Inside the Minds of Government Chief Data and Artificial Intelligence Officers:

Adita Karkera recently sat down with Dr. Matthew McCarville to discuss his experiences in his role as the Chief Information Officer (CIO) for the State of Nebraska. Dr. McCarville’s career began in finance, where he earned his MBA and worked at a hedge fund until it dissolved during the 2008 financial crisis. He pursued further education to deepen his existing data analysis skills, earning an MS in Business Intelligence, an MS in Software Development, and a PhD in applied AI and business intelligence. After that, Dr. McCarville joined the Union Pacific Railroad, where he modernized IT infrastructure and advanced data analytics on fuel. As AI became more prevalent in the transportation industry, he began using predictive analytics to estimate locomotive spending. He then moved to PwC, becoming their first Chief Data Scientist for Human Capital, Metrics & Analytics at their international office. After his time at PwC, Dr. McCarville relocated to the University of Florida, where his wife was also based. There, he was appointed as the university’s first Chief Data Officer (CDO) and concurrently served as a professor in data analytics and artificial intelligence. In December 2019, he filled the newly created Chief Data Officer position for the State of Florida, again collaborating with his wife, who became the Deputy Director of HR. Dr. McCarville experienced a “massive pivot” when COVID-19 hit in March 2020. With Florida’s CIO and CISO roles vacated, he was appointed interim for both positions. During this period, he employed robotic process automation (RPA), conducted data analytics, and used automation to streamline the unemployment process for constituents and support those delivering the services. During this period, he developed dashboards to measure key metrics in health, education, and unemployment, describing the experience as “a deep immersion in a lot of broad areas” that he would not have otherwise encountered. He also developed an enterprise data catalog, which enabled metadata management and consolidated siloed agency data into a repository for analytics, AI, and dashboarding KPIs for reports flowing into the governor’s office. After his tenure in Florida, Dr. McCarville went on to become the CIO for the University of Colorado. He then became the CIO for the state of Nebraska, where he began building AI and BI platforms and cybersecurity capabilities, all from scratch, while maintaining the state’s existing infrastructure.

Strategies for Collaboration between the CDO and CIO
When asked about improving collaboration between the CDO and CIO, Dr. McCarville stressed the importance of measurement, citing Nebraska's governor: “You can’t analyze and improve things that you’re not measuring and in order to measure things, you need data.” He explained that data is vital for decision-making, and he cannot make decisions unless he fully understands the impacts of initiatives as shown through government data—specifically, the people affected, and the outcomes achieved. Dr. McCarville noted that Nebraska has never paid for technologies like AI and cybersecurity, so the state must use data as an asset to scale up in the most impactful way. As Nebraska migrates to the cloud, the state’s IT leaders have recognized the critical need for comprehensive data cleansing to reduce operational costs. This initiative underscores the importance of data in the decision-making process.

How the CIO Role Fits into Nebraska’s Hierarchy
Dr. Matthew McCarville explained that his office operates under the shared Department of Administrative or Management Services and that he serves as a cabinet member for the governor. The Cabinet meets monthly, with each member treated as an independent leader of their agency. All agencies must use the CIO’s office for IT needs unless there is a specific exception.

Challenges Around Data Sharing and Department Collaboration
When asked about some of the challenges surrounding data sharing, Dr. McCarville highlighted the importance of cross-agency collaboration. He pointed out that in Nebraska, services like unemployment, Medicare, and SNAP are managed by separate agencies, requiring citizens to apply to each individually. This fragmentation displayed how data sharing would simplify constituent interactions and improve agency efficiency. He pointed out that departmental silos and shadow IT systems are ongoing challenges, with agencies often duplicating efforts. Dr. McCarville also noted that Nebraska’s budget deficit has inadvertently promoted centralization and efficiency: “It kind of forced the view of centralization and efficiency because they can’t all afford to go rogue and do things on their own anymore…they’re being forced to cut things and be more efficient and centralized, it’s not a mandate on centralization”. Because of this situation, Nebraska began to modernize its systems, which led to improved reporting and greater data quality. Silos previously hindered updates and allowed vendors to sell the same products to multiple agencies, but the push for efficiency drove a modernization mindset without strict mandates.

Cybersecurity in the State of Nebraska
On the topic of cybersecurity, Dr. McCarville shared that Nebraska previously relied on a single policy analyst to manage infrastructure security with firewalls. In the past 18 months, the state ramped up its efforts, becoming one of the first to adopt a whole-of-state model: “We have 93 counties and 90% of our state is rural small towns. The city councils are farmers, shop owners, and lawyers in the town…How we move forward here in Nebraska from a cybersecurity perspective is [by asking ourselves] 'How do we take care of those that do not have funding to do it on their own?’” To address this situation, Nebraska offset cybersecurity costs by pooling resources, platforms, and data management across agencies. The state modernized its approach by developing a joint Security Operations Center (SOC) and dedicating a 5,000 sq ft space in the CIO building, using monitors to display metrics, analytics, and KPIs. Nebraska also created Network Nebraska, a shared broadband backbone connecting schools, universities, and libraries, supported by RFPs and vendors for cybersecurity implementation. Additionally, the state is rolling out a “train the trainer” program, bringing in vendors to educate and certify counties and constituents on best cybersecurity practices, fostering collaboration in the whole-of-state model.

