Generative AI has the potential to transform every industry. According to BCG, the industry leaders we’ll be celebrating in five years will be those who established a clear generative AI strategy in 2024.  

These AI systems use comprehensive training datasets to build complex algorithms that can create new, original content. As you don’t need a degree to benefit from generative AI, all businesses can use this technology to improve efficiency, boost productivity, and enhance customer experience.  

But, with great power comes great responsibility. As of yet, AI systems lack human-like critical thinking skills. This means they’ll accept and learn from the data they’re given, regardless of whether it contains bias. This could cause serious problems further down the line.  

To remain ethical and develop reliable AI solutions, businesses must ensure that the teams responsible for developing such systems include people with diverse backgrounds and perspectives. This will help them create algorithms and products that do not contain bias and better serve a wider range of customers. 

In this article, we’ll delve into what makes diversity in AI so crucial and highlight six tactics you can use to build and maintain diversity within your AI teams.  

 

Why diversity matters in generative AI design. 

With its ability to create content, cultivate ideas, and influence key decisions, generative AI has enormous potential. However, the success of any AI system depends on the quality of the data it’s trained on. If conscious or unconscious biases are embedded in the training data, they’ll be reflected in the model’s algorithm and undoubtedly influence its output.  

Algorithmic biases can have highly damaging consequences. For instance, self-driving cars trained predominantly on data from light-skinned pedestrians now struggle to identify and avoid dark-skinned pedestrians at night. Similarly, AI models used to predict women’s health outcomes contain societal biases that cause diagnoses for Hispanic and Asian women to be far less accurate than for white women. If the teams responsible for developing such models had been diverse rather than homogeneous, these potential biases could have been pinpointed earlier and may not have impacted the final product. 

For AI to be as impactful as possible, it must serve all users with equal accuracy. The easiest way to achieve this is by involving a diverse group of people in the design process. Not only is this crucial from an ethical standpoint, but it’s also a strategic business move. Products developed by diverse teams are more likely to reach and benefit a broader customer base. 

 

How to curate a diverse generative AI team. 

Diverse AI teams aren’t built by accident. Intentional effort is required at every stage of the recruitment process. Here are three tactics that’ll boost your chances of success:  

Reduce barriers in your hiring process. 

Write job adverts that appeal to a wide range of candidates by avoiding gendered language and excessively specific requirements. If you work with an external recruitment partner, make sure they build your talent pipeline from diverse sources. Throughout the interview process, use unbiased recruitment tools (especially those with the power to filter applications) and cultivate a diverse interview panel to help candidates feel represented.  

Include multi-dimensional representation.  

Diversity goes far beyond gender and race. Think about experiential and socioeconomic diversity, too. For instance, adding women to traditionally male-dominated tech teams or hiring individuals who have worked across different industries and geographies will encourage new ways of thinking. 

Encourage interdisciplinary collaboration.  

Involving more perspectives is always a good idea, especially when making mission-critical development decisions. Encourage your AI team to ask ethicists, sociologists, and colleagues in different departments for their opinions.  

How to champion diversity within your organisation. 

Hiring diverse talent is pointless without an inclusive culture that values diverse employees and encourages them to stay. Here are three strategies that’ll help you increase employee retention:  

Start at the top.  

Your leadership team sets the tone for inclusivity. If they lead by example and visibly champion diversity and inclusive behaviour, it’ll ripple throughout your organisation. Their actions should encourage transparency and highlight that diversity is a core value. 

Educate every employee. 

Give all employees the tools to contribute to your inclusive culture by offering mandatory training about topics like unconscious bias and cultural competency. This also reinforces your diversity commitment to potential hires.  

Enforce non-negotiable policies. 

You must create and enforce policies that protect and support diverse hires. These might include flexible work arrangements for working parents, or disabled employees, policies that guarantee fair treatment during performance evaluations, and pre-arranged mentorship programmes that remove the onus from diverse employees to locate and contact potential mentors. 

 

When designing generative AI products, especially those with the potential to influence health outcomes, determine which objects self-driving cars should avoid, or allocate sentences to convicted criminals, it’s crucial to ensure that human and societal biases are not embedded in the model’s algorithm.  

While this is essential from an ethical standpoint, it’s a strategic move, too. Diverse teams are more likely to outperform homogeneous teams, and by encompassing a wide range of perspectives, they’re well-positioned to break into new markets and build products that accurately reflect the needs of a global, diverse customer base.  

To learn more about why diversity should be prioritised and gain further insights into how to hire and retain diverse talent successfully, check out Generative’s latest whitepaper: From Bias to Balance: Strategies for Cultivating Diversity in AI.