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AI Unbiased: Creating a Fairer Future

This image is a stylized representation of a human head, created using a circuit board design. The head profile is filled with intricate lines and patterns resembling electronic circuitry, set against a solid background.

In today's tech-driven world, AI has become a cornerstone of workplace efficiency and decision-making. However, it’s crucial to acknowledge that AI is not inherently objective. In fact, AI can often perpetuate and even amplify social biases. As human-centered leaders, we must recognize and address these biases to ensure fair and inclusive workplaces. 


Every part of the process in which a human can be biased, AI can also be biased. And the difference is technology legitimizes bias by making it feel more objective, when that’s not at all the case. -Nicole Napolitano, director of research strategy at the Center for Policing Equity

Some ways that AI perpetuates biases according to UNESCO:


  • Recruitment: AI algorithms used in resume screening and candidate selection can perpetuate biases, leading to discriminatory outcomes against minorities, women, and 2SLGBTQ+ individuals.

  • Performance evaluation: AI systems may use biased metrics for performance evaluations, undervaluing contributions from diverse employees and creating feedback loops that hinder their career progression.

  • Promotion and Career Development: AI might favour career paths typical of the dominant group, disadvantaging those who don't fit this mold and perpetuating inequality in advancement opportunities.

  • Decision-Making and Policy Enforcement: AI systems enforcing workplace policies might apply rules unevenly, disadvantaging certain groups if not carefully designed and monitored. 



As leaders, we must not fall into the trap of assuming AI is infallible. Let’s commit to being vigilant and proactive in ensuring that our AI systems serve everyone fairly by:


  • Understanding the contexts where AI can mitigate bias and where it might exacerbate it

  • Implementing ethical guidelines and provide comprehensive training

  • Forming a diverse task force to ensure data inclusivity

  • Maintaining consistent human touchpoints throughout AI processes

  • Investing in diversifying the AI field by improving AI education and providing access to tools and opportunities



By actively working to identify and correct biases, we can harness AI’s potential while promoting a more equitable and inclusive workplace.

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