Promoting Data Talent in Nebraska
Dr. Matthew McCarville discussed how Nebraska is cultivating young talent in data analytics. He shared the following on how his experience as a professor encouraged him to hire former students as interns: “Some of those interns have worked for me four or five different places and that really got me to understand the impact and hunger of early career talent”. He witnessed firsthand the benefits of providing interns with the right tools and opportunities, which in turn foster growth across both private and public sectors. Nebraska leverages a split intern model, where interns spend two days a week supporting K-12 schools and two days assisting universities. This approach includes engaging high school students and teaching them tools like Tableau and Power BI. Dr. McCarville emphasized the need for data expertise from interns in academia: “The state’s sitting on mountains of data that does not get analyzed because we just don’t have the staff, so how do I leverage the research capacity of our institutions… If they can show us how to improve Medicare or Medicaid services or any entitlement program by researching our data to see where we're lacking and where those gaps could be, that's a win-win for the state, for the research world, for the applied and theoretical academic research titles”.

Success as CIO of Nebraska
Reflecting on his 18 months as CIO, Dr. McCarville spoke of his commitment to understanding Nebraska’s history by reviewing contracts and vendor relationships. He found his staff eager to modernize, despite previous limitations due to budget and resources. Now, he aims to treat vendors as long-term partners and, where possible, hire interns to drive progress. Dr. McCarville shared: “We are working with the local strategic air command air force base and the feds to be able to pump our interns through cyber and AI top secret security clearance programs so that they can become that top tier talent with a basis formed in their education and applied understanding at the State of Nebraska. So, we become that avenue that they are benchmarking our standards for education and training”.

Advice for Future Data Professionals
To conclude the conversation, Dr. McCarville encouraged future professionals to consider public sector roles, describing them as “government startups” where individuals can make an immediate impact using data, AI, and analytics. He stressed the importance of AI governance and ethics: “We're working with vendors that help us with the governance as much as we are working with the data cleansing and the enablement because they all want to enable it, but they don't want to think about the ramifications if you do things outside of ethical or legal boundaries. Not every amazing use case for AI is legally able to be implemented in the public sector.” The CIO finished the interview with advice for new practitioners: “We can do a lot of those things that students would not necessarily have the ability in their first job in corporate or consulting to be able to jump right into. They would have years of working their way up into that. Whereas in government, we can throw them right in the deep end and say, hey, we're going to swim. We're going to swim right now. You're going to help us get there.”

We are proud to spotlight Dr. Adita Karkera, Chief Data Officer at Deloitte Consulting LLP, and Michelle Boston, CIO, Head of Data Management Technology & Enterprise Architecture at Bank of America, as honorees in the CDO Magazine Global Data Power Women series.

In their recent interview, led by Amy Horowitz, Group Vice President at Informatica, Dr. Karkera and Michelle Boston offered valuable perspectives on the changing landscape of data leadership. They discussed moving from compliance-focused governance to adaptive, mission-driven strategies, with a focus on integrating AI-specific considerations such as explainability and bias. Their conversation addressed the challenges of advancing AI initiatives, balancing innovation with effective governance, and engaging stakeholders across organizations. These insights are essential for navigating the complexities of modern data and AI leadership.

We are pleased to present Part Two of our series featuring Dr. Adita Karkera, Chief Data Officer at Deloitte Consulting LLP, and Michelle Boston, CIO and Head of Data Management Technology and Enterprise Architecture at Bank of America, both recognized as honorees in the CDO Magazine Global Data Power Women series. Building on their initial conversation with Amy Horowitz, Group Vice President at Informatica, this installment delves further into how data leadership is evolving, highlighting a shift from compliance-based governance to agile, mission-driven strategies. Dr. Karkera and Michelle Boston share fresh insights on integrating AI, addressing important aspects such as explainability, ethical considerations, and mitigating bias, and discuss the ongoing challenges of implementing AI initiatives, balancing innovation with robust governance, and engaging stakeholders across organizations. Their perspectives continue to offer essential guidance for navigating the complexities of modern data and AI leadership.

Adita Karkera recently interviewed Chris Kraft to discuss his experiences in his role as the Deputy Chief Technology Officer (CTO) for AI/Emerging Technology at DHS. Chris started his career in the private sector in consulting, helping organizations implement and modernize large-scale systems. He then transitioned to Vice President of Corporate Solutions at SiriusXM, where he worked during the merger of Sirius Satellite Radio and XM Satellite Radio. During this period, Chris also attended law school, which ultimately led him to the federal space. As a public servant, Chris worked to modernize systems for the Executive Office for United States Attorneys (EOUSA) and subsequently the Federal Emergency Management Agency (FEMA). Upon joining the federal government, Chris was struck by the opportunities that technology provided to make the way individuals work more efficient and to free up time for people to do higher-value work. For example, at FEMA, Chris developed a Generative AI solution called FEMA OCFO GPT to help address budget questions that can take thousands of hours per year to answer and pull resources away from other mission-critical areas. The solution was built upon preloaded budget information and generated draft responses to budget questions, which the organization could validate and iteratively build upon outside the system, saving time and resources. In March 2024, Chris assumed his current role as the Deputy CTO for AI/Emerging Technology at DHS, where he pioneers the usage of artificial intelligence across DHS.

