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Preprint (Author's original)arXiv.org - Non-exclusive license to distribute, Open
Preprint
Workforce pDEI: Productivity Coupled with DEI
arXiv.org
01 Dec 2023
Abstract
Ranking pertaining to the human-centered tasks -- underscoring their
paramount significance in these domains such as evaluation and hiring process
-- exhibits widespread prevalence across various industries. Consequently,
decision-makers are taking proactive measurements to promote diversity,
underscore equity, and advance inclusion. Their unwavering commitment to these
ideals emanates from the following convictions: (i) Diversity encompasses a
broad spectrum of differences; (ii) Equity involves the assurance of equitable
opportunities; and (iii) Inclusion revolves around the cultivation of a sense
of value and impartiality, concurrently empowering individuals. Data-driven AI
tools have been used for screening and ranking processes. However, there is a
growing concern that the presence of pre-existing biases in databases may be
exacerbated, particularly in the context of imbalanced datasets or the
black-box-schema. In this research, we propose a model-driven recruitment
decision support tool that addresses fairness together with equity in the
screening phase. We introduce the term ``pDEI" to represent the output-input
oriented production efficiency adjusted by socioeconomic disparity. Taking into
account various aspects of interpreting socioeconomic disparity, our goals are
(i) maximizing the relative efficiency of underrepresented groups and (ii)
understanding how socioeconomic disparity affects the cultivation of a
DEI-positive workplace.
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Details
- Title
- Workforce pDEI: Productivity Coupled with DEI
- Creators
- Lanqing DuJinwook Lee
- Publication Details
- arXiv.org
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Other Identifier
- 991021880165104721