In this episode, Jamey explores the growing impact of artificial intelligence (AI) on diversity, equity, and inclusion (DEI) initiatives within organizations. Jamey opens with a balanced perspective, noting that while AI can be a powerful tool for supplementing an organization’s DEI capacity—especially with tasks like data synthesis, trend analysis, and policy review—it also comes with significant limitations and potential risks if not applied thoughtfully. The episode discusses why you need to be cautious when viewing AI as a silver bullet. Instead, advocate for a considered, human-centered approach to integrating AI into DEI strategies.

Jamey outlines the key challenges associated with AI, such as its inability to understand organizational context, the risk of bias and misinformation, and the oversimplification of complex DEI work. He emphasizes the importance of human oversight, transparency, and organizational guidelines for responsible AI use. The episode also provides practical use cases where AI can play a supplementary role in DEI, such as landscape analysis, programming, data review, and inclusive practices—always underscoring that human review and contextual adaptation are crucial. Listeners are encouraged to approach AI as a means for improved effectiveness within DEI rather than efficiency, and to remain open-minded but cautious about its integration.

To learn more and connect with Jamey, visit: www.Equity-At-Work.com

List of Key Topics Discussed:

• The dual narratives around AI: evangelism and doomsaying
• AI’s strengths and limitations in supporting DEI initiatives
• The importance of intentional, careful, and human-guided AI usage
• Challenges of anthropomorphizing AI and oversimplifying DEI work
• The black box problem: algorithmic transparency and bias
• Human irreplaceability in relationship-building, critical thinking, and context adaptation
• Practical use cases for AI in DEI (e.g., trends analysis, policy review, program support, hiring, data benchmarking)
• The necessity of human review and context-specific adaptation of AI outputs
• Recommendations for developing organizational guidelines on AI use in DEI

I'm Jamie Applegate, Senior Director of DEI at EquityAtWork, and this is your DEI minute, your go to podcast for leaders looking to navigate the ever evolving landscape of diversity, equity and inclusion in the workplace. Whether you're just starting out with DEI or looking to sustain your long term successes, each episode will provide you with the actions you can take to move DEI forward at your organization, all in 15 minutes or less. Join us every other week as we break through the noise and help you do dei. Right. Let's get to it. Today we're going to talk about artificial intelligence and its applications in diversity, equity and inclusion efforts. I want to start by sharing that AI absolutely can be a powerful tool that adds to an organization's capacity as it designs, develops and implements DEI for its strategies and initiatives. AI has valuable DEI applications through an organization's operations and and across the employee lifecycle.

That being said, AI also has significant limitations and its implementation can bring serious negative consequences if it is done haphazardly. It is necessary to be intentional and thoughtful when utilizing AI for DEI work, or for any work for that matter. I say this because the typical narrative around the use of AI in any field and in DEI is that people tend to fall into one of two camps. So on the one side, there are folks who see AI as the bright, singular future. They are AI evangelists. AI is going to do everything for us. It will solve all of our problems. It will fix everything.

On the other side, there are those who think that AI is likely going to destroy the world. It's going to use huge amounts of energy, it is going to destroy the climate and the planet, it will exacerbate already massive income inequality, and it will ruin people's lives by taking away their jobs. So I just want to recognize that those are the two camps that people sort of tend to fall along this narrative. But I actually think that most people fall somewhere in the middle believing that AI can be transformative, but that like any type of technology that is disrupting the status quo, it can also have significant unintended negative consequences. So I just want to pause there and say AI can be a really helpful tool, but you got to be careful with it. So that's what we're going to talk about today. We believe that companies can and should use AI in their DEI efforts, but that it should be done carefully. So for today's episode, we're going to start with the challenges to effectively applying AI and DEI work.

We just want to make sure that we're really aware of what where Things could go wrong. So first off, AI platforms provide statistical and pattern based analysis, not actual knowledge. AI platforms are not humans and it is helpful to avoid anthropomorphizing them. So do not assign them human attributes or characteristics or think of them as humans. I know there are tons of stories of people developing very close personal relationships with AI platforms or AI sort of agents. AI platforms are not human. Don't treat them as though they are anything other than text based prediction platforms. So AI platforms can identify and synthesize huge amounts of information, but they can only provide a pre written answer or craft a response based on learned linguistic patterns.

