'Little evidence' unconscious-bias training creates lasting change, says ESRI

'Little evidence' unconscious-bias training creates lasting change, says ESRI

New technologies, such as algorithms and machine learning in recruitment processes, have the potential to reduce labour market discrimination.

There is “little evidence” that unconscious-bias training leads to sustained changes in behaviour, according to new research looking at combating racial discrimination in the labour market.

Due to be published by the ESRI today, the study examines how effective the different measures such as legislation, affirmative action, and equal-opportunities policies are at promoting diversity in workforces. 

There are “consistent” indicators of labour-market discrimination against the black and the Irish Traveller ethnic groups, the report notes, with the highest rates of discrimination and lowest employment rates experienced by Irish Travellers. 

“This suggests that these groups may be in most need of targeted interventions,” it states.

Other non-Irish ethnic groups are also more likely to experience discrimination in the workplace than ‘white Irish’. 

Diversity training tends to work best at increasing minority representation if it is voluntary, and the aims are well communicated, the study notes.

Unconscious-bias training can raise awareness of bias, but there is little evidence that it changes behaviour, it adds. 

There is also a risk that diversity training and unconscious-bias training can be used to ‘tick the box’ regarding pro-diversity efforts, in that they can lead to the assumption that the problem of discrimination has been resolved and no further effort is required,” the report states.

The effectiveness of affirmative action measures "greatly depend" on how they are conducted and communicated, the study found. While such policies that rely on strict quotas for minority groups have been shown to improve ethnic minority representation, such measures have also experienced a considerable backlash in the United States. 

New technologies, such as algorithms and machine learning in recruitment processes, have the potential to reduce labour market discrimination, the study finds, as long as the algorithms used do not replicate previous biases in recruitment. 

Formalised recruitment at “its most basic level, with positions advertised and the use of interview boards” is generally associated with a greater diversity of hires. 

“When designing recruitment processes and job tests, recruiters do need to be careful that they do not unintentionally discriminate against certain groups by design,” the report stated.

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