It’s how we use the AI, not the technology itself, that enables us to solve problems and build a better working world.
It’s no surprise, emerging technology continues to transform organizations and entire industries. Artificial intelligence (AI) is equipping workforces with super powers, helping to cure diseases and pushing the boundaries of space exploration. At EY, AI is allowing our people to complete tasks faster and more accurately than ever before, so they can focus on more meaningful work for our clients.
There’s tremendous opportunity in AI and today’s business leaders are seeing its benefits. However, as we push the boundaries of innovation, we should do so responsibly. With inequality and widening gender gaps creating social divides, business leaders must be diligent in how they develop and use AI technology to ensure it helps, not hinders, inclusive growth.
As CEOs discuss key issues facing business and society at the World Economic Forum, here are three ways business leaders can take a responsible approach to AI:
1. Address biases
In addition to solving complex problems quickly and accurately, AI is also being used to reduce human bias in decision-making processes. If you look at AI tools for hiring, they can help organizations eliminate some biases so hiring decisions are based on desired capabilities and the innate skills of candidates.
At the same time, if biases are embedded in the hiring tool (such as workforce preferences by gender or ethnicity), the AI will reinforce this unintended bias in the hiring process.
Therein lies the responsibility of humans in the process. If we’re programming biases into AI technology, the future success and inclusive application of it cannot be fully realized. When developing AI, it’s critical to recognize biases, scrutinize algorithms and test the outcomes at every stage.
2. Diversify talent
To avoid programming biases into AI technology and contributing to broader social inequalities, business leaders also need to attract and hire diverse talent.
Why? There is a clear correlation between the lack of diversity in AI talent and distortions in some machine-learning outcomes. Unfortunately, technology fields continue to be male dominated and it’s estimated that only 18% of women hold top positions in AI disciplines.
Business leaders must ensure their talent pools are gender-balanced and representative of people and teams with the right mix of skills, experiences, education backgrounds and social, cultural and professional perspectives. This mix of diversity is critical at every stage of AI development.