AI in Transforming Diversity Equity and Inclusion – ep.147

In this episode, we explore how artificial intelligence is transforming Diversity, Equity, and Inclusion (DEI) initiatives in organizations. Join us as we discuss the ways AI can enhance recruitment processes, eliminate biases in hiring, promote equitable opportunities for underrepresented groups and share success stories from companies leveraging  it. Tune in to discover how AI can be a powerful ally in the pursuit of a more diverse and inclusive future while we begin to understand the risks..

Melyssa Barrett:  Welcome to the jali Podcast. I’m your host, Melyssa Barrett. This podcast is for those who are interested in the conversation around equity, diversity, and inclusion. Each week, I’ll be interviewing a guest who has something special to share or is actively part of building solutions in the space. Let’s get started. Many of you know that I retired from a payment technology company a couple of years ago and really wanted to work in the area of diversity, equity, and inclusion, or DEI some add a B to it for belonging or a J to it for justice and call it Jedi. But at the end of the day, I am drawn to the work. My parents always showed me the way to community engagement. I’ve been working to transition into doing work where I can empower communities, whether I’m consulting on DEI, working with nonprofits, creating content for this podcast, doing success coaching or improving workforce development.

I even find myself working on infrastructure projects. So I’m always thinking about how we can improve the world, especially for marginalized and underrepresented communities. I enjoy working with people that have an eye for building up the country, and there’s a lot of focus, of course, these days on artificial intelligence. And some of the work that I’m doing with the Data Institute focuses on research so that we can facilitate digital equity for all. And in the decades of the years that I worked in the product and risk organizations, I had the benefit of managing a credit reporting agency. I negotiated contracts that exchanged massive amounts of big data, and I explained and managed governance for sophisticated analytic models, machine learning models, and those are used to identify and mitigate fraud credit losses really around the world. So information products has kind of been an area where I have had a focus.

And so by way of example, I watched the credit reporting industry really shift to provide more transparency about the information that’s contained in your credit report, the ability to manage the data included in your report, and what decisions can be made that rely on the information in your credit report. It has certainly increased the levels of objectivity used in those decisions. I’m not going to say life is perfect for sure, but I remember my father telling me about his experiences when he merely walked into a bank and they would refuse to do business with him. And so now data is the new gold as people say. There is so much value in what data you have, what you can do with the data, who owns the data, who’s permitted to use the data, what can be created with the data. And so I thought I would just spend a little bit of time talking about artificial intelligence or ai.

And I just want to say, I mean, make no mistake, the paradigm shift is happening. Artificial intelligence, as we call it, is certainly here. People are relying on AI more. It’s built into a lot of the tools that you’re using, and it is accelerating productivity, no doubt. It is increasing learning and development and so much more when we think about workforce development, your career, even your grandchildren’s careers, they will be totally different. And nearly every city has to grapple with the opportunity to improve their own infrastructure. And yes, we need to invest heavily in infrastructure, but they’re also focused on workforce development, resilience. How do we create an economically thriving place to live, work, and play? We have seen cars shifting from gas to electric, parking sensors being put in, parking lots on traffic lights connected to your phone, connected to your wallet, even in roadways to provide improved logistics.

And yes, all that data is being generated and is being sent or kept somewhere. So as I talk about data, one of the things that I like to talk about is in my career, I have seen data work very well. I have also had the benefit of seeing what is left out of the data. And in many cases, there are lots of people that are left out of the data. Good data produces good products. But obviously as you look at AI powered recruitment tools and recruiting, you have companies using AI to analyze workplace data in real time to identify where underrepresented groups may not be thriving, right? They can then offer tailored recommendations to address the gaps, the use of AI driven language tools to help companies communicate more inclusively changes in language for job postings and internal communications. These are all things that are being done where AI can essentially make it more inclusive and ensure that they’re not excluding any specific groups.

It is ai absolutely a game changer. It can absolutely add a layer of fairness and accountability. And these are just a couple of examples. I mean, AI will cut across every industry and even create some new ones, right? Some of you may remember the movie Hidden Figures, and if you haven’t seen it, make sure you do. But the ladies that are in that movie were at the intersection. They computed things manually, math by hand, and then watched this IBM computer transform the number of calculations that can be done. It accelerated what could be done. And I feel like that’s what we’re watching is AI is accelerating kind of everything exponentially, the amount of data and how it’s processed, the models themselves, and that intersection creates acceleration. And I think AI can now create other models faster than you can even imagine. And so if you get nothing else out of this, this is why the discussion and perspectives of everyone, when we think about equity, diversity, inclusion, these are reasons why it’s so important.

These AI tools can surface biases. These are biases that you may not even realize are there, and there are, and I’m sure there will be unintended consequences. So it’s not just about doing things faster, but it’s also about doing them more fairly. And so when we start talking about diversity, equity, and inclusion, these are reasons why it’s so important with any technology and AI is not perfect, but there are real challenges that we need to be talking about. When it comes to ai, it can absolutely amplify the biases it’s supposed to eliminate if it’s not carefully and intentionally programmed and monitored.

AI learns from data, and if the data reflects inequalities and the biases of our society, it can reinforce them. If a company’s historical hiring data, for example, shows a preference for a certain group of people over others, an AI system could unknowingly replicate the same bias when making those decisions. So these are models that are being used. And then financial services, we created models all the time, and the financial services industry, of course, has a lot of regulations and governance around the models that they use, not only how they’re created when they’re created, but the maintenance and update of those models over time. And even more so after the 2008 mortgage crisis. We need to ensure that we have a focus on transparency when it comes to ai. Some of these AI models are black boxes, meaning we have no idea and don’t understand how it’s even making the decisions it’s making.

And that lack of transparency is driving ethical concerns, especially when decisions are being made, whether it’s hiring promotions, I could go on and on with so many decisions that people are just plugging into AI and using that information for a variety of things, anywhere that people’s livelihoods are on the line. We need to make sure there is enough transparency and we need to understand how those decisions are being made. And so here’s the good news, we can overcome these challenges, right? It starts with transparency and it requires human oversight. Businesses need to audit their AI systems regularly and ensure that it’s doing what it’s supposed to be doing, promoting equity and not hindering it. So diverse teams need to be involved in developing these AI tools, and AI is only as good as the people who create it, use it, train it. So having diverse perspectives included is critical to ensuring fairness and quite frankly, accountability.

When we think about ai, we should also be thinking about privacy, governance, policy, and voting. So we need people to start thinking about how business models can and will be shifted. What used to create a thriving economic environment in a city will be different, right? Even five years from now. So community engagement will be essential. So if you’re not educating yourself about artificial intelligence, not just using it and plugging it in, but educate yourself on ai. You don’t have to be an expert, but get curious about what decisions are being made, what data is being transferred, what data is even in there. There will absolutely be inaccuracies, but just be aware of what may be missing in the information when AI is making the decision. I will be back with some success stories, some conversations with people, and we’ll spend some time talking about AI and practice and other information that may be interesting. So feel free to reach out, leave a comment, let me know what you think, what you’re interested in. We have the power to reshape the world that we live in. We can create spaces where every voice is valued and no one is left behind. So let’s work together and make this a reality.

Thanks for joining me on the Jali Podcast. Please subscribe so you won’t miss an episode. See you next week.

.