Differences between the public and private sectors

On the topic of the public sector versus the private sector, Chris emphasizes that the private sector offers more adaptability, but the decisions there do not nearly have as wide an impact as they do in the public sector: “At an organization like DHS or FEMA, when you make decisions on systems and approaches to implementing technology, they can have a significant wide-scale impact to the general public. I went back to the private sector for a little while, but the reason I stay in the public sector is being able to be part of the mission and being able to help people and do things that I think are really important for government to be doing, [like leveraging] technology responsibly. So, it’s really the mission and being able to help support the mission that keeps me very excited about the work that I do and the work that our teams do.”

How the CTO organization fits into the broader operations model at DHS

Expanding on how his role fits into the operational structure of DHS, Chris notes that the CTO organization works directly with the Chief AI Officer to lead AI efforts across DHS. His organization consists of three divisions: the AI Corps, the AI Governance and Engineering Division, and the Emerging Technology Division. The AI Corps was announced in February 2024, and Chris highlights how the government quickly hired and onboarded 25 AI experts who support cross-functional teams to take DHS’s use of AI to the next level. The AI Governance and Engineering Division helps with department-wide governance initiatives including use case inventories, safety and rights requirements, and complying with guidance under Office of Management and Budget (OMB) Memorandum M-24-10, which pertains to the use of AI within the federal government. The final division is the Emerging Technology Division, which focuses on the future of artificial intelligence and technology: “The idea there is that we need to continue to look forward to what’s coming next, and maybe it’s quantum or some other capability, or maybe it’s just another different application of AI; but having that group, really helps us continue to stay at the forefront of technologies.”

Generative AI initiatives at DHS

Discussing upcoming Generative AI initiatives at DHS, Chris highlights three key pilot use cases, which the DHS Artificial Intelligence Task Force (AITF) selected from a pool of around 30 submissions. The first pilot is with US Citizenship and Immigration Services (USCIS), which leverages a Generative AI chatbot to train officers to engage with refugees and asylum seekers using prompt engineering. The tool allows USCIS officers to ask questions and get human-like responses, which enhances their training as they become more comfortable with the types of answers they may receive in the field. The current training is provided by actors, which is limited by cost and requirements. The chatbot helps serve as a complement to existing training by providing more effective on-demand assistance to the officers without the cost of actors. The second pilot is with Homeland Security Investigations (HSI) and involves loading millions of investigations records into a vector database that generates responses to users’ questions. Chris states: “I sat in the room when the agents were testing this, and it was just so encouraging to hear the agents say, ‘It’s like the needle in the haystack. I’m finding things that I didn’t even know existed.’ Agents are searching for monikers for dark web cases and they’re identifying some that they didn’t even know were connected. I think that’s really the power of natural language processing and embedding information: using artificial intelligence to find similarities, surfacing the similarities, and then using Generative AI to summarize that information.” The third pilot initiative is housed under FEMA, and its purpose is to create hazard mitigation plans to support underserved communities. Chris explains that extensive and specific plans are required to qualify for funding, but some smaller communities don’t have all the necessary resources to create those plans: “The idea is to use Generative AI to capture information and then generate the plan, so you reduce the burden and make it easier for those underserved communities to get the resources that they really need.”

Challenges DHS faces in its AI deployment

Speaking on the challenges in deploying AI at DHS, Chris sheds light on the obstacles surrounding talent acquisition and bringing in the right people to implement and leverage AI technology, including contractors as well as federal employees. He notes that the DHS AI Corps (what will be the largest dedicated AI team in the federal government) is extremely helpful since it utilizes a vast breadth of knowledge to ensure things flow smoothly with internal talent and external partnerships. Another challenge Chris has seen is workforce readiness in the face of Generative AI and making sure his colleagues within DHS have the tools they need to understand and utilize this technology. Chris notes that training sessions are being held across DHS to address this problem. He emphasizes how DHS has already approved the use of commercially available tools like ChatGPT, Copilot, and Grammarly, but the challenge is making it clear to others how and why they should use these tools: “I think for those of us that are in technical positions, it’s easy to lose sight that most of our organization is just not as familiar or comfortable with the technology. So we’ve been holding a number of sessions where—and for a lot of them, I’ve actually been running these sessions—we’ll walk through these use cases of how you can leverage the tools: let’s walk through example one, here’s the data, here’s the prompt, let’s put it into the tool, let’s see what comes out.” These sessions build the workforce’s understanding of the full cornucopia of AI tools currently available to them in hopes that they will use these tools in their day-to-day tasks to make the way they work more efficient.

What the governance landscape looks like at DHS

Discussing the governance landscape for emerging technologies, Chris describes the protocols in place at DHS, including policies on the use of AI, facial recognition, and commercially approved Generative AI tools. He underscores that DHS is required to have an AI Governance Board to comply with OMB Memorandum M-24-10. Chris expands on the purpose of the AI Governance Board: “That’s a critical governing body that is actively engaged in how we’re leveraging artificial intelligence and how we’re using the capability responsibly.” He also notes that the DHS Office for Civil Rights and Civil Liberties (CRCL) leads DHS AITF’s Responsible Use Group (RUG) to actively govern DHS’s AI pilots (mentioned in part 2). The RUG and CRCL help to ensure that DHS uses AI technology responsibly, remains transparent in its use of AI, and follows external guidance such as the requirements outlined in M-24-10; for example, maintaining an AI use case inventory.

