CZ and Friends

Quantum & Law: Kaniah Konkoly-Thege on Quantum, Policy & Leadership

• Cecilia Ziniti • Season 1 • Episode 5

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How do legal leaders navigate the complexities of emerging technologies like quantum computing while shaping public policy and guiding organizations through change? 

In this episode, Cecilia Ziniti sits down with Kaniah Konkoly-Thege, a legal expert whose journey spans from the Department of the Interior to cutting-edge work in quantum computing. Kaniah shares her experiences working on the historic Cobell case, navigating public policy, and bringing a business-first mindset to legal leadership.

You’ll hear:

– How Kaniah’s early work on the Cobell case shaped her approach to legal problem-solving
– Why understanding emerging technologies like quantum computing is critical for legal leaders
– How general counsels can position themselves as business partners and trusted advisors
– Insights on engaging with policymakers and creating smart, balanced regulations
– Predictions for the future of AI and quantum in legal practice


Follow @Kaniah Whitehorn Konkoly-Thege on LinkedIn.


Book Mentioned:
Killers of the Flower Moon


Show notes:

– Kaniah’s journey from the Department of the Interior to quantum computing
– Lessons from working on the historic Cobell case
– Building technical fluency as a legal leader
– Why public policy understanding is essential for legal strategy
– Balancing innovation with smart, thoughtful regulation
– Predictions for the role of AI in the future of law

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⁠@Cecilia Ziniti⁠ on LinkedIn

⁠@CeciliaZin⁠ on Twitter/X

⁠@GC AI⁠ on LinkedIn

⁠gc.ai⁠ website

Cecilia Ziniti:

What problem are you trying to solve? Even with AI, and I take that problem there too, right? What problems are you trying to solve? And does the framework you're proposing actually solve them? So, right, I mean, and if a lot of it is around data privacy, let's look at the f the data privacy frameworks that exist today, maybe create stronger data privacy, and then like port that over into the technology you're talking about, right? Because otherwise you come up with these really, you know, heavy-handed, blanketed regulatory regimes that create a lot of stress on small startups.

Kaniah Whitehorn Konkoly-Thege:

Welcome back to Susie and Friends, where we talk with legal leaders, technologists, and operators driving innovation and excellence in their companies and beyond. I'm your host, Cecilia Ziniti. Today's guest is Kaniah Konkoly-Thege. She's a brilliant legal mind and technologist who's built her career built her career running straight into complexity. She started off at the Department of the Interior right after the COBA case, which we'll get into, go straight into that largest federal settlement implementation in history. Since then, she's gone into frontier tech, working in a lot of government and government adjacent areas, bringing legal insight to everything from AI to quantum computing where she is now. She's been called the liberal arts translator, dear to my heart, also a liberal arts major, and she sits at the intersection of disciplines and actually makes sense of them. I also count Kanaya as a personal friend. We actually met through a shared executive coach. In this episode, we're going to talk about her early career, her passion for hard problems, and how she's thinking about the future of legal leadership in the age of deep deep tech. Let's dive in.

Cecilia Ziniti:

Kaniah, welcome to the show. Thanks to Cecilia. It's so good to be here. I'm so honored to be able to sit here and talk with you. This is going to be so much fun.

Kaniah Whitehorn Konkoly-Thege:

I literally can't wait. Daymaker. Let's go. All right. So you graduated from law school and started at the Department of the Interior, just as the COBAL case was getting going.

Cecilia Ziniti:

