Funders test algorithms to spot promising science, raising hopes of faster reviews—and fears of bias



Summary

Funders are experimenting with AI algorithms to streamline the grant review process, aiming for faster and more efficient identification of promising research. These algorithms analyze data like past publications and grant history to predict success, potentially speeding up review cycles and reducing administrative burden. However, the use of AI also raises concerns about potential biases embedded within the algorithms, which could disproportionately favor certain researchers or institutions, hindering innovation and perpetuating existing inequalities in funding distribution. The success of this approach hinges on ensuring fairness and transparency in the algorithm’s design and application.

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