Advice for those looking to grow in the data and AI field

To wrap up the conversation, Chris shares his perspective on the importance of organizations protecting themselves as they leverage AI to achieve their missions. He states that government organizations should be well-educated on the technology they use, understand how technology constantly evolves, and have adequate resources to support these efforts. Chris acknowledges the importance of the government being at the leading edge of AI, emphasizing that public organizations need to work together in this endeavor: “I also think in the public sector—primarily at the federal level, but I also think it applies to state and local—we need to work together and we need to share information, because there’s no point in every federal agency or department figuring this out on their own and having to just blindly try to navigate. I know there are a lot of efforts underway to collaborate through the Chief AI Officer Council and other activities across the federal space, but I think it’s important that we work together, share information, help each other out, and continue to leverage the technology responsibly.”

Adita Karkera recently spoke with Fredy Diaz to discuss his role as the Deputy CDO of the US Department of Agriculture (USDA). Fredy has an extensive background in data governance and analytics and mentions the nontraditional path to his current role, which started in the US Marine Corps. That's where he says he 'fell in love' with data analytics while working in aviation and logistics and then proceeded to move through other government agencies including the Department of Defense, Department of Labor, and USPS Office of the Inspector General before he arrived at the USDA.

Where the role of Deputy CDO fits in operationally within the USDA

When asked about his current role within the USDA, Fredy reports to the Office of the Chief Information Officer (CIO), where his team has been granted technology capabilities and benefits that they're able to leverage. The Deputy CDO describes his role as 'very fun and exciting,' where he sits on the USDA CDO Council with the CDO and eight other mission-area assistant CDOs. He emphasizes his role as an adviser to CDO and Chief AI Officer Chris Alvarez. Fredy says his day-to-day is building relationships and trust across the organization: 'We value trust with our different organizations, and that’s how we’re able to leverage different programs.'

Artificial intelligence within the USDA and the Department’s core data strategy

On the topic of artificial intelligence AI, Fredy notes that the CDO is also functioning as the Chief AI Officer, and USDA is still having conversations about where the AI governance functions live. He says the USDA is ensuring it has 'AI-ready data and processes in place for AI that could have some alignment with our IT functions but may also have a lot more resonance with what we're doing currently in the data space.'

The Deputy CDO then discusses how the USDA is currently working on its second data strategy, but its five main strategic goals are focused on:

1. Strengthening data governance and leadership
2. Recruiting and upskilling the workforce
3. Maturing the enterprise data platform
4. Data sharing within the USDA, external agencies, and the public
5. Improving analytics techniques and ensuring the Department bakes in ethics from a data analytics standpoint

Fredy concludes the conversation by discussing the challenges the USDA faces, which includes understanding the existing strategy, distinguishing where it executed well, and finding communication gaps. The CDO states, 'We spent a lot of time from listening sessions, surveys, draft revisions—getting a pretty good representative group of folks across the Department to help us write the strategy. What we wanted to ensure was that it wasn't a shock when it went through the clearance process or when it finally came out.' When the strategy came out and a diversity of stakeholders were proud of it, it showed the Deputy CDO, the CDO, and others that the work was a success and not just a 'paper exercise.'

Focus on AI strategy initiative

Fredy Diaz continues the conversation with a discussion about an artificial intelligence (AI) initiative he is excited about—the USDA is currently working on developing its AI strategy in accordance with the Office of Management and Budget. The Deputy CDO reveals how the credibility his organization has built from developing and starting to execute its data strategy in a more holistic view across multiple stakeholders is ‘paying dividends,’ and now it’s just a matter of doing that exercise again. Fredy says this has been helpful for crafting a vision for AI in the USDA as well as aiding in the Department’s ability to execute on newer technologies like Generative AI.

An AI use case within the USDA and the Department’s open data work

When asked to provide a use case of AI within the USDA, Fredy elaborates on two items he’s most proud of. The first is that the Department has an AI Center for Excellence. Fredy expresses, ‘I love the fact that this started as an initial group and has scaled up, and now we have a bunch of practitioners that we can call on for various projects, big hairy problems that come up with AI, and we’re not just solving it at the Department or in small pockets—we can call in this group where needed.’

The second is the USDA’s work with its chief technology officer and working to spin up a technology quickly, evaluate it, ‘kick the tires,’ and see if it’s good for the agency’s purposes. Fredy notes, ‘That partnership has really paid off, and we’re expecting that when it fully matures it will reduce our time to evaluate technologies and software.’ The conversation then shifts to the USDA’s open data strategy, which includes public data, such as the Census of Agriculture, as well as its own open data platform in which the public can see how dollars are being spent in different areas. The CDO also mentions that the USDA is publishing data in university classrooms nationwide, which not only gives students the opportunity to view real-world data and problems, but also may pique students’ interest in working in public service by showing them what organizations like the USDA have to offer.

Successful data literacy programs within the USDA

On the topic of data literacy programs within the USDA, Fredy shares three programs that he thinks have done exceptionally well: the USDA’s data science training program, which has grown from two dozen participants to nearly 200 participants within the organization, focused on upskilling and training members through a capstone project as well as networking; increasing the amount of rotational opportunities that employees are given; and rapid prototyping and hackathon events so individuals can apply learned skills and have even more chances to participate.