What what is that case? Tell us about it. So it is a wild case. Actually, so it started in 1996, but when I started in 2003, so let me back up. In December of 2002, the judge ordered the entire Department of the Interior to disconnect from the internet. So, and this is back in the day, right, where internet and access and emails and things like that were about where probably society is today with generative AI, right? Some people understood it. A lot of organizations were trying it out, but it really hadn't been this well-known thing where everybody kind of understood cybersecurity and other things, right? So the crux of the case is that individual Indian money account holders, okay, that's kind of the term use. So let me back up. In the US government, as native people and tribes were moved to different reservations, uh, the US government held assets in trust for them. So whether it be in mining, oil and gas and timber, all of this stuff, the government would then sell leases or sell the pro the product coming out of these assets and then, in theory, reimburse the individual Indian money account holders and tribal account holders for the money made off of these assets. So this case essentially requested an accounting of all of those assets. And what makes that a little unique is that usually when you bring a lawsuit against the US government for monetary damages, you are put into the Court of Federal Claims. And there had been a number of cases trying to force the U.S. government to pay rightful amounts of money in the Court of Federal Claims. This particular case, because it requested an accounting, put it in the desk district court. And they happened to go before a judge named Royce Lamberth, who really, I think, over time felt like it was his mission to help Native people receive what they what he felt, and I think what a lot of folks felt they deserved, which was an accounting of these accounts. But what that meant was the US government had to do an accounting from 1887 to the present day. So you're talking millions upon millions of accounts. So over time, they kind of narrowed the field to doing a statistical accounting, but that still required the department to find millions and millions and millions of records. So these records were paper, they were sitting in boxes in field offices in the middle of nowhere, Montana, all the way to, you know, legacy uh uh legacy IT systems, right, that had been developed over the years. And so the judge had a lot of concerns that these records were not being maintained properly. He hired a team of experts to come in and do a penetration test within the department, which I think everybody knows today is pretty common. But back then, people really didn't get what pen testing was. So it was fairly easy for these pen testers to find this data. And so after that, you know, report came out, the judge ordered the entire department to disconnect. So in IWAC, this was just a few months after. And I should mention, people didn't really know what that order meant. And so the rumor was, and and folks have told me this when I started, people were ordered to come in on a Friday afternoon and literally unplug their computer from the internet because they didn't know, like they didn't have like systems architecture, right? Like you'd find today. Some offices may have had some sense of what their architecture and their net their network architecture looked like, but for the most part, it wasn't well known. And certainly where this data resided was not known at all. So fast forward a couple months, I walk in, and effectively the attorneys on the case, and mind you, these are senior federal or federal attorneys, were like, we are touching this case with a 10-foot pole. The judge had been held, I mean, the the secretary of interior had been held in contempt twice. Wow. And so I'm this baby attorney who walks in, like on my second day in the job, they're like, Great, nice to have you, go meet with the secretary. And I was like, the secretary of interior? Okay, that sounds great. Having no idea, right, that that is really uncommon. So essentially what they asked me to do is figure out this crazy cybersecurity stuff and help the Department of Justice present to the special master in the case a reconnection plan for each office and bureau. So I had to essentially figure out this, you know, cybersecurity and what would be considered, you know, an appropriate reconnection plan that included segregation of data and, you know, mapping out network architecture and stuff like that. Which I had no clue until I just started from the city.

Kaniah Whitehorn Konkoly-Thege:

But you think like, you know, you you take a job as an attorney at the Department of the Interior. I I don't think you're expecting, and certainly not at that time, you're not expecting to be a cyber attorney. Like what an amazing analogy. And I think your analogy to AI is apt because it's kind of like uh and this is a I guess a career theme. It's like, what are you up for? Are you an attorney that's up for anything? And can you figure it out? And so yeah, tell me, in this case, uh, you grew up on reservations. Um so working at an interior must have had extra personal meaning. Did that did that come into your work on the case? And and and what did you end up doing?

Cecilia Ziniti:

Um it was, you know, so so I did. I was born on the Pima Reservation in Arizona and lived between Seminole in Florida, Choctaw in Mississippi, Navajo in New Mexico, and Tehona Otam in southern Arizona. When I was 11, I moved to Tucson for a couple of years and then moved to DC at 15. And so when I moved to DC, I had a very hard time because I was not around. It was kind of the first time I'd been on the East Coast. There's not a lot of Native people there. There was a lot of questions like, we don't really look native, we don't understand, right? And so I spent a number of years really not sharing my heritage with a lot of my high school and college friends. And so walking into interior and reconnecting with Native people, reconnecting with people who look like me, but and had the life experience that I had was really meaningful. Now, I will say working on this case was also a challenge because as I was, you know, working on it and learning more and more about kind of the institutional racism that had been put in place over the last few centuries that led to where the department was today, right? It was very educational, but it was also a bit of a challenge to really think about am I contributing and helping or am I just perpetuating stuff? So, but it was, I think overall it was really helpful for me just to reconnect with where I came from and feeling proud about being able to say, yeah, I'm an, you know, I'm an enrolled member of the Osage Nation.

Kaniah Whitehorn Konkoly-Thege:

And how did the early work maybe, maybe tell us a war story from the case, other than then kind of walking in? So if you have any any any good stories from the case to share.

Cecilia Ziniti:

Um, at one point there was a legal opinion issued that I kid you not said Kanaya Kinkoli Tege is a lawyer. And that the crux of it was whether an administrative lawyer in the administration, right, not Department of Justice, could have attorney client privilege over communications. So there was some discussion between myself and the CIO of one of the offices, I don't remember which one. And the plaintiffs wanted to get the the kind of the transcript and the information that came out of our conversations. And so the issue of whether agency counsel could actually assert attorney client privilege was the question. And the judge ruled that they could. But the best part was I had this opinion that I kid you not, I printed it out, I highlighted my name, and I'm a lawyer. And so for the next few years, I had that. I wish I could find it today because I'm gonna still probably keep it.

