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Intro: Hello and welcome to Tech Law Talks, a podcast brought to you by Reed Smith's Emerging Technologies Group. In each episode of this podcast, we will discuss cutting-edge issues on technology, data, and the law. We will provide practical observations on a wide variety of technology and data topics to give you quick and actionable tips to address the issues you are dealing with every day. 

Kendra: Hello, welcome to Tech Law Talks, a new Reed Smith podcast series on artificial intelligence or AI, as it's commonly called. I am Kendra Norwood, a partner in Reed Smith's Global Regulatory and Investigations Practice Group. I'm based in Washington, D.C., and my specific practice area is government contracts. Through the Tech Law Talk series, we will be exploring the key challenges and opportunities that are presented within the rapidly evolving AI landscape, and today we will focus on AI in government contracts. For today's episode, we are very fortunate to have a special guest joining us, Krystal Brumfield, who for the past three and a half years has served as the Associate Administrator for the Office of Government-Wide Policy at the General Services Administration, or GSA. Now, for those who may not be familiar with GSA, it's an independent agency of the U.S. Government that provides centralized procurement and shared services for the federal government, managing a nationwide real estate portfolio, overseeing over $100 billion in federal government contracts for goods and services purchased by the government, and for delivering technology services to millions of both government and public users across dozens of federal agencies. So when we decided to do a podcast on AI and government contracting, Krystal immediately came to mind as the perfect podcast guest to discuss that topic, and I am so glad to have her here today. So welcome, Krystal.

Krystal: Thank you, Kendra. Excited to be here with you and Reed Smith.

Kendra: Wonderful. So if you could start off with a brief introduction of yourself and your role and responsibilities at GSA, that would be great to set the stage for our discussion today.

Krystal: Sure. So I served as the Associate Administrator for Government-Wide Policy in January 2020 through May 2023. In that role, I was designated as the Regulatory Policy Officer, the chief acquisition officer. I also served as the chair of the agency Cyber Supply Chain Risk Management Executive Committee. And as the associate administrator of OGP, it's what we call government-wide policy for short, I oversaw the drafting and promulgation of the federal acquisition regulation, also known as the FOG. IT policy, as well as the Federal Acquisition Institute, which is responsible for training and educating the 20,000 plus federal acquisition professionals across the federal government.

Kendra: Oh, wow. That is such an impressive background and just some really big responsibilities. And again, I think you're the perfect guest to have here today to talk about this topic. So again, thank you so much for being here. So I guess I'd like to start by framing our discussion a bit. I tend to think about AI in government contracting in two ways. So first, I think about how the government uses AI to support the federal acquisition process, and that's from contract formation to contract administration, and ultimately through contract closeout, and using AI in that way to work smarter, faster, and more efficiently. And the second way I think about government contracts AI is the approach used by the government to purchase AI-driven tools through government contracts in order to support agency missions. We are seeing more and more federal government contracting opportunities that are either in whole or in part being released for the acquisition of AI of some type. And so I'm hoping we can address both of those uses of AI during our time today.

Krystal: So, Kendra, you absolutely have described it correctly. It's kind of a two-pronged approach from the way that we see it or saw it in my role as the associate administrator at GSA. We saw it so much so used in our everyday work, really across agency, that once the executive order President Biden issued on safe, secure, and trustworthy development and use of artificial intelligence, the agency decided to hire a chief AI officer because it was that important of a function across the agency. As you mentioned, it's really, it is sort of a new phenomenon when it comes to government contracting. And so one of the other things that we saw when when we are doing procurements is that there was a gap in understanding and knowledge between where we needed to be in the use of AI and the acquisition workforce. And so while I was there, we stood up the GSA Acquisition Policy Federal Advisory Committee, which what we call GAPFAC for short, which is a federal advisory committee that consists of federal, state, local, and government officials, representatives from trade associations. Professors from universities, as well as business leaders from all across the country to really help us, answer problems related to federal contracting. And one of those problems is AI, understanding AI, what it means to the business of federal contracting. And that's one of the key areas that we saw was important. It was a growing trend and it's ever evolving. And so our GAPFAC very soon will be focusing on AI in procurement.

