In this thought-provoking conversation with Dr. Cari Miller,<\/a> we dive into the critical process of auditing AI tools. From identifying red flags to navigating Saas contract compliance challenges and adopting best practices, this discussion offers actionable insights to help HR professionals make informed decisions and safeguard their hiring processes.\u00a0<\/p>\n\n\n\n Navigating the AI governance landscape can be challenging and complex. This guide can help you start understanding by first learning how to evaluate AI hiring tools effectively.<\/p>\n\n\n\n Q: Without complicating things too much – what do HR professionals need to know to understand the concept of AI Governance?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>Well, I can tell you about this. There\u2019s a series of books called the Oxford Handbooks<\/a>, published out of Europe, connected to Oxford University. They\u2019ve defined organizational governance<\/em>, and when we talk about AI governance<\/em>, it tends to follow a similar framework.<\/p>\n\n\n\n In a nutshell, governance is built on three pillars: people, policy, and process. And then there\u2019s the overarching culture that shapes how these pillars function.<\/p>\n\n\n\n For example: The process, in this case, would be how you make that policy actionable. In procurement, for instance, you\u2019d include steps like:<\/p>\n\n\n\n It\u2019s about aligning people, policies, and processes to ensure that governance isn\u2019t just theoretical but effectively implemented.<\/p>\n\n\n\n Q: Moving on to AI vendors – why is it important for HR leaders to understand the legal aspects of verifying AI claims for talent acquisition tools?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>We just had an election, and a lot of people are asking, “What does this mean for AI governance and responsible AI?”<\/strong><\/p>\n\n\n\n That is a big question on everyone’s mind right now. As best I can tell, here\u2019s what\u2019s going to continue to happen:<\/p>\n\n\n\n For example, you cannot be discriminated against. These protections have existed since the 1960s. You can’t build a system that systematically declines jobs for people in protected classes\u2014that’s not going to be okay.<\/p>\n\n\n\n With these two points in mind:<\/p>\n\n\n\n It\u2019s critical to stay vigilant and ensure these systems perform in fair and equitable ways. No matter who won the election, this is where we\u2019re headed.<\/p>\n\n\n\n Q: What are some practical steps HR leaders can take to establish clear standards and expectations with vendors right from the start?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>There are a couple of things happening here, and it\u2019s just so human nature\u2014we see this all the time.<\/p>\n\n\n\n You\u2019re almost always approached by a vendor with a shiny new toy. It looks really cool, and they say, \u201cWe\u2019ll let you try it for a year, six months, or even 30 days,\u201d<\/em> or whatever the dangling carrot might be. And you think, \u201cOkay, it\u2019s free\u2014what\u2019s the harm?\u201d<\/em><\/p>\n\n\n\n Next thing you know, you\u2019ve adopted something without:<\/p>\n\n\n\n That\u2019s red flag number one<\/em><\/strong>.<\/em> We always want to make sure there\u2019s a legitimate business need before moving forward.<\/p>\n\n\n\n Before implementing a new AI tool, <\/p>\n\n\n\n Remember: AI isn\u2019t going to magically fix a messy process inside your organization\u2014that\u2019s not how technology works. So, proceed with caution. <\/em>You are in control of what you sign up for. If you manage this step wisely, you\u2019ve already won half the battle.<\/p>\n\n\n\n You also need to ask the right questions and establish responsible expectations and guardrails. For example:<\/p>\n\n\n\n These are the basics, but they\u2019re crucial gates to ensure you\u2019re making informed decisions.<\/p>\n\n\n\n Q: You mentioned that free trials can be a great incentive to explore a tool. What key factors should HR professionals evaluate before signing up for one?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>A free trial is excellent\u2014don\u2019t look that gift horse in the mouth. However, it\u2019s the cart before the horse. What you want to do first is make sure you have a legitimate business problem. Investigate the solution thoroughly.<\/p>\n\n\n\n If all of that checks out, then absolutely, go for the free trial. But don\u2019t start with the free trial and then wonder afterward, \u201cMaybe I should check them out?\u201d<\/em><\/p>\n\n\n\n That approach just doesn\u2019t make sense. So, put the cart behind the horse, and you\u2019ll make smarter, more informed decisions.<\/p>\n\n\n\n Q: When an AI vendor tells you their tool is \u201cbias-free,\u201d what can you ask the vendor to validate that claim?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>It\u2019s really important to investigate what you\u2019re about to buy\u2014or even what you already have in-house. Instead of reacting on the backside\u2014saying, \u201cOh, something happened; now I need to hold you accountable,\u201d<\/em>\u2014focus on the front end.