Kaniah Whitehorn Konkoly-Thege:

So that was my man. We're gonna find it and we're gonna put it in the show notes. But yeah, these moments of like identity, right? Of like, this is literally it turn the case. I can imagine. So, how you know, something like that. Obviously, the the the identity of being a lawyer is gonna carry through. Anything else from that early work shape how you think about, you know, really big cases or legal challenges in general, today as a general counsel.

Cecilia Ziniti:

Say two things. One, not being afraid to learn the really hard stuff and not being afraid to ask what you might think of as stupid questions. So, you know, when I was taking this crash court, I basically had a couple of folks from NIST and, you know, probably NSA and other folks, right, sitting down and trying to explain to me basic principles of cybersecurity. And I was like, what's a WAN, right? White area network. What's a LAN? What's a local area net? What does this mean? Like, how do the wires flow? I mean, I asked crazy questions because I was just, I had no idea what I was doing. And I felt like I couldn't understand how to actually translate the legal part of what I needed to do, right? To show data segregation, to show that this information was protected without trying to like understand the framework of what it is, right? Because if the judge would just say to me, well, what about, right? I wanted to make sure I had an answer. What if someone wanted to infiltrate the data by doing X, Y, Z? I wanted to understand, is that possible? And so I just asked a ton of questions. And what I found was everybody was really, really happy to answer them. And they, and things I thought were stupid questions really weren't. And that actually plays into what I do today. I'd say the second thing I I learned from that is, you know, just taking raising your hand and taking on the hard problems. Because I think you learn more. I think it's easy, right? I never was in big law. I know a lot of folks that, you know, went through big law and had, you know, some great experiences. I also know folks who, you know, spend a lot of their years in big law doing kind of the rote mechanics of law, right? Learning, you get precision, but you don't necessarily learn to balance risk. You don't learn how to find these corner cases and actually figure out what's going to happen in a corner case. So when you take on those really hard problems, you quickly figure out how they're going to, you know, you see how they unra unravel. And sometimes it's good and sometimes it's bad. But I think when you take those hard problems on, then over time you start to figure out what's the likelihood that, you know, these these hoof prints are going to be a zebra versus a horse? What's the likelihood, right? That, you know, this one clause in a contract is going to lead to some huge litigation. So um, so yeah, those are the two things I took away. I love it.

Kaniah Whitehorn Konkoly-Thege:

Yeah. So for context today, uh Kanaya is the uh chief legal officer of a company called Quantinuum, which is doing quantum computing. So maybe for our listeners, I'm semi-familiar, but what is quantum computing?

Cecilia Ziniti:

It's a great question. That is that is the multi-billion dollar question in quantum, which is how to explain quantum computing. So I think, you know, a lot of people are when I first started doing this about eight years ago, I would use the analogy that people understood quantum under kind of in a in a three-prong rubric. The first was you might have heard about it because you watched Marvel movies and it's Ant-Man, right? The second is you might have been told by a man in black about this, you know, scary thing called Schwarz algorithm, which is gonna break public key encryption and that's gonna be the next huge issue to face us, you know, as a society. And then maybe you've learned enough about quantum where if you Google it and you see a really pretty gold chandelier looking thing, you might be able to understand that that's a dilution refrigerator. And I use that context because I think it helps level set that everybody wants to talk about Schrdinger's cat and you know, quantum mechanics. Quantum mechanics is extraordinarily hard. But what you do need to understand is the principle behind it, which is essentially when these systems scale out to, you know, large-scale, what we call large-scale fault tolerance systems, being able to solve real world problems, they can solve problems that you can't solve today. A good example that I've heard of many, many examples that folks try to give on how you can solve it and make it relatable. And there's two that I kind of like to use. One is if you think of planning a wedding and you have 100 guests and 10 tables, if you are planning it, it might take you a few weeks to figure out the right seating chart because your brain, the way your brain is thinking about it, you are solving and kind of eliminating possibilities, multiple possibilities at the same time, right? You know that Uncle Joe just can't sit next to Aunt Mary and that the two cousins need to be at this table and this table, you know, whatever. Typical classical computer is not gonna be able to solve it. It'll take 10,000 years to solve it because, right, it's working in these ones and zeros, and every probable chance, every iteration of where those people could sit, it has to first figure out and then eliminate it, right? And so a quantum computer is gonna function a little bit more like the way your mind thinks. It's gonna eliminate a lot of these probabilities at once to get to that, you know, the most ideal optimal seating arrangement. The other example I've heard people give is if you think about a hotel, a hundred rooms, there's treasure in one room, you have to go find that treasure. You knock on every door and open every door, it's gonna take you a really long time. If you could find a way to open all doors at once, then you can identify where that treasure is. It's a challenge, right? Because to really get into it and to start explaining that, you know, you have this single qubit that, you know, is sitting between a ground state and, you know, it's it's I can't remember even what the state of energy is called, right? But you know, it's kind of sitting in this special um, you know, state and and it's holding all of this information at once. And then you do a measurement of it and you figure out what that, you know, information is, it starts to get a little bit cloudy. So I think you find a lot of people like to use analogies, but the critical piece is what does it mean for us, right? And so that's where we like to give examples like say in chemistry, we worked with Microsoft recently and we're able to identify a catalyst and really be able to map out exactly what was going to happen in the chemical reaction as nature provides it. And you would think that we could do that using classical computers, but we can't. We get close, but we can't. You find this in imaging with quantum sensing and being able to like get the exact image, it's just it's like a lot more precision. So that's where we like to focus in terms of what is quantum, because otherwise you'll kind of go down a rabbit hole of how do you get this crazy energy state where something's a zero and a one at the same time, right? So that's where we have to focus.

