Summary of Allocation Requires Prediction Only If Inequality Is Low, by Ali Shirali et al.
Allocation Requires Prediction Only if Inequality Is Low
by Ali Shirali, Rediet Abebe, Moritz Hardt
First submitted to arxiv on: 19 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computers and Society (cs.CY); Theoretical Economics (econ.TH)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel framework for evaluating the effectiveness of algorithmic predictions in allocating societal resources is proposed. The approach uses a simple mathematical model to assess the performance of prediction-based allocations in various settings, including hospitals, neighborhoods, and schools. The results show that such allocations outperform baseline methods only when between-unit inequality is low and the intervention budget is high. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This framework can help identify individuals for interventions more efficiently. It uses a simple mathematical model to evaluate the performance of prediction-based allocations in different settings, such as hospitals, neighborhoods, and schools. The results show that this approach outperforms baseline methods when there is little inequality between units and the intervention budget is high. |