Kendra: Oh, that's wonderful. I had not heard about GAPFAC, but I love the way it seems as if it's using a very collaborative and cross-sector approach with individuals involved sort of at all levels of government, across the government, and even in the private sector. So that sounds really exciting. I look forward to hearing more about what comes out of that. So I guess let's just dive right in as we talk about how AI is used to support the federal acquisition process. Now, during your time at GSA, were there any specific milestones or key developments related to the use of AI other than what you've already mentioned, which is phenomenal, in order to improve contracting procedures?

Krystal: Absolutely. So on the government side, GSA started using artificial intelligence for the pre-award vendor assessment about two years ago. So just to kind of break it down to the listeners of how it works in a very simplified way. You would gather data, relevant data, about potential vendors from various sources. And so this data could include historical performance data, financial records, customer reviews, compliance records, all from available public databases or information that's provided from the vendors themselves. This data is then integrated into a centralized system or platform where our AI algorithms can assess and analyze it. This could involve cleaning the data and standardizing the data to make sure that it's consistent and it's accurate. Then we would move to the scoring and ranking phase where the algorithms would generate scores and rankings for each of the vendors based off of the extracted features and historical data. The scores will reflect the likelihood of the vendors meeting our specific criteria or performing well in the context of the contract that's being awarded. Then we would move to the decision phase where. Final output that we would see would be an AI analysis providing whoever the decision maker is with valuable insights and recommendations, helping the procurement officer or the project manager make a more informed decision on who to invite to further evaluate or negotiate the contract with. And so we've seen this process work many times, the benefits being that we gain more efficiency in the government. It helps us to reduce some of the automated or arduous tasks that we have. We've also experienced there being more accuracy. And so we're reducing more human error throughout the process. As you can imagine, there are lots and lots of contracts, could be a lot of modifications to those contracts. And so to help scale that volume down, AI has been helping in that way. And then it also creates an opportunity for us to rely on data-driven decisions rather than subjective judgments. And so this helps a lot in a lot of different ways. But one of the things that we've been careful about is making sure that it's essential that we ensure that we train the AI models on diversity and representative data sets so that we can manage the bias that data sometimes has, as well as ensuring that we have fair evaluations throughout the process.

Kendra: So that's pretty impressive, Krystal. I'm sort of awestruck right now because it sounds like to me that for all practical purposes, AI is being used to handle pretty much the entire evaluation process up to the point of making those recommendations to the selecting official. And I guess I'm wondering, is there any involvement or is there still involvement by a source selection board or some other human element in this process before the recommendation goes to the source selection official?

Krystal: Absolutely. That human component can't be replaced. Because we know that AI is ever-evolving, it's a new phenomenon that we're still trying to understand. And it is instances where there has created error and biases. Then the human eyes and perspective and analysis remains a key component to keep as a part of the process.

Kendra: Well, that sounds like a win-win. I mean, you know, there could be errors with AI, but of course, as you mentioned, there are often human errors. I mean, it sounds like AI could be used to reduce those. And I would imagine perhaps reduce the amount of protests that we see, which isn't good for my business, but I think overall good for the government if we can sort of eliminate or at least minimize or mitigate that human error factor. So that's great to know. So just moving along, you know, as I understand it, there's two basic categories of AI. So there's traditional AI, which is great for, you know, addressing sort of well-defined problems, performing repetitive tasks, and dealing with very structured data. And then there's generative AI, which is used to work with more unstructured data and sort of designed to learn new content. You've already explained how some of that is already happening in federal government agencies, GSA in particular, sort of using that traditional AI to automate certain manual tasks across the entire government contracts lifecycle cycle. I know Department of Health and Human Services uses it to consolidate certain contract vehicles. I previously worked at NASA. You're at GSA. I know both of those agencies are using traditional AI to deploy robotic processes, basically bots, chatbots that are software-based robots to execute standard rules-based business procedures and interface with the users, the system users. And so, it's sort of that kind of traditional AI, I think that does have the potential to reduce. Workload backlogs, which, as I understand, it can be substantial depending on the agency, in addition to helping agencies conduct procurements more quickly, which is what I think I heard you say as you described the system that's already in place now. I know the Air Force was at one time contemplating using AI to help acquisition professionals better understand these very complex procurement policies, rules, regulations, again, towards towards speeding up that process, which can often be very lengthy and is often something that discourages some companies from wanting to do business with the government just because of the involved process. So it seems as if AI could certainly be used to help that. Now, these are just a few examples. And, you know, there's some who believe that, you know, this kind of traditional AI could be used to completely automate, you know, sort of those early contracting procedures, You know, deciding what type of contract should be used, what contract type should be used, how it should be structured, should it be set aside for small business. You know, they've said that GSA multiple award schedule contracts, the blanket purchase agreements, IDIQ task order contracts, GWACs, the government-wide acquisition contracts, all of those are sort of in many ways specific to GSA And I'm just wondering if you have any thoughts on how specific to those contract types AI could apply.