Kaniah Whitehorn Konkoly-Thege:

I love that. It's so funny because the so thinking about the wedding guest complexity, you know, you throw in my mother who randomly is inviting, you know, her hairdresser or whatever, and it's like just the ever-changing complexity of the perfect example. So, funny enough, here on the uh, you know, we we did some show notes before, and it said something like, you know, Kanaya is a good translator. So I feel like I understand quantum. So we we we hit that point, delving one one layer deeper. How did you build that technical fluency over your career to go from sort of early-nist and you know, kind of cyber through to quantum? And I think you you you did a stop at Honeywell doing you know, complex technology there. What are some tips and tricks that our that our listeners might try to to get to that point to where you are? And what do you do to build that?

Cecilia Ziniti:

So um, so first, thank you. I'm glad that made sense. Because as I'm talking, I'm like, I feel like I'm rambling on trying to explain quantum. I'm always balancing like how much technical do you get versus how do you kind of rely on some of these other areas? Or like, you know, how do you how do you think about moving towards what it does versus how it operates? But um for me, honestly, what I did is again, I kind of relied on the ask a bunch of questions. I found a bunch of scientists. I'm really lucky. I work in a field with we have um 350 plus PhD physicists and scientists. So folks who worked with some of the Nobel Prize winners for ion trapping systems from the team that came out of NIST that won the Nobel Prize on this. So our teams, you know, I have some of the best and brightest in the world. And what I found is they are very happy to kind of spend time with me if I explain Supreme Court cases to them. So we would sit down like over lunch or or over a beer, and you know, they would kind of start with some basic mechanics of physics, right? Thinking about like the transfer of energy and you know, thinking about like how uh, you know, different principles are functioning. And then I would in turn, you know, they'd say, like, help me understand this legal principle, right? And so I'd try and find a way of, I don't know, explaining first I'd be like, what cases that I gotta prepare? Like, I'm not necessarily reading every Supreme Court case that's coming out, but you know, certainly some of the big ones that have come out over the years, they're like, help me understand this principle, right?

Kaniah Whitehorn Konkoly-Thege:

So um Yeah. So so like I guess like day to day, so looking back on yourself, you know, before walking into the COBOL case or when you first went in-house at those moments, you're giving yourself a piece of advice. What do you say?

Cecilia Ziniti:

Oh gosh. Um, speak up and don't be afraid to ask for things. I think, you know, one of the biggest lessons I learned, and I I do try, I hope this isn't a problem anymore, right? I mean, we, you know, there's so many women these days in the legal field. I remember when I was when I started law school, they said ours, ours was the first class that had an equal number of men and women, and then it kind of dropped down again, and I don't think it came back till 2017. But when I was early in my career, I remember I walked into one of my colleagues' offices and he had two computer screens. And again, at the time, that wasn't really common. And I was like, How did you get two computer screens? I want two computer screens. And he's like, Did you ever ask for it? Exactly. Exactly. I did it. I did not ask. And so that's the that's the advice I would give myself. And that's the advice even today. I'm like, have you asked for what you want, right? If you want to raise, ask for it. If you want, right? You you you've got to be a little bit aggressive for yourself. And I find, at least for me, I tended to be aggressive for everyone else and then shy about asking for myself.

Kaniah Whitehorn Konkoly-Thege:

Yeah, no, it's great advice. So the judge that I work for, um, there's an expression in Spanish, El no ya lo tienes, right? You already have your no if you don't ask. So in this case, the two monitors. I'm also not surprised, you know, techie having two monitors. I personally like the ergonomics of just the one, but when you're reviewing, you know, very high volume of legal work, that's that's it a must. So how um, you know, I'm gonna I'm gonna go off script a little bit, but tell us about Kanaya, the general counsel, and kind of when you became a general counsel, and then sort of like what how are you in that role?