Advice for aspiring data professionals

To conclude the conversation, for those looking for a career in data and analytics in the future Fredy provides some words of advice that include embracing data challenges. He says, “Don’t be afraid to volunteer. I’ve had a lot of folks that have expressed interest in rotating to the Office of CDO somewhere in the organization, and it just started with the question of how they could be of help. It starts with making your intentions known and just letting someone know—either a peer or even just a cold email to someone—and say, ‘I would love to explore an opportunity.’”

Adita Karkera recently sat down with Robert (Rob)  King to discuss his role as the CDO of the US Department of Energy (DOE). A systems engineer by trade, Rob has a wide-ranging background in IT, which includes working in the private sector before joining the Department of Homeland Security (DHS) in 2011. From 2012 to 2020, he 'took the reins on driving a data and analytic strategy' for the DHS, during which time he became its CDO for mission support in 2016. Rob then became the inaugural CDO for the Social Security Administration (SSA) in 2020 where he stood up a data governance board; introduced data literacy, governance, and analytics; and drove consistency across the SSA’s 1,500 field sites. By 2023, both of those leadership experiences led Rob to his current role as the DOE’s CDO where he and his team are building out an enterprise data management program.

Lessons learned and how the CDO fits within the DOE

When asked about what he’s learned through his years as the DOE’s CDO, Rob highlights that the role is still new (only mandated five years ago by the Evidence Act), and it’s 'one that needs to be able to orchestrate across many other functions of the organization.' The CDO discusses the importance of corporate psychology; even though he and his peers are mostly data and systems people, they still need to 'win the hearts and minds' of others in the organization and build coalitions to enhance their mission through data and advanced analytics products. Regarding how the role of CDO fits within the DOE, Rob states the position falls under the chief information officer  (CIO), but it was initially under the chief financial officer (CFO) in FY2022 before he joined in FY2023. Under the CFO, it was a collateral duty role, but the DOE shifted it to a full-time role under the CIO, allowing the CDO to manage an enterprise data management program without other distractions.

How does AI play into the CDO’s role, and what is the current data strategy at the DOE?

On the topic of artificial intelligence (AI), Rob shares that the DOE appointed a new chief AI officer and formed an AI Executive Order working group that is tri-chaired by the chief AI officer (Director of the new Critical and Emerging Technology Office), a responsible AI officer (Deputy CIO), and the CDO (Rob). Rob explains, 'We need to be working in that coordinated, collaborative manner to develop a cohesive strategy … and recognizing that we cannot separate data and its critical role to AI.' The conversation then pivots to the DOE’s data strategy, which the CDO prefaces with the fact that more than 50 national lab security sites and program areas comprise the DOE, many of which are government-owned and contract operated—a culture that poses a unique challenge to the data strategy work. 'When I work with our legal and oversight bodies,' Rob notes, 'it’s really trying to find the blend of how we balance the federal, legislative, and statutory drivers against the fact that there aren’t necessarily government organizations to which our programs are being operated, so we have to look at this through a multidimensional framework.' With that in mind, and referencing other federal data strategies, the DOE has come up with five strategic goals that have commonality with other strategies. These five goals include establishing data governance and stewardship, building data architecture and infrastructure, focusing on data quality and discoverability, determining what data literacy and a data literate workforce look like, and ensuring responsible and sustainable use of data for artificial intelligence.

Adita Karkera recently sat down with US Immigration and Customs Enforcement (ICE) CDO Carin Quiroga to discuss some of her day-to-day responsibilities as well as some of ICE’s current data initiatives and strategies. Carin spent 11 years at US Customs and Border Protection before joining ICE and becoming the CDO—a position she has held for the past two years.

The role of CDO within ICE and current accomplishments

Carin’s role is currently positioned under the chief information officer. She highlights how her role as CDO includes getting others excited about data. When Carin began her role as CDO, the goal was to become an 'action-oriented' office and tackle the issues and gaps within ICE’s data. Her team conducted various interviews with different stakeholders and leaders to pinpoint exactly what their issues were. Then the team created the IT data modernization roadmap whose framework is 'collect, automate, and use.' Carin states, 'We needed to ensure we were collecting the right data at the right time, stop collecting data that we didn’t need or didn’t use, and then really drive automation and use that data to increase transparency and make decisions.' Based on this roadmap, ICE’s data office was able to create an accountable, measurable data strategy.

An ICE data initiative that excites the CDO

One data exchange and sharing initiative that Carin is very excited about is the 'data bodega,' which she explains is 'a centralized location where everybody can go to know how to get the data and where to get the data from.'

ICE’s Data Empowerment Program

Continuing the conversation, Carin Quiroga discussed creating the Data Empowerment Program after she became ICE’s CDO. The program focuses on data literacy because “everybody has a role in the data life cycle.” She wants to ensure everyone has an opportunity to gain experience and feel “empowered” in their data journey.

Passions that currently motivate the CDO every day

When asked about what drives her every day, Carin reinforced the idea that “data is knowledge, and knowledge is power.” The CDO says she’s very excited about bringing others together and using data to make better decisions and become more efficient.

How ICE addresses data governance and quality

Carin described data governance in terms of “changing the culture to understand you’ve got to let go of your data. You’re going to share it, and someone else is going to use it.” By understanding this, individuals within the organization are more likely to implement data standards and ensure the quality of their data is accurate. The CDO also emphasized the importance of collaboration between the different agencies, particularly the Department of Homeland Security (DHS), which includes monthly CDO councils between the different agencies to discuss their challenges and the work they’re doing.

