As Governments Embrace AI, Privacy Engineering Is Becoming Harder to Ignore
- As she begins leading government partnerships at the Paragon Policy Fellowship, Akintan is positioning privacy engineering as a practical discipline for how institutions adopt artificial intelligence.
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Artificial intelligence is moving quickly into workplaces, products and public institutions. For Modupe Akintan, the more important question is not whether organisations will use it, but whether the systems they adopt are designed to handle people’s information responsibly.
Akintan, a Nigerian computer engineer and Stanford graduate student, has built her work around privacy engineering: translating expectations such as data minimisation, appropriate access and user control into choices that engineers and organisations can actually implement.
Source: Facebook
That focus is now shaping a new chapter in her career.
In December 2023, Akintan took on the role of Director of Partnerships at the Paragon Policy Fellowship, where she is helping government agencies turn emerging technology concerns into concrete projects for technical fellows.
The role places her at an increasingly important intersection: governments want to experiment with generative AI and other data-intensive systems, but many still need practical ways to evaluate what those systems collect, what they can access and what risks they create before deployment.
Akintan said:
“For me, privacy is most useful when it becomes something an engineer can build or test. If an organisation says an AI system should only use the data it needs, then we have to be able to define what ‘needs’ means in that system and put controls around it.”
A technical leader entering public-interest technology
Akintan’s move into Paragon is not a departure from her earlier work. It is an extension of it.
Before Stanford, she worked in cybersecurity and privacy in Nigeria, where she supported organisations trying to translate security and data-protection requirements into operational practice.
At Stanford, her research has focused on measuring technology risk and testing whether commonly used indicators actually correspond with real-world security outcomes.
She also spent the summer of 2023 in user privacy engineering at Apple, an experience she describes at a high level as formative because it showed her how privacy considerations can shape product decisions before a feature reaches users.
Across those settings, Akintan says the recurring challenge has been the same: organisations often know the principle they want to uphold, but the harder work is determining what the technology must do differently.
She said:
“You can have a very good policy and still have a system that exposes information unnecessarily. “That is why I am interested in the engineering layer. I want to understand the data flow, the access path and the control that actually reduces the risk.”
What her Paragon work is designed to do
At Paragon, Akintan’s work begins before a fellowship team writes a recommendation.
Government partners may arrive with a broad concern about generative AI, AI security, misinformation or another emerging technology.
Her role is to work with them to identify the decision underneath the concern, shape a project around it and make sure the final scope is specific enough to produce something the institution can use.
That process draws heavily on her technical background. A question framed as ‘How should we use AI responsibly?’ may need to be narrowed into questions about the information entering a system, the systems it can connect to, the people authorised to use it and the controls that should exist before deployment.
Akintan sees that translation work as central to her leadership at Paragon.
She said:
“The goal is not to produce another broad document about AI. “The goal is to help an institution get from a concern to a decision it can act on. That means understanding both the policy objective and the technical reality.”
Why privacy engineering matters for AI
Akintan’s expertise is increasingly focused on privacy engineering for AI systems because AI changes the way organisations interact with data.
A traditional application may have a narrow set of inputs and permissions. AI systems can be connected to large repositories of information and can infer, retrieve or generate information in ways that are less predictable.
For Akintan, that makes privacy-by-design more important, not less.
She points to questions such as whether a system is collecting more information than a task requires, whether access is broader than necessary, whether sensitive information can flow into third-party tools and whether privacy risks have been assessed before the system goes live.
These are not simply compliance questions, she argues. They are architecture and product questions.
Akintan said:
“AI can create enormous value, but access to more data should not automatically be treated as better. A strong system should be able to use what is necessary for the task without making unnecessary exposure part of the design.”
Building a reputation around implementation
At Stanford, Akintan is completing a master’s degree in Computer Science with a concentration in Computer and Network Security. Her academic work, industry experience and new leadership role at Paragon are converging around a clear professional direction.
Rather than focusing only on privacy law or broad AI ethics, she wants to work on the technical mechanisms that make privacy enforceable in real systems.
That means developing methods for reducing unnecessary data use, limiting access, assessing privacy risk and helping organisations understand what protections need to exist before AI is deployed.
Her work at Paragon gives her a new environment in which to apply that thinking: public institutions making decisions that can affect large numbers of people.
For Akintan, the opportunity is not simply to participate in the AI policy conversation. It is to help shape what implementation should look like.
She said:
“The important part for me is turning principles into systems. “That is where privacy engineering can make a real difference.”
Source: Legit.ng
