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SUMMARY:Does AI de-Bias Recruitment? Race\, Gender\, and AI's ‘Eradicati
 on of Difference Between Groups’  - Dr Eleanor Drage\, University of Cam
 bridge Centre for Gender Studies
DTSTART:20220222T131500Z
DTEND:20220222T140000Z
UID:TALK167119@talks.cam.ac.uk
CONTACT:Manu Sasidharan
DESCRIPTION:AI is currently extensively deployed in recruitment technologi
 es with little regulation or guidelines either from within corporations or
  from external regulatory bodies. We’re seeing a huge demand among HR pr
 actitioners for AI-powered software that reduces HR costs and streamlines 
 the recruitment process\, while simultaneously allowing them to achieve co
 rporate DEI goals. However\, recruitment stakeholders often have a limited
  understanding of how AI-powered tools work. In this paper\, we look at ho
 w gender studies and critical race theory can interrogate some of the clai
 ms made by Recruitment AI companies about how their tools help mitigate bi
 as\, and demonstrate why practitioners should be attentive to how differen
 ce is produced rather than making futile attempts to remove it altogether.
  We discuss four limitations of anti-bias measures in AI for hiring: 1) de
 biasing measures treat race and gender as isolatable characteristics or at
 tributes\, rather than systems of power\; 2) outsourcing ‘diversity work
 ’ to technologies may ignore or distract away from systemic inequalities
  in organisations 3) AI-powered hiring tools replicate the unequal power r
 elations between the observer and the observed\; 4) AI hiring software pro
 duces the ideal candidate it supposedly identifies. We close with three re
 commendations regarding the use of AI-powered hiring tools and software.
LOCATION:Darwin College\, Richard King Room
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