Cecilia Ziniti:

Yeah, thank you. Um, I like to think of myself as a business partner first. Um, you know, when I first walked into the role, I was very lucky to have a mentor who in Honeywell, he hired me in. He felt very strongly about promoting women and minorities, BIPOC, you know, making sure and not just hiring them in, but also really helping to mentor and grow people. And the first one of the things he always said to me is like, don't be the office of no. Don't assume, you know, don't take the most conservative position. Figure out how to make the business, you know, do what the business wants to do with it as much as you can. You know, we used to say write a fast, right but fast, right? Or fast but right, those kind of principles. But very early on when I started acting as a, you know, being a GC, I really tried to be that business partner first. It also irritated me that I was a cost center. By the way, of course, right, that is how legal functions. I just didn't appreciate it at the time. I was like, I have value, I'm not just a cost. And so, you know, I would say to myself, how can I show my value? And I found a lot of it was really sitting there with your leadership, right? At from the very beginning, figuring out what is it you want to do. You want to go sell something? Let me help you. I'll stand right there with the BD team, right? Ready to sell the products and then write the contract in the manner that's the best for us. But right, I mean, you're kind of structuring the deal from the beginning and you're building relationships with, you know, outside count, well, not just outside council, but outside parties. Um, and you're really trying to find the best solution for everybody.

Kaniah Whitehorn Konkoly-Thege:

Great. No, I love that. So you mentioned adding value. You in particular have found a lot of areas that are very kind of public policy, you know, government adjacent, right? So you started off in interior, now you're working in quantum, which of course is highly regulated, spent a lot of trips to DC. If you follow Kanaya on LinkedIn, she's a great follow on LinkedIn for many reasons, but you're gonna see a lot of a lot of um, you know, capital steps pictures. So, in particular on the policy side, how have you added that value? And was it something you specifically sought out?

Cecilia Ziniti:

Yes. So, right after I started working in the quantum field, first uh when I first started with Honeywell, we didn't, we Honeywell had not told everybody what we were doing. It was still kind of this secret, small kind of skunkworks project that was tucked away, reported right to the CEO, which was helpful, right, in terms of kind of scaling out the business. But we hadn't told the street, we hadn't told anybody. So in about late 2018, early 2019, it came to our attention that we were too big not to tell everybody, right? It was we were finding success. Um, once we, as we were making the announcement that Honeywell was investing in quantum and building a quantum computer, um, I learned that the US government was looking to uh impose very strict export controls on quantum. And I think at the time they were suggesting somewhere, I think roughly 200 qubits. There was no, and by the way, qubits aren't all made the same. They have, they're noisy, they have uh, they have errors in them. And so having a noisy qubit isn't very helpful. And so what we were, you know, what we were trying to get folks to understand is you need to have a, you know, a qubit that has high fidelity, basically where 99.9 plus percent of the time you're gonna get the answer you expect to get, right? You're not gonna have this interference. And at the time, the government really wasn't listening. And so what I found was there was such a small group of people who understood the technology, and they were all scientists, and that meant they didn't really understand public policy. And so I started meeting with the regulators and frankly going up to Capitol Hill and talking to, you know, Congress members to try and just get them to understand. You know, if you're a public policy person, you've got to have a little bit of context for the technology. And if you're a scientist, you've got to have some understanding of public policy and economics and what the marketplace uh what's what's happening in the marketplace. And I'll give you an example. The technology relies on a lot of suppliers that are overseas. And most, many of these suppliers, for some of the key parts, whether you're talking about dilution refrigerators or lasers, and we don't use dilution refrigerators that's used by superconducting systems like IBM. We use lasers, but these these makers, these suppliers, they're mom and pop shops. There's only, I believe, two companies in the world that make dilution refrigerators. And that's starting to change a little bit. Folks are, you know, kind of investing now.

Kaniah Whitehorn Konkoly-Thege:

Dilution refrigerators. So this is literally like you're gonna have an explosion if you don't refrigerate the stuff. Is that fair?

Cecilia Ziniti:

Uh kind of, yeah. No, it's the it's a pretty uh gold chandelier looking thing. Essentially, what it does is it pumps uh helium-3 down into the chip to remove the heat so that you can actually generate the qubit and per perform operations on the qubit. So without getting too technical, that's a superconducting system. They have a chip, and I I think it's called a Jos Josephine pump, essentially where you have like a grid like this. Um, that's exactly what it is.

Kaniah Whitehorn Konkoly-Thege:

I found one.