They are not creating knowledge, they are simply parroting what they have seen and predicting what word is going to come next in a sentence. AI platforms cannot determine the veracity of any data or information or the reliability of any source. And that is a very, very, very challenging thing. They can only report what they had fed to them. Next thing is AI generated outputs are responses to human inputs. So AI platforms seek information in response to what we as humans ask for. So AI platforms do not attempt to understand subtext or context or what a human user might be trying to articulate. They only respond to text as it is explicitly written by a human user.

Some of them can respond to audio, but they're breaking that audio down into text and then trying to understand what the text says. They're not understanding emotion or subtext or context. They don't know your organization, they don't know you. They don't know what you're trying to ask for. AI platforms do not think or comprehend or empathize. If an AI platform provides you with something valuable, it is exclusively because your input and all of the creativity and thought and care that went into creating your prompt was good enough to allow the AI platform to find that information. The third thing DEI is deeply sensitive in human work. An organization's DEI efforts must speak to its unique and specific context and culture and support the entire organization, its component parts, and all of its employees.

Fourth, AI makes everything seem simple. But DEI is complex and challenging and it is a misstep. To oversimplify DEI work, AI provides an engaging user experience that is very easy for anyone to use. You ask a question and you get an authoritative, seeming answer. But how do you know you're asking the right questions? So much of what AI provides comes down to the prompts you input as you seek a solution. So the reality is that there is no perfect prompt. So what AI gives you can only be seen as a potential solution. Not the solution that speaks to your problem in your specific context.

Next, AI might have access to huge amounts of information, but it doesn't know you or your organization. AI experts are rarely DEI experts or experts in your organization's DEI work. And DEI experts and experts in your organization's DEI work are rarely experts in dei. This lack of expertise going both ways, combined with the simplicity that AI platforms offer, can lead to mistakes in how best to apply AI to DEI efforts. AI is also guided by algorithms whose inputs and weights we we cannot see. And DEI work relies on proven best practices implemented transparently. AI platforms are essentially black boxes. We cannot see inside them because that is the proprietary information that makes these companies so valuable.

So it's impossible to know what biases might be present in your preferred AI platform or what information or sources the platform prioritizes or downplays. You can see things like on Twitter or as is now called X. Elon Musk says that he is updating the algorithm. He doesn't say what he's doing, he just says that he's updating it based on challenges or information. That's wrong. This is the problem. We can't see what's changing or what's being changed. So AI platforms have access to again, massive amounts of data and information.

Also, the way that they access some of that information is the subject of ongoing lawsuits. But often the source of the information presented is unknown. Sometimes they'll cite a source, sometimes they won't. But often there's an ever present concern that what the platform provides is completely made up and a hallucination. What they found is that these hallucinations are in fact getting worse with the more information that the AI platforms have. So you can ask yourself who's doing the gut check on whether what we're seeing from AI is correct. Finally, AI cannot replicate skills that people contribute to DEI work. AI can only reflect what already exists.

It is a mirror. AI cannot truly know or understand your organization or its people. AI cannot build and sustain productive and meaningful relationships. It can't think critically or creatively. It can't be curious or develop new and innovative ideas. And it can't spend time imagining what could be and how to get there. So that was a long list of serious challenges that come with using AI platforms. Any personal organization that is currently using AI or thinking about using AI or how to use AI should pause and work through those before moving forward.

That being said, those challenges are just that. They're challenges that should not stop you or your organization from using AI. It's all about recognizing how AI might go sort of awry. Because as I mentioned at the top of the episode, it's all about being intentional and acting with care. We have to recognize what we don't know and how something could cause harm, and then we can create an approach that allows us to fill in the blanks and mitigate that harm. So, in short, you and your organization should be open to utilizing AI and DEI efforts, but with care. And so here are a few tips as you explore your organization's openness to utilizing AI and dei. You should absolutely avoid developing an over reliance on AI as the primary driver of your DEI strategy and programming.

