of public participation initiatives in AI.
  • Understanding of the limitations of current participation frameworks.

Conclusions:

  • The project highlighted the need for more explicit and diverse approaches to public input in AI.
  • Alternative participation models, particularly those originating outside the tech industry, are encouraged.
  • Future AI governance could benefit from broader societal engagement.