Cecilia Ziniti:

So it's a golden chandelier grid. All right, good stuff. Okay. And it essentially you run that helium-3 through all of those coils down to the bottom to where that chip is to help cool, right, cool it so that you can actually create that qubit and read the information off of it. So that's that's a dilution refrigerator. Lasers, I think more people kind of know what a laser looks like for the most part. But again, you're talking about these were made for academics. These, you know, these mom and pop shops would maybe make a handful of these things a year used by researchers and professors. And so, in say the laser space, you know, we were talking to these suppliers and they're used to lasers that maybe need to have, say, a 2,000-hour life. And we're like, no, no, no, we need 10,000 hours. So suddenly you're not just asking for them to create, you know, bigger or you know, more powerful systems. You're actually fundamentally changing their product in addition to yours. And so when that product is sitting in, say, Finland or Austria or Germany, having export control regimes in place, right, where you have to get a license for RD, that's a really, really challenging thing, especially for smaller companies. So that's where I spend a lot of time trying to get regulators to understand, you know, gotta make this process easy, or else countries that have, you know, domestic capabilities to do this are going to they're they overtake the US market because the US companies are not going to be able to get what they need, right? So um, so yeah, so I did spend a lot of.

Kaniah Whitehorn Konkoly-Thege:

So it's good. So basically, so the public policy aspect is like you've got kind of a limited supply chain or a traditional supply chain. You've got this super high promising technology that is difficult to understand. And then you've got, you know, a many billion dollar public company, Honeywell, doing this work. And the question is like sort of similar to Circa 2003 Kanaya, where it's like, all right, we've got this problem, kind of figure it out, go to the hill. So walk us through a meeting that you might have on Capitol Hill for this, maybe like from like the prep to the meeting itself.

Cecilia Ziniti:

Yeah. So um, I will say it it helps that I've been doing this for a number of years, and I know how so today I know how sophisticated each member is or is not in quantum. So I'll say so.

Kaniah Whitehorn Konkoly-Thege:

You map out in Congress, you're like, all right, Senator Markey may not be as familiar, Senator whatever. That's right. Is okay, got it. That's right.

Cecilia Ziniti:

Um, and there are there, you know, there's there's a tech committee. There's not ex quantum is growing, but at the time when I was initially talking to folks, it was in 2018, it was when the National Quantum Initiative Act was initially coming into play. And, you know, it was really just a hi, this is quantum, you know, it is outside of labs, it is a real thing. This is, you know, companies are investing, big companies like, you know, Honeywell and IBM and Google and AWS, right? They're all investing. Today, the conversation is much more nuanced, where it's, you know, you really need to be investing in these particular use cases because that's going to be, you know, and and making sure the funding is very strategic so that it can help um, you know, grow and and develop the ecosystem, but also help promote certain use cases that need to be studied earlier on, right? So I think these legislat, you know, the legislatures have a much better understanding of some of the nuances, right? So the early cases in quantum, we think are gonna be sitting more in chemistry, right? Um, as opposed to say optimization, like the problem I gave you with the wedding scenario. That's really more of an optimization problem, which isn't gonna be the initial problems that are solved. It's gonna be much more around the chemistry, big pharma, I think. We've had a lot of focus from uh JP Morgan and other financial um investors who are very interested in running like Monte Carlo simulations, right? So showing the Hill that, hey, this is this is a big deal and big companies believe in it enough to invest is important. But I think I'd say today what we do is we wanna, you know, we we have specific asks. So we map out, of course, you know, to the extent there's any funding, uh, we map out the appropriators, both on the House and the Senate. We look at who has made public statements on quantum, who's been supportive of the bills in the past. And it's very interesting. It's very bipartisan. You'll find like Senator Blackburn, huge supporter. Representative Khan from from California, huge supporter. And, you know, there's there's a lot of it's hopefully going to stay bipartisan. It's just that the whoever you're talking to kind of has a different interest. So on the Democrat side, it tends to be a little bit more about economic security and kind of growing jobs and things like that, like you would expect. Also around environmental right impacts on the or you know, reducing impacts on the environment. Republican side tends to be a little bit more focused on national security, making sure we're keeping up and not allowing, you know, adversary nations to advance beyond in some of the technology. But both of them wind up to be the same, which is how do we help promote the technology? So we spend a lot of time around talking points, but making sure they understand why it's Important for their constituents.

Kaniah Whitehorn Konkoly-Thege:

So it sounds like some of the time, you know, it it's obviously a long, a long game, but you hit your message hits. So I read that the UK made a $500 million quantum commitment. There's new legislation in here in the US proposing a quantum sandbox act. So what next? So you get you get them to make this commitment and then how does that affect your job, right? So like you're you're GC now this quantum company, you brought in this amazing boon being the government action. What what do you do? Does it come with handcuffs? What is it, what what happens next? You probably can't talk about it as much, but just really thinking about this end-to-end journey of kind of public policy.