<\/p>\n\n\n\n Ask questions like:<\/p>\n\n\n\n Remember, data tends to decay. If they\u2019re pulling resume data from 20 years ago, that may not reflect today\u2019s reality. I need to know what\u2019s in the system, where it came from, and whether that data was appropriate for its intended purpose.<\/p>\n\n\n\n For example:<\/p>\n\n\n\n It\u2019s important to scrutinize these aspects upfront. If the vendor starts responding with, \u201cWe don\u2019t know,\u201d<\/em> or, \u201cWe\u2019re not sure,\u201d<\/em> or, \u201cIt\u2019s private,\u201d<\/em>\u2014those are potential red flags.<\/p>\n\n\n\n Q: Is it better to hire a third-party compliance professional who truly understands what a tool is claiming to do? Is that a good way to approach it\u2014if, of course, it\u2019s feasible?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>Well, that\u2019s a tough question. If I put on my ethics hat,<\/em> I\u2019d say absolutely\u2014you should do that. You need to do that.<\/p>\n\n\n\n But if I put on my practical business hat,<\/em> I\u2019d acknowledge there\u2019s an expense involved, and there\u2019s no definitive answer. Ethics are subjective\u2014your ethics, my ethics\u2014and they don\u2019t always align.<\/p>\n\n\n\n Here\u2019s the balance:<\/p>\n\n\n\n In that case, you\u2019ll need to rely on the rules and regulations as they develop to guide you on what\u2019s working and what isn\u2019t.<\/p>\n\n\n\n Q: What is the current state of companies hiring teams for AI red-teaming, and how are they addressing or overlooking AI governance to ensure responsible use of AI tools?<\/strong><\/p>\n\n\n\n Dr. Cari: <\/strong>It\u2019s a spectrum, as you\u2019d imagine\u2014a bell curve.<\/p>\n\n\n\n On one end, you have very large organizations, particularly multinational companies. They often have entire departments dedicated to this because:<\/p>\n\n\n\n That said, I\u2019m definitely seeing a movement toward greater AI literacy.<\/a> People are starting to realize, \u201cWait a minute, these tools aren\u2019t perfect. Tell me more about that.<\/em>\u201d That\u2019s a positive shift, but overall, I\u2019d say it\u2019s still a bit slow going.<\/p>\n\n\n\n Q: What tools have you seen raising red flags versus those that seem to be taking this seriously?<\/strong><\/p>\n\n\n\n Dr. Cari:<\/strong><\/p>\n\n\n\n For example, an employee could have a neurodivergent condition or even something as simple as an eye infection\u2014factors that these tools often overlook. It\u2019s a broad spectrum, but anything involving voice or video assessments<\/strong> requires extra caution.<\/p>\n\n\n\n For instance, LinkedIn has a Skills Cloud<\/strong> feature. Have you ever downloaded your skill data? It\u2019s fascinating\u2014and sometimes concerning.<\/p>\n\n\n\n For example, they label me as an \u201cexpert digital marketer,\u201d which isn\u2019t accurate anymore due to the decay<\/strong> of those skills. It\u2019s a reminder that even trusted tools have areas requiring scrutiny, especially when it comes to the data they rely on.<\/p>\n\n\n\n As I\u2019ve read through some of their work, the engineers often start with this noble intention\u2014saying things like, \u201cWe\u2019re doing this to match people so they\u2019re well-suited for opportunities.\u201d <\/em>But then, in a small paragraph at the bottom, you\u2019ll find something like, \u201cAlso, this is a revenue-generating tool.\u201d <\/em>Wait a minute\u2014those two things shouldn\u2019t be true at the same time. That\u2019s not okay.<\/p>\n\n\n\n I\u2019ve noticed that HR professionals are struggling to sift through the muck and get to the bottom of these issues. And honestly, this is where you really need an expert to help guide you.<\/p>\n\n\n\n Over time, I think this will get worked out. But for now, it\u2019s a really murky area.<\/p>\n\n\n\n Q: Going back to the video interview tools we were just discussing, would you say it\u2019s too soon to rely on those tools at all?<\/strong><\/p>\n\n\n\n Dr. Cari:<\/strong> Yes. Let me give you an example from one organization. I won\u2019t name names, but here\u2019s what they did:<\/p>\n\n\n\n I spoke with their engineers, and they designed their video interview tool in a very specific way. They asked job-specific questions based on O*NET<\/strong> standards<\/a>\u2014questions tailored directly to the job role.<\/p>\n\n\n\n Here\u2019s the key part:<\/p>\n\n\n\n That\u2019s it. They included some summaries, but the process only involved the words<\/em> coming out of the candidate\u2019s mouth. This approach removed potential biases, like skin color, lighting conditions, or any other visual factor. I can get on board with that because it focuses solely on what the candidate is saying.<\/p>\n\n\n\n But here\u2019s the problem\u2014most video interview tools aren\u2019t even doing it that way.<\/p>\n\n\n\n Q: What are best practices for companies when it comes to adopting AI tools?<\/strong><\/p>\n\n\n\n Dr. Cari:<\/strong> <\/p>\n\n\n\n
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You might have a policy that states, \u201cWe want to ensure all AI tools we use are fair and equitable, without discrimination. If an issue arises, there will be a process for reporting, investigating, and addressing it.\u201d<\/em><\/p>\n\n\n\n\n
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