D&I and the Rise of the AI Machines: Understand they’re as (un)inclusive as we make them

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Are you interested in learning about the intersection of diversity and inclusion (D&I) and artificial intelligence (AI)?

There are many reasons why HR professionals should be interested in D&I and AI. Here are a few:

D&I is good for business. Studies have shown that companies with more diverse workforces are more profitable, innovative, and customer-focused.

AI can help HR professionals achieve D&I goals. AI can be used to identify and address unconscious bias, track progress on D&I initiatives, and create more inclusive workplaces.

AI can help HR professionals save time and money. AI can automate many HR tasks, freeing up HR professionals to focus on more strategic work.

AI can help HR professionals improve employee engagement and retention. AI can be used to provide personalised employee experiences, create more flexible work arrangements, and help employees develop their skills and careers.

Join us for a free webinar featuring D&I experts.

As AI continues to develop, it is likely that HR professionals will find even more ways to use it to support D&I in the workplace. By staying up-to-date on the latest AI trends, HR professionals can ensure that they are using this powerful technology to its full potential.

Who Should Attend:

This webinar is for anyone who is interested in the potential for bias in AI systems and how we can mitigate it.

To register for free click here.

Programme

In this session, you'll gain valuable insights into how to ensure that the AI machines we develop are as inclusive as we make them. You'll learn about the potential biases that exist in recruitment and HR processes, as well as in society at large, and how to mitigate them through careful development and use of machine learning algorithms.

Topics Covered:

The potential for bias in AI systems

How to mitigate bias in AI systems

How to ensure that AI is used to help us progress

D&I and the Rise of the AI Machines: Understand they’re as (un)inclusive as we make them