Cecilia Ziniti:

So I think I would say a lot of it is focused on learn quantum in all these aspects, right? And the reason I say that is because right now the US government has invested in a program called um quantum benchmarking initiative out of DARPA. And essentially they're kind of evaluating right now the scalability of a number of different systems. We're participating in it, but so are a number of companies. But I think that's a good thing. I think it's good for the government to really test the efficacy, right, and the scalability of various systems. I think the challenge that is facing the quantum world right now is that you have a lot of companies and the government, you know, doesn't want to pick winners and losers. And that's fine, right? We believe in our technology, we believe we're the best, and we believe that we're going to succeed. And so from our perspective, what we really want to see is we don't want to see the US government contract or ignore quantum. And we also don't want to see a situation like back in the 80s where remember genetic testing was kind of first getting started, and there were all these scary stories about like monsters running around Harvard Square MIT was like making these crazy things in their labs, and that's just silly. And we don't want to see that kind of regulation. I mean, you know more than better than anyone kind of the regulatory quagmar AI is in globally right now. And so for us, I think we feel very strongly about making sure that there's smart regulation that people understand, right? I've heard people say, oh, we should just regulate quantum the way we do AI. And I'm like, no, please.

Kaniah Whitehorn Konkoly-Thege:

No. So why why why does that cause the the face palm? Can I why why why why is that a face palm? Tell me more.

Cecilia Ziniti:

It's a face palm in part because I think it's like, what problem are you trying to solve? Even with AI, and I take that problem there too, right? What problems are you trying to solve? And does the framework you're proposing actually solve them? So, right, I mean, and if a lot of it is around data privacy, let's look at the f the data privacy frameworks that exist today, maybe create stronger data privacy and then like port that over into the technology you're talking about, right? Because otherwise you come up with these really, you know, heavy-handed, blanketed regulatory regimes that create a lot of stress on small startups.

Kaniah Whitehorn Konkoly-Thege:

Yeah. I mean, I I definitely, you know, I try to try to be, you know, moderately neutral, I think, on this stuff. But on AI in particular, you know, the the idea that the technology could be used for bad, yeah, of course it can, but so can, you know, fire and electricity and cars and everything else. And so, you know, this is one where I I do tend to agree, you know, with Sam Altman or or with others that have testified on the Hill that it's like, okay, this technology has this potential. Like, let's look at the application layer things. You know, there's things like the um, you know, revenge porn and sort of like things associated with with bad use or you know, financial you know, basic fraud using AI to create a voice um double of somebody. Okay, that's fraud. You know, prosecute that. Um, it'll be interesting to see. I had any any predictions what's gonna happen with AI regulation? I don't know.

Cecilia Ziniti:

I want to use um no, I you know, I hope, I hope that cooler heads prevail and that we have, again, smart regulation. I don't disagree. It can be a very it's a powerful tool, but my gosh, like you say, right? There's already frameworks in place to address criminal behavior. And so it's just one tool. I mean, we feel that way in quantum. Will quantum break public key encryption someday? I'm sure it will. You know, you can use it, not today, but eventually you can use it to, you know, break to for cryptography, right? You can break encryption with it. But guess what? You can still hack a system, you can still call somebody up, put in ransomware. There's so many other things that you can do to exfiltrate information and to, you know, kind of act poorly, be a bad actor. So, you know, it's so I g I hope, I hope that as the regulations progress, and I'm sure that they will, that at least they will take into consideration the impact on small companies and small startups and not create regimes that are just, you know, really kill the small company in favor of the large companies. That's what I really, really don't want to see.

Kaniah Whitehorn Konkoly-Thege:

Yeah, it's it's been interesting to see the sort of like there was a really um Bill Gurley gave a big talk, we'll drop in the show notes around kind of like regulatory capture. And, you know, it was, it was, it was interesting for me to see, you know, big name VC really get into the the issues that I've been thinking about around public policy and how you regulate and you know, looking out for customers and and kind of what is the optimal thing. It's it's been fascinating, of course, with the new administration and so on. Again, I'm not gonna not gonna get political. I I definitely um it's something that, you know, as lawyers, and I think I had the same uh you know thoughts you did when you got on COBOL of like, okay, which side am I on? But then I think about like when I was at Amazon and I advised the company on accessibility, I did so much more for accessibility of those devices than I ever could have as an advocate or as a government regulator, because there were a bunch of times where if it was easy to do the right thing and if it was something where we could have good wins on accessibility, you know, I would do it. So, or you know, encourage the company to do it. And it was great. And I think ultimately, like, you know, the thinking about the opportunity of tech, you know, I even see it here at GC AI, right? People like you or GCs like you are using it, you know, every day to to be more strategic, to prep for those meetings, to get things done. So yeah, it's been it's been really fun. All right, let's go to the lightning round. So basically, it's been super fun. I've been educated on on quantum, you know, and hearkened back to to my wedding some years ago with uh with my mom inviting hairdressers and throwing them at a table seven with with uh you know with with Uncle Marty kind of thing. But anyways, here we are. So what's a book or concept that has shaped your thinking, something that has influenced you?

