From Brooklyn to the United Nations: Julia Stoyanovich’s Global Mission for Responsible AI

When New York City became the first municipality in the country to establish a task force examining how automated decision-making systems affect its residents, Julia Stoyanovich was at the table. Appointed by then-Mayor de Blasio to serve on the NYC Automated Decision Systems Task Force, she helped lay the groundwork for responsible AI governance at the local level. The task force examined where and how city agencies use automated decision systems, what oversight, safeguards, and recourse should accompany that use, and how the systems affecting New Yorkers’ access to public services and other government decisions could be made more transparent and accountable.

That work—bridging technical rigor and public accountability—is a theme of Stoyanovich’s career. As an Institute Associate Professor of Computer Science and Engineering at the Tandon School of Engineering, Associate Professor of Data Science at the Center for Data Science, and Director of the Center for Responsible AI (R/AI), she has spent years translating the technical foundations of algorithmic systems into actionable insights for city officials, policymakers, and ordinary New Yorkers.

That commitment to the public good has not gone unnoticed. This year, City & State magazine is honoring Stoyanovich with an Above & Beyond Award, recognizing her sustained contributions to New York through policy engagement and public education, and her determination to ensure that AI systems deployed in civic life meet meaningful standards.

Taking the Conversation Global

Stoyanovich’s reach, however, extends well beyond the five boroughs. In February 2026 alone, she spoke twice at United Nations headquarters, addressing two very different audiences on the same urgent theme: how humanity can shape its relationship with artificial intelligence before that relationship shapes us in unwelcome ways.

Speaking to the Next Generation: “The Joys of Doing, Learning, and Being”

The first event was a panel at the 64th Session of the Commission for Social Development titled “Shaping the AI Future: Ethical and Inclusive AI Governance for Youth and All,” which brought together diplomats, UN delegates, civil society leaders, and young people from around the world.

Stoyanovich’s contribution, titled “The Joys of Doing, Learning, and Being,” began with a children’s