Advice for aspiring data professionals

Carin closed the interview by talking about her enthusiasm with working with women in data and creating diversity in a male-dominated technology industry. The CDO said, “For me, it’s just so important to have everybody’s point of view, everybody’s history, everybody’s perceptions while we’re going through this journey.” The CDO’s advice is to never give up and to always be your authentic self.

Adita Karkera recently spoke with Ken Pfeil to discuss his day-to-day activities as the CDO for the Commonwealth of Virginia. Ken has an extensive background in the private sector after his military service, which includes working for Dell and being a technical architect for Merrill Lynch, as well as working more than 20 years in the information security sector before taking on his current role.

Where Ken Pfeil’s office is located and the work he drives with other agencies

Ken's office is codified in Virginia law, and it officially became an agency in July 2021. The CDO reports directly to Secretary of Administration Margaret 'Lyn' McDermid, and his office works with more than 100 agencies to provide data services. Ken states his office is mandated by Virginia law to provide the data governance standards across the Commonwealth and does so through a three-tiered hierarchy, which consists of the Virginia Data Advisory Commission, an executive data board, and a data governance council. Underneath this lies an informal data stewardship group, which Ken explains is 'the meat and potatoes part, where everyone gets to learn their collective responsibilities when handling data, using data, and owning data.' The CDO also highlights a Data Maturity Management Assessment (DMMA) conducted by his office to other agencies, which surveys their culture, support, and how they’re handling data. The survey, which achieved a roughly 84% response rate, assisted Ken’s office in finding agencies that were more mature in their data governance and used some of their practices to help other agencies that are not yet operating at that level.

How Ken’s team is breaking down and prioritizing key issues throughout Virginia

When discussing how the CDO's office is addressing significant issues in Virginia, Ken states that certain objectives must be met within a time frame, such as engaging in Operation Bold Blue Line, an objective to lower crime within 13 localities in Virginia. Ken affirms, 'We were instrumental in facilitating all of the data collection transfer, dashboard analytics,' which helped the governor of Virginia make decisions regarding where a police surge may be needed. He also emphasizes how much support his office has had from the governor and first lady and Virginia cabinet members: 'Most of the time, if there is an issue, I can generally raise it with them, and they’ll go right back to that agency head and say you need to sit down … to figure this out.'

Differences between private and public sectors in terms of data challenges

Ken discusses some of the differences he’s noticed between dealing with data challenges in the public versus private sector. For instance, the data maturity level in the private sector is usually higher than in the public space, according to Ken; and other agencies are typically resistant to change, so he is wary of throwing too much information at others just because it works in the private sector. When discussing some of the challenges he faces, Ken states, “One thing that resonates everywhere is the ‘silo-ization’ of data.” Many agencies are very cautious of sharing their data with each other, and the CDO helps them to see the positive outcomes of sharing that information.

Further insight into data trust

Ken describes how data trust between agencies consists of two major parts: the Commonwealth Data Trust (CDT) and the Virginia Open Data Portal. The CDT is mainly for agency-to-agency sharing, or locality-to-locality sharing, and consists of a universal entity index of 8 million to 8.7 million Virginians. The index is stripped of personally identifiable information and allows the CDT to use the data successfully and securely on an anonymized basis. The CDT also consists of a common memorandum of understanding, for which Ken is the trustee. This document is 27 pages long. The CDO notes, “We decided early on that we were going to list the first 22 pages as what our obligations are to each agency”—for example, keeping data private and secure, classifications and roles, among other topics.

The Open Data Portal was set up for transparency per Virginia code and allows localities to federate their public data to another locality through Ken’s agency. The CDO also presents his agency’s data trust automation process, which helps facilitate data transfers between other offices. The process would usually take one to two days previously, but Ken’s team has cut that down to a matter of minutes using this automation initiative.

Ken’s efforts around data literacy

When discussing the topic of data literacy among agencies, Ken underscores that every member of the Commonwealth Data Trust is eligible to participate in data literacy and upskilling programs. The agency has partnered with Dataversity so that “any agency has the ability to take courses—from the executive level, where you know nothing about data, to the DMBoK [Data Management Body of Knowledge] certification side of the house.”

Upcoming projects Ken is excited about

Ken highlights one initiative he is especially excited about, which involves working with the Virginia Department of Veterans Services to identify every veteran in Virginia and “make sure they understand what their entitlements are, how to get access to said entitlements, and just facilitate taking care of veterans.” Another initiative that the CDO introduces is the Office of Workforce Development and Advancement where his agency provides oversight in the workforce development ecosystem. Ken’s agency has helped provide pathways from education to the workforce and is playing a major role in putting together a singular job portal to place citizens in the workforce, utilizing artificial intelligence (AI) to identify skills that align to existing jobs. The CDO emphasizes that “the governor had an initiative to bring 400,000 jobs into the state of Virginia when he was inaugurated, and I think we’ve hit over 230,000 already.”

Leveraging and governing the use of AI at the state level

On the topic of AI within his agency, the CDO explains how they are using predictive analytics for cyber security to supplement other localities not having sufficient staff to properly address their own security issues. In terms of governing AI, the CDO addresses four main focus areas to help establish guardrails and safety mechanisms: “One of them is around privacy and intellectual property, we also have policy standards for effective and safe usage around AI, we have IT-related safeguards … and lastly, we want to ensure all of our Virginia students are properly trained within those guardrails and they’re ready to compete for jobs in the workforce.”

