Help wanted: an examination of hiring algorithms, equity, and bias
By Miranda Bogen, A. Rieke. 2018
247 citations recorded by the source corpus.
Subfields: AI Ethics, Fairness & Society
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In AI Ethics, Fairness & Society
- Luca Oneto
- Berk Ustun
- Manish Raghavan
- Emilio Ferrara
- Jon M. Kleinberg
- Silvia Chiappa
- Karen E. C. Levy
- Arjan Durresi
Citations in the corpus
- A Causal Bayesian Networks Viewpoint on Fairness (2018, neutral): “Machine learning is increasingly used in a wide range of decision-making scenarios that have serious implications for individuals and society, including financial lending [10,36], hiring [8,28], online advertising [27,41], pretrial and immigration detention [5,43], child maltreatment screening [14,4”
- Actionable Recourse in Linear Classification (2018, background): “A model should provide recourse to its decision subjects in applications such as lending [40], hiring [2, 9], insurance [38], or the allocation of public services [11, 39].”
- Trustworthy AI: From Principles to Practices (2021, background): “Such breaches can range from biased treatment by automated systems in hiring and loan decisions [49, 146] to the loss of human life [52].”
- Fairness in Machine Learning (2020, background): “Machine Learning (ML) is increasingly used in a wide range of decision-making scenarios that have serious implications for individuals and society, including financial lending [20, 120], hiring [17, 77], online advertising [72, 150], pretrial and immigration detention [10, 158], child maltreatment s”
- Trustworthy Artificial Intelligence: A Review (2022, methodology): “The hiring algorithm used by a major tech company was found to be biased against women [20].”
- Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models (2023, background): “This could lead to the perpetuation of existing inequalities in the job market, limiting opportunities for affected individuals and reducing diversity in the workforce [102, 103].”
- Mitigating bias in algorithmic hiring: evaluating claims and practices (2019, methodology): “5 We supplemented this list with an inventory of relevant companies found in recent reports by Upturn [14], a technology research and advocacy firm focused on civil rights, and RedThread Research [39], a research and advisory firm specializing in new technologies for human resource management.”