Krystal: Sure. So, I mean, Kendra, these are all great examples of how traditional AI can be used and has been used to improve and automate procurement processes within the federal government organizations. There are countless ways and things that we can point to that have have been beneficial to using AI. But I also want to make sure that it's important that we keep in mind that by using AI to automate these routine tasks, for example, the market research and the pre-solicitation period that I mentioned earlier, or the contract modifications, invoicing, or the award-free determinations, there can be some pretty substantial financial impacts for the government or even the contractor or both if errors occur around pricing or payments. And so there's all, but there's concerns that we have sometimes when we rely on AI alone, when it's reading regulations, right? It could lead to regulations being misinterpreted in some cases or even possibly misapplied. And so if that happens, it could have some opposite effects of slowing down a procurement process. In ways that we don't anticipate there could be. And so whether it's through increased bid protests or the need to redo procurements when AI generated errors or discovered. Or even if there are a number of unintended consequences with using AI that we know about or don't know about, this by no means is a perfect solution. So we have to weigh the pros and cons when it comes to it, because although there are a lot of benefits to it, there are certain things that we don't know. And in some cases, there are certain errors or inefficiencies that it may cause.

Kendra: Those are all great points. So, you know, as many benefits as AI bring to the table, you know, There are, again, associated risks, and it sounds like the government is taking that into account and factoring that into its use of AI by not eliminating the human element. So I guess turning to generative AI, I was thinking how this could be used to, in some instances, allocate or manage risk. I know that, for instance, it's already being used to collect data points to determine if If a contractor or a prospective contractor is presently responsible, that's a term of art in government contracts, as I'm sure you know, and you have to be presently responsible to be eligible to receive a government, a federal government contract award. So that's, you know, sort of that use of collecting disparate data and bringing it together to make determinations on responsibility. Also, maybe schedule and risk assessments, you know, determining whether, you know, a project is likely to be completed on time, but at the same time, as you mentioned, on the flip side, could have some consequences in terms of setting up some unrealistic expectations to the extent AI isn't factoring into some of the very real considerations that go into whether a project is completed on schedule. Now, again, these are just hypotheticals, well, except for the one about the responsibility determinations. But again, in terms of the generative AI, can you speak briefly on that, the use of that in the government?

Krystal: So I think what you kind of laid out there are all great examples. And we know these and even, in fact, other applications for AI are just around the corner if they aren't already in use. But GSA has really been at the cutting edge and the lead, and we've long recognized the power of generative AI to increase efficiencies, to lower our operating costs, and even to prevent and detect some criminal activity against the federal government. My office, our top priority was to make government efficient. More modern, streamlined, and accessible. That was our North Star, that we drove all of our policies behind that and our drive to make government operations more efficient and effective was to make sure that we're modernizing the way that we're doing things. And the regulations would reflect that, that we were streamlining them to make sure that processes disease were more efficient and they were accessible to all. And so with that in mind, we think that there is power and great benefit from generative AI. A couple of examples that we saw was with creating documents for contracting officials. We also saw we are utilizing pattern recognition and trend analysis of financial data to identify fraud activity in federal financial systems. Using generative AI to create sample data sets that could be used to test software or even customize commercial software for government use. Also, the cybersecurity threat detection could use AI by using it to model trained historical cyber data like network traffic or user interactions so that they could anticipate and respond to the cyber attacks against our federal IT systems, which of course we often know contain very sensitive information related to government contracting, whether that's financial data or confidential and proprietary data that belongs to companies doing business with the federal government agency, but it resides in government systems. So all of these examples really just show the benefit of generative AI. I think the applications are limitless in terms of how AI can improve our operations or the government's operations and also how they can better deliver efficiencies all across the federal government.