Advice for future data professionals

To conclude the interview, Ken shares his advice for individuals who are looking to prepare for a role within the data and analytics field—it’s to not focus on a singular framework or system. “Immerse yourself in different areas of technology … get out there and understand how the whole system works together,” he suggests. The CDO also reveals that leaders must learn to work better with the newer generations and that trust always goes both ways.

Dr. Bryan Pendleton discusses his role as CDO in the DHS Office of Intelligence & Analysis (I&A), his journey to the position, and DHS efforts to make discoverable the vital intel used to aid in the protection of US citizens.

Dr. Pendleton partners ‘humans with machines’

Dr. Pendleton came to the DHS in 2011 as an intelligence officer after a career in the US Army and the Defense Intelligence Agency. Since then, he has had multiple roles within DHS I&A and, in 2016, was asked to lead a technical intelligence group leveraging computer and digital forensics that became foundational to his journey to CDO.

'We had a very large backlog of data that needed to be made sense of, but we had a very small staff, and all our processes were very manual in nature,' Dr. Pendleton said. He applied his background in Lean Six Sigma to bring in lean approaches and automate those processes using machine learning. These approaches worked to quickly derive value from the data and disseminate it to those who needed it. His efforts partnering humans with machines informed the basis for his appointment to CDO.

Connecting the dots for the mission

Dr. Pendleton said, 'In the aftermath of 9/11 and the failures of the US government broadly to connect the dots, it became really clear to me that my job was all about the dots.' He explained his primary responsibility is to get intelligence professionals the data they need to identify threat actors. He is constantly working to identify which 'dots' are relevant, negotiating appropriate access to that information, and providing the DHS workforce with advanced analytics to support them connecting the 'dots.'

For more on how Dr. Pendleton engages his stakeholders and how 'everything is about partnerships and relationships,' watch part 1 of the full interview above!

Key pillars of Dr. Bryan Pendleton’s data strategy

DHS’s data strategy is built upon four pillars, the first being maturing its data management process: 'We actually did have really good data management practices and procedures, but what we didn’t really have was a cohesive end-to-end process.' The second pillar is all about improving information-sharing within the DHS to 'help get ahead of some of these issues that resulted in the catastrophes of 9/11,' as Dr. Pendleton explains. The final two pillars include 'adopting emerging technologies to include advancement of our accelerated adoption of artificial intelligence' and improving data literacy and acumen of non-data professionals.

Dr. Pendleton’s AI responsibilities and priorities

Speaking on AI innovations, Dr. Pendleton wears multiple hats: To the intelligence community, he is the 'senior official appointed to accelerate I&A’s adoption of AI,' and he represents I&A and DHS on the Augmenting Intelligence Using Machines Executive Steering Group. For DHS, he is I&A’s representative to a consortium of senior officials responsible for AI within DHS components. They meet to ensure strategies and initiatives are 'in synchronization' with secretary  guidance and priorities and are led by the DHS headquarters.

Managing data governance across the DHS

'When it comes to data governance broadly, our team facilitates something we have—which I view to be a best practice across the US government—called the Data Access Review Council (DARC).' DARC’s core focus is the sharing of data agreements to ensure that any distribution of bulk departmental data comports with all the applicable privacy impact assessments and is appropriate and lawful. This works by 'being very use case case-driven. It’s an extraordinary, complex landscape to facilitate information- sharing agreements, but the DARC, in my mind, really accelerates those things by bringing all the stakeholders together from the very beginning.'

Dr. Pendleton’s key accomplishments as the DHS I&A CDO and future key initiatives

The CDO celebrated as “monumental” publishing, implementing, and measuring the success of his first data strategy. Dr. Pendleton also highlighted how getting the DHS’s data scientists to work alongside the intelligence team enabled mission work: “The more they work side by side, the more they start to speak each other’s language and understand what [the others] are capable of.” On data acumen and literacy and through a partnership with the intelligence training academy, they have launched a Data 101 module that is now part of the basic intelligence training course for all DHS analysts.

Among other initiatives, the CDO celebrated the kickoff of the DHS AI Taskforce: “I think that the intelligence community has a lot of capability when it comes to AI, and to the extent that some of those capabilities actually are unclassified in nature, I want to see how I can be the bridge to bring intelligence community capabilities to the department.”

Dr. Pendleton’s advice to aspiring data professionals

Dr. Pendleton provided some advice for aspiring data professionals: “Figure out what you’re passionate about, what drives you, what mission you want to support, and let that be the thing that guides you.” He emphasized the importance of soft skills like teamwork, relationships, and negotiation in helping individuals advance their careers. Dr. Pendleton explained that diversity, equity, and inclusion must work together in the workforce: “The problem with having a simply diverse workforce is if they’re not included in actually solving problems and bringing their very best to bear, we get suboptimal solutions to the toughest problems. … It’s not just about the diversity of our workforce; to me, it’s about actually including those people practically and bringing them to the table.”

The First CDO at FDA

Ram Iyer became the FDA’s first CDO during the COVID-19 pandemic after 25 years working across private industry, non-profits, consulting and international agencies.