Cecilia Ziniti:

So probably not rel uh relatable for most people, but the number one book that kind of shaped me was Killers of the Flower Moon. And when I read it, I was like in my 30s and I was I remember I was sitting in my apartment reading, and suddenly I see this passage that talks about Charlie Whitehorn who's shot basically murdered. And I sat back and I I was like, my dad's name is Kenneth Charles Whitehorn. So I pick up the phone, I'm like, Dad, I'm reading this book about and so premise of the book, right? Well, watch the movie if you haven't, it's a great movie. And essentially what happened is a lot of white settlers moved into the Osage Nation. The Osage had been in Missouri, they moved to Oklahoma in part because they felt like no one would want that land. It was pretty crappy land. Just so happened they preserved their mineral rights and there was a ton of oil where they were settled. Um they suddenly, in about the late 1800s, early 1900s, became the wealthiest people in the world. They would be akin to kind of what the the Middle East, the Saudis and the Emiratis and the Qataris are today. So reading this book, I come to find out this is impactful to my own family. And it started this journey of kind of digging back into who am I? Where do I come from? What happened with my family? And kind of because I'm a very I love to look in the future. I love tech, I love like what's happening next. And it was the first time where I took a step back and said, where do I come from and what does it mean? And how is it impactful to me and you know, my family, my people, my tribe, et cetera?

Kaniah Whitehorn Konkoly-Thege:

I did not expect that answer. That's lovely. So good. Any bold prediction about the legal field, stepping us into the future. We're talking in five years, maybe we're not on a podcast, we're exchanging chips in our brain or something. But what what what what do you see five years from now? How's legal practice?

Cecilia Ziniti:

So I swear to you, I am not saying this because of you and GC AI, but I I believe every lawyer is gonna be using hopefully GC AI, but some AI tool. Think, you know, I genuinely cannot tell you how much it has revolutionized my law department, my team, my I've contracted hiring. I have streamlined how we use our outside counsel. And I think that more and more law departments are gonna start using these tools. I I think today you still have a lot of fear and uncertainty, and people just don't appreciate some of the, you know, that this this concern about how is it trained and what is, you know, where's the confidential information come from. But 100%, whether it's GC AI or some other tool, hopefully GC AI, of course, but is going to be all over the law department.

Kaniah Whitehorn Konkoly-Thege:

I love it. I love to hear that. All right. So you've given us so much to reflect on from kind of quantum to working in government to, you know, kind of the personal side, incredible courage to run into complex things and and have this amazing career. Anything else that you want to leave leave listeners with? Gosh.

Cecilia Ziniti:

Um, all I can say is I just really appreciate being here. I think it's I, you know, when I first met you, I was so impressed. I love lawyers, or well, I because of course you're a lawyer, but you're also a CEO. And I love to see meet visionaries who can actually take their vision and execute on it, right? I don't, I shouldn't say there's not a ton of visionaries in the legal.

Kaniah Whitehorn Konkoly-Thege:

I shouldn't say that, but you know You're just like making it happen. I mean, you've done that. I mean, literally, you've taken this technology quantum, which is like it literally is like physics. And by the way, can I majored in physics, which is like kind of amazing?

Cecilia Ziniti:

I avoided, I actually double majored in international relations and spanish to avoid physics. That's the irony of my life. I chose William and Mary. I did this double major because I figured out if I did that, I wouldn't have to take like calculus and physics.

Kaniah Whitehorn Konkoly-Thege:

Wow. Look at that. Well, it works out. So congratulations, Kaniah. It's so exciting. Thank you for joining us. This has been so much fun. That was my conversation with Kaniah Konkoly-Thege, a legal and technical translator with a gift for making sense of the very hardest problems. If you're working at the intersection of law and emerging tech, or just trying to think more expansively about your career and leadership, I hope this episode gave you something useful. Follow CZ and Friends wherever you get your podcasts, and subscribe to our newsletter at gc.ai slash newsletter. Or just find us online. You can find me on LinkedIn. We'll give you behind the scenes insights, guest announcements, and practical tools for legal and business leaders. Thanks for listening.