Diversity in the workplace can help foster original ideas. It can help businesses reach out to a wider range of customers. It can even bring about a boost in profit and revenue. Yet, while many businesses understand the value of diversity, they also have a tendency to recruit and promote the same type of person, time and time again.
Seeing the invisible
The main culprit for this is unconscious bias – making quick mental judgments about people without even realizing it’s happening. In many ways it’s hard-wired into our brains, making it difficult to identify and even harder to tackle.
These unintentional biases can cause people to make decisions that favor certain types of people ahead of others. It’s why candidates with Asian or African sounding names are less likely to be called in for an interview. It’s why plus-sized employees are still treated poorly in the office. Or why women are underrepresented in the FTSE 100.
The diversity reports regularly published by tech giants such as Facebook, Google, and Microsoft further reiterate the problem: there’s still a lot to be done in terms of boosting the low percentage of female and ethnic minority employees in the industry.
A truly diverse workforce requires more than just box-ticking by HR. It requires businesses to consider a broad range of factors when making everyday work decisions. Gender, race, and age are the obvious ones. But there are less obvious factors – such as an employee’s economic or academic background – that can contribute to a truly diverse work environment.
The million-dollar question is: how can we achieve this?
Technology to the rescue
Innovation in artificial intelligence (AI), Big Data, and automation is adding a dose of objectivity to business decision-making. For example, cloud-based solutions are giving HR managers the insight they need to eliminate bias. AI-powered language detectors can filter out gender-biased wording in job descriptions and performance feedback. This can encourage managers to reassess their language and hiring or promotion decisions. Anonymous recruitment processes can encourage recruiters to focus on skills, rather than a candidate’s first or last name. And tools that compare an employee’s KPIs against tenure can alert managers when someone is consistently assigned fewer or less important tasks because of unconscious bias.
Technology can help HR managers see which areas of their business need fine-tuning in order to encourage diversity, but it’s not infallible. AI can reflect society’s biases; language processing, for example, has been shown to reinforce gender biases (such as associating the word “doctor” with “man” and “nurse” with “woman”). AI is promising, but it can’t always understand context.
Another thing to consider is that technology tends to move faster than government – meaning regulating its effects can be difficult. In the UK, some protections already exist. Government services and businesses must disclose if a decision was made entirely by a machine, and if so, it can be challenged. For businesses, this means being cautious with how some technology is introduced. AI must be brought in for the right reasons and in the most appropriate way. Transparency with all automated processes will be key. Avoiding creating over-hype and spurring ethical fear among the workforce will be important as well.
There’s still a long way to go before technology can address all the problems associated with bias in talent management. And even with the best technology in the world, human judgment will remain important. Because it’s not about calling out people who are guilty of bias, rather, it’s about teaching them to not be biased. Communication with people and coaching them to grow – without bias, but with some tech help – is the future of HR.
Remember: diversity attracts diversity. This needs to be reflected in an organization’s cultural foundation. From there, it will trickle into talent strategy, leadership development plans, and everyday decisions made with candidates, employees, vendors, and suppliers. Leveraging diversity can lead to better outcomes for everyone involved, and if the vision is right, technology can help us make it a reality.
Technology isn’t infallible; it still needs to be taught how to play fair. Find out “How AI Can End Bias.”
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