Labor and Employment
Jobs are a critical gateway to economic opportunity.
We work to ensure that technologies promote equity across the employment lifecycle, and that employers are held accountable for their use. We have written research reports on predictive hiring technologies and equity, scrutinized the digital hiring practices of large hourly employers, and testified in front of regulators and legislators across the country. We continue to support modernized civil rights laws and regulations across the country, and support the use of hiring tools that mitigate bias and discrimination.
Aaron Rieke, Urmila Janardan, Mingwei Hsu, and Natasha Duarte
In this report, we investigate how large hourly employers are using technology to hire for low-wage hourly jobs. We scrutinize 15 online application processes, raise concerns with selection procedures like personality tests, and offer recommendations for employers and policymakers.Read more
Latest work in this issue areaAll work in this issue area
We submitted comments to the EEOC’s Draft Strategic Enforcement Plan for 2023-2027, pushing for more proactive support of civil rights in recruiting and hiring.
We sent a memo on technology’s role in hiring discrimination to agency leaders within the Biden administration.
Without active measures to mitigate them, bias will arise in predictive hiring tools by default. This report describes popular tools that many employers currently use, explores how these tools affect equity throughout the entire hiring process, and offers reflections and recommendations on where we go from here.
In the Harvard Business Review, Miranda explains what we mean when we talk about “hiring algorithms” and why predictive hiring technology is far more likely to erode equity than it is to promote it.
Selected press and events
Urmila Janardan was quoted in Bloomberg Law: “The farther a job evaluation strays from the essential functions of the job, the more likely it is to discriminate by disability.”
Aaron Rieke speaks to Recode about how AI hiring systems can be ineffective and even discriminatory.
I’m really skeptical that there’s real validity there, said Aaron Rieke.
“Technology can’t do that hard work for you,” Rieke said. “AI is not a panacea or a solution to bias.”