At FDA, “our focus was very heavily on just getting things done in the first few months for the immediate needs”. Mr. Iyer believes that having the CDO one level removed from the commissioner has given his team the needed visibility and helped them make tremendous progress over the last two years.

Creating an Actionable Data Strategy

The FDA’s data strategy consists of three pillars: value-driven projects, building foundational capabilities, and a hyper-focused plan for talent. “With all these three we’ve been able to successfully create an ecosystem of tools, processes and data removing some friction that existed in the organization for user data.” Emphasizing the combination leadership support and these pillars, he celebrated resolving problems in the data-practices side and mission priorities.

A Few Success Stories as a CDO

Mr. Iyer highlighted creating FDA’s master data catalog for the products or ingredients they need to monitor and how they have used AI to pull data from artifacts to create digital assets. Mr. Iyer also discussed the office’s success in upskilling, laying out their “70-20-10” model: “70% of their time is spent working on real problems... 20% of the time is spent on mentoring….only 10% is spent on typical traditional classroom training so we have found this to be particularly effective”. Using this strategy, the FDA was able to solve essential problems while saving time and significant funds and produce a cohort of 36 trained data scientists with a common understanding of how to solve problems for the agency.

On the Value of Publishing a Data Strategy

Publishing the data strategy “allows us to test our implementation against the north star that we establish”. Mr. Iyer notes the critical step to collect input from key stakeholders and individual perspectives when developing their strategy: “when we built our strategy, we did not do it in isolation... it’s important that the process is collaborative and inclusive”. The strategy must be able to adapt to new things like AI, but not be so high level as to be ineffective for implementation.

FDA Initiatives Implementing AI

FDA looks at AI at multiple levels: operations, productivity, and policy. Mr. Iyer says operations provide a learning and testing ground to be more aggressive on AI. On productivity, the FDA is considering capabilities for office suites or other operational areas. He identifies policy and regulation as the larger and time-consuming issue. FDA both supports centers on policy and is working with multiple agencies and public private partnerships. “We have formed an AI governance and guidance board that is meeting to help identify the right use cases and also implement them and through those learn what is the right use of AI within the agency”. They use a guiding principle of “faster is not always better and easier is not always the best.”

Career Lessons Learned

Mr. Iyer expressed appreciation for how quickly and effectively the FDA responds to challenges and the remarkable talent that exists at FDA: “because I started in the virtual environment, I did not have the interactions that I would have liked to have with so many of the great talented folks across the agency and if I had known all the great talent that was available, I think I would have built my network faster to solve some of the bigger problems”.

Adita Karkera recently sat down with Dr. Alan Sim to discuss his role at the CDC and their innovative project initiatives as well as his insights into public health data. With a background in epidemiology and public health, Dr. Sim’s career has spanned 25 years at the CDC “looking at the application of informatics IT in public health.”

Dr. Alan Sim’s role within the CDC

Dr. Sim serves the CDC’s new Office of Public Health Surveillance, Data, & Technology (OPHDST).  Expanding on his role, the CDC’s CDO calls himself a “data diplomat” to his peers: “the term data diplomat best suggested that I would take a role where I would represent them…highlighting often the work that’s being done that unfortunately sometimes gets buried under layers of bureaucracy”. To accomplish this Dr. Sim created the Enterprise Data Office based on three priority areas: Enterprise Analytics and Data Science, Strategy and Enterprise Data Management, and Data Governance and Policy.

How Dr. Sim is operationalizing data governance for the CDC

Dr. Sim noted that: “To try to implement data governance is extremely challenging and you generally don’t have consensus, and the progress you make is very minimal “. The CDO noted his approach is about breaking things into domains of work by communities that are particularly invested in the data. Dr. Sims suggests that “when you have those communities that are really invested in the data products that are being generated there, you have a higher chance of finding commonality and consensus”. To achieve this unanimity, the CDC stood up a data standardization management and harmonization working group along with an IT and Data Governance initiative focused on investments and data architecture implementation.

Initiatives at the CDC

Dr. Sim highlighted CDC’s where CDC is making public health systems more responsive to public health disasters. Dr. Sim discussed strengthening the public health data by creating a front door for bringing data to the CDC. To accomplish this, the agency is looking to standardize the funnel of where data comes in and use “best of breed” processes to ensure the data then gets disseminated across CDC. Dr. Sim is also excited about partnering with program data scientists who leverage computer vision technology to identify satellite images and locations of cooling towers during a Legionnaires’ disease outbreak, as well as developing machine learning and NLP techniques to mine social media posts to identify trends in suicide incidents and aide in suicide prevention.

Improving internal data literacy at the CDC

Dr. Sim discussed how the CDC HR office “developed a career ready program that creates a career community where we can identify what are those necessary skills, necessary milestones to help existing staff move up the career ladder”. The CDC has an online data academy where they provide self-guided training on data science languages. Dr. Sim spoke about helping individuals learn about the diversity of public health data and the resources they would need: “if I myself was a junior data scientist or someone who is interested in improving data literacy, what are those resources that would be available to help me to do those kinds of things and advance my career”.

Advice for aspiring data leaders

To conclude the discussion, Dr. Sim provided advice he would share with aspiring data leaders. “Be bold and innovative, attack problems creatively… leverage the data, the tools, the services that are available and while you’re attacking the problem connect with your peers”.