Any application of AI in the DEI space should be narrow in scope and conducted within clear and transparent organizational guidelines. As a quick note, this might mean that you need to develop those clear and transparent organizational guidelines before you start using AI platforms. AI can absolutely supplement human capacity, but it should never be considered of replacement for people and what they bring to organizations. Any information provided by AI should be reviewed and verified by a human being to ensure that it meets your organization's specific needs and that the information shared is in fact accurate. Overall, for best results, AI in the DEI space should not be a play for improved employee efficiency or productivity. There's not really actually current data that shows that it improves these things, and it should actually be a play for improved effectiveness both for DEI leaders and for the organization as a whole. Okay, so we understand the challenges to using AI in DEI efforts and we're still on board. So let's talk through a couple quick use cases for this.

I'll share a focus area, what I think AI can do in that area, and then what you should do with the output that your AI agent or platform generates. So first, for example, with DEI landscape, AI can review a wide variety of news sources and synthesize workplace DEI trends and DEI related policy and regulatory updates. You should then take that, review it, identify how those trends and policies and regular updates might impact the organization, and develop your own recommended action plans for a focus area of DEI policies. Again, AI can synthesize huge amounts of available text and identify sample DEI policies. You should take that as a foundation and develop policies that are specific to your organizational context and what your organization needs for something like DEI programing. Again, you can have AI research current trends and DEI best practices, including professional development, leadership development, ergs, things like community engagement. And then when you get that from the AI, you can align those trends with your organizational needs and adapt the AI generated information to your organization's context. And then also one thing you'll want to do is build in timing and sequencing that works for your specific organization.

For something like DEI data analysis, again, AI is phenomenal at analyzing massive data sets, both internal and external, and both text based and numerical, to identify trends, conduct organizational comparisons, and industry benchmarking. You should take what it gives you. You should review it for accuracy, and then you should look at prioritizing those identified trends and determining any additional areas for exploration. And then develop organizational specific goals and recommended actions. For something like inclusive practices. Again, AI can research current trends and support doing things like translation services if you have a multilingual workforce. But the best practice there, you should review that AI generated list of practices, prioritize based on organizational context, and develop action plans with timing and sequencing. And then for anything like language, you should review the AI generated output to ensure accuracy and make sure that you're recognizing that while some people from different countries might speak the same language, there might be different words that they use for various things.

And so you just need to be aware that just because, for example, someone speaks Spanish, they might speak a different Spanish than someone in a different country who also speaks Spanish. And so just be aware that the Spanish that you're getting from AI, which Spanish is it speaking? For something like recruiting and hiring, you can ask AI to identify potential untapped talent pipelines from underrepresented groups and communities, suggest edits to job descriptions and review hiring processes. But again, you should take that and evaluate it to make sure that what it's saying actually makes sense for you all. For employee engagement, you can analyze employee engagement data and identify longitudinal trends, and then you should check those for accuracy. Again, it's hopeful that the AI is absolutely correct, but it might not be fully right. So make sure you're checking the math. For performance management, you can ask it to find best practices or suggest standardized processes. You can ask it to review performance management data to identify potential instances of bias.

Again, the trick for you, review what it spits out. Don't just trust it. And then finally, for something like compensation, you can have it analyze compensation data and identify pay inequities. And then you should evaluate those analyses, confirm whether they are in fact inequities, and then look at the corrective actions that AI gives you, and then use that as the basis for potential decisions. So AI, like any emerging technology, I've been thinking about electricity or the telephone or the Internet or social media. It has the potential to be incredibly disruptive in ways both positive and negative. It is very easy to become an AI evangelist, seeing it only as a benevolent force that does everything faster and better than a human ever could. It's also easy to become an AI doomsayer, believing that AI is going to destroy everything.

If you want to understand this belief, you can just Google or look up the paperclip problem and you'll get a real good glimpse into this worldview. But the right path is to see AI as a potential game changer that also has significant, significant and inherent limits and challenges for dei. AI can help augment the creativity and critical thinking that humans have brought and continue to bring to this space. It can help save time for folks who are stretched thin trying to implement against a massive number of priorities. And it can help employees identify potential problems hiding in massive data sets. AI and DEI can help improve our effectiveness, and that is absolutely worthwhile to explore. So if you are working through how to implement AI within your DEI framework, or you're more broadly looking at AI in your organization, we're here to help. Let us know.

Send us an email or connect us on our website. Thank you so much for listening.