Kendra: Wow. I mean, as you said, the possibilities are limitless. You know, it's just the power of data and the power that AI brings to the table in terms of leveraging that data to make things more efficient and more mission focused, as you mentioned, for federal agencies. So just quickly, I want to touch on how the government is going about purchasing these tools, these AI tools that they're using to use traditional regenerative AI in their day-to-day work. I've seen solicitations come along here lately that are for the purchase of AI tools, whether that's the entirety of the procurement or AI is still somewhat embedded as an expectation or an option for a contractor to propose when they are selling or attempting to sell to the government. Now, I guess the biggest thing that comes to mind for me is that have there been any ethical concerns that factor into how the government is going about procuring these AI technologies? And if so, how are they being addressed?

Krystal: Yeah, well, I believe that there are some fundamental requirements that the government only procures AI technology. That it both use, you know, do so responsibly, but also trustworthily. So first, we have to recognize that AI is one of the most profound technological shifts in this generation. And because the space is so large, and because it has so many complexities, I think contracting officers, they should consider cybersecurity. Supply chain, risk management, data governance, and other standards and guidelines when it comes to procuring AI, just as they would any other IT procurements. I think it's critical that our acquisition workforce also work with and consult with the technical subject matter experts like software engineers and data scientists. You know, the good news is that there are several efforts that are underway already to ensure that the ethical AI standards are in place and they exist. For example, GSA and the Department of Defense's Joint Artificial Intelligence Center have a center of excellence effort in place and have had it for several years now that has a focus on advancing AI technology across DOD. The center of excellence has a guide to AI ethics that it promotes the development of ethical AI by adopting AI applications with a human-centered mindset and approach. The guide also includes a series of questions that should be answers to every phase of an AI development project to ensure that there are ethical designs, developments, and deployments within the AI solution, along with any other extensive testing to mitigate unintended consequences from the application of this AI technology. The Department of Defense also has its own policy document on ethical principles of AI. And of course, the president has issued an executive order. That really addresses and really is the foundation of which all of these different policies rest with regards to being in promoting the use of trustworthy artificial intelligence across the federal government. And so absolutely should be ethical considerations. And I think we are seeing a lot more information come out about considerations to think about or require when it comes to ethics.

Kendra: Wow. So it just seems like there's a lot going on, but it also seems like it's being done in a very intentional and thoughtful way in the government, which is reassuring. And I'm sure my clients, our customers that are doing business with the federal government, whether they are selling AI technologies to the government or implementing AI technologies in order to better sell to the government or better perform on government contracts. And so it just, you know, it's encouraging to see that the government is already in many respects leveraging the power of AI in both purchasing as well as in its administration of government contracts. So I guess the last point I want to touch on speaking to sort of my client base is sort of what should government contractors keep in mind as they consider how to incorporate AI into their business models?

Krystal: Sure. Well, companies who are doing business with the government or even those who are interested in entering into the government procurement market space, they should make sure that their company's vision and goals are aligned with the technological evolution that's occurring around AI. I mean, identifying the AI tools that can lead to future business opportunities is essential, I think, for the private sector. I also think that it's also important to consider what business objectives can be better achieved through the use of AI. And just for businesses in general, they should be mindful that AI is going to continue to grow in the government space. It's not going to go anywhere. And so companies have to keep up with that. And they want to be a part of the government solution. They have to prepare for it. And so I think to jump in the game, They got to get involved. They got to be a part of the game. And so they've got to adopt AI as a part of their practice and as a part of their protocol and as a priority in their business.

Kendra: Well, that's very well said. I couldn't agree more. And I think we are right at the point where I want to thank you so much for your time and your contributions today. I think this has been really enlightening for me and hopefully for the listeners as well. Thank you so much. And then we will continue to look forward to everything that comes along with AI in the federal government space.

Krystal: Thank you, Kendra. Appreciate the conversation today.

Kendra: Likewise. Thank you so much for listening and have a great day.

Outro: Tech Law Talks is a Reed Smith production. Our producers are Ali McCardell and Shannon Ryan. For more information about Reed Smith's emerging technologies practice, please email techlawtalks@reedsmith.com. You can find our podcasts on Spotify, Apple Podcasts, Google Podcasts, reedsmith.com, and our social media accounts. 

Disclaimer: This podcast is provided for educational purposes. It does not constitute legal advice and is not intended to establish an attorney-client relationship, nor is it intended to suggest or establish standards of care applicable to particular lawyers in any given situation. Prior results do not guarantee a similar outcome. Any views, opinions, or comments made by any external guest speaker are not to be attributed to Reed Smith LLP or its individual lawyers. 

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