• Opinion
  • November 8, 2018
  • 7 minutes
  • 1

Blind hiring is curbing biased decisions — using algorithms and AI

Opinion: A "white" name can dramatically increase chances of being invited to a job interview

blind hiring

This piece was written by Ulf Rinne (IZA — Institute of Labor Economics). It can also be found in our future of work newsfeed.


“If you’ve got the grades, the skills and the determination, this government will ensure that you can succeed.” These were the words of then Prime Minister David Cameron in October 2015 in light of recent findings on biased recruitment decisions. In many instances, job applicants are — consciously or unconsciously — judged on the basis of prejudices and stereotypes rather than solely in terms of their qualifications, talent and experience.

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For example, a different name alone can dramatically decrease the chances of being invited to a job interview. In the United States, a pioneering study found that the callback rate for a job interview was nearly 50% higher for applicants with “white” names (Emily Walsh and Greg Baker) than for otherwise similar persons with African-American names (Lakisha Washington and Jamal Jones).

The callback rate for a job interview was nearly 50% higher for applicants with “white” names

Similarly, evidence from Sweden finds 50% more callbacks using a Swedish name than a Middle Eastern name when sending out otherwise equal applications to real job offers.

Application photos can aggravate the problem. When résumés of the same fictitious female character, differing solely in her name and application photo, were sent out in Germany, callback rates were strikingly different. In this study, the character’s first version with a German name (Sandra Bauer) had a callback rate of 18.8%, its second version with a Turkish name (Meryem Öztürk) a callback rate of 13.5%, and its third version with the same Turkish name, but additionally wearing a headscarf on the photo, a very low callback rate of just 4.2%.

Hiring discrimination on the basis of race, gender, age, sexual orientation or religion is thus well documented. This is not only unfair and costly for the victims, but it also has substantial economic costs for society. So what if the key information categorising individuals into minority groups was removed from the application?

Leading graduate employers responsible for 1.8 million jobs in the UK committed to name blind hiring

As a response to Cameron’s speech in 2015, leading graduate employers responsible for 1.8 million jobs in the UK committed to name blind hiring. Most recently, the Bank of England implemented anonymous applications to minimise the bias in recruitment and to boost diversity. But blind hiring has also begun to go global. To isolate the effects of anonymous job applications, field studies have been conducted in Europe, Canada and Australia.

While, intuitively, blind hiring processes should lead to more objective decisions, they are not a universal remedy against all forms of discrimination in the labour market. For example, biased decisions can still be taken when applicants and recruiters physically meet, that is, in the interview stage. In that case, discrimination would simply be postponed. Often, it is also the case that the scope for removing identifying information is limited. For instance, episodes of maternity leave indicate the applicant’s gender, while bilingual applicants can be easily assumed to have some form of immigration history.

A suboptimal method of de-identifying application documents can also result in high costs — not only monetary, but also resulting in time-consuming, labour-intensive and error-prone procedures.

However, pilot projects show that when using an efficient method of de-identifying application documents, blind hiring can be successful in terms of effectively reducing discrimination. As expected, in most studies callback rates between minority and majority groups converge when anonymous job applications are introduced. The resulting effect, however, depends on the extent of discrimination prior to the introduction of anonymous applications. Affirmative action also becomes harder to implement.

Nowadays, more and more employers try to overcome prejudices and biases by relying on innovative recruitment processes

Nowadays, more and more employers try to overcome prejudices and biases by relying on innovative recruitment processes. And new possibilities are becoming available. For example, GapJumpers, a Silicon Valley start-up, offers employers anonymous screening of job applicants. The idea is to reverse conventional hiring. Before submitting any documents or personal information, applicants take custom-tailored anonymous tests that take the specific job requirements into account. And just with the resulting test scores at hand, hiring firms decide whom to invite for interview.

This is just one example how to take advantage of technological progress to combat hiring discrimination. In the future, digital recruitment methods may even become standard. For example, LinkedIn has just announced to use artificial intelligence features in the hiring process. And unless human programmers insert prejudices and stereotypes in the underlying algorithms, there is hope for objective recruitment decisions. — Ulf Rinne

(Picture credit: Unsplash/Hunters Race)

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