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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.06119 |
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| _version_ | 1866914079726108672 |
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| author | Natarajan, Neil Noray, Kadeem |
| author_facet | Natarajan, Neil Noray, Kadeem |
| contents | Organizations (e.g., talent investment programs, schools, firms) are perennially interested in selecting cohorts of talented people. And organizations are increasingly interested in selecting diverse cohorts. Except in trivial cases, measuring the tradeoff between cohort diversity and talent is computationally difficult. Thus, organizations are presently unable to make Pareto-efficient decisions about these tradeoffs. We introduce an algorithm that approximates upper bounds on cohort talent and diversity. We call this object the selection possibility frontier (SPF). We then use the SPF to assess the efficiency of selection of a talent investment program. We show that, in the 2021 and 2022 cycles, the program selected cohorts of finalists that could have been better along both diversity and talent dimensions (i.e., considering only these dimensions as we subsequently calculated them, they are Pareto-inferior cohorts). But, when given access our approximation of the SPF in the 2023 cycle, the program adjusted decisions and selected a cohort on the SPF. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06119 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Possibility Frontier Approach to Diverse Talent Selection Natarajan, Neil Noray, Kadeem Computers and Society Organizations (e.g., talent investment programs, schools, firms) are perennially interested in selecting cohorts of talented people. And organizations are increasingly interested in selecting diverse cohorts. Except in trivial cases, measuring the tradeoff between cohort diversity and talent is computationally difficult. Thus, organizations are presently unable to make Pareto-efficient decisions about these tradeoffs. We introduce an algorithm that approximates upper bounds on cohort talent and diversity. We call this object the selection possibility frontier (SPF). We then use the SPF to assess the efficiency of selection of a talent investment program. We show that, in the 2021 and 2022 cycles, the program selected cohorts of finalists that could have been better along both diversity and talent dimensions (i.e., considering only these dimensions as we subsequently calculated them, they are Pareto-inferior cohorts). But, when given access our approximation of the SPF in the 2023 cycle, the program adjusted decisions and selected a cohort on the SPF. |
| title | A Possibility Frontier Approach to Diverse Talent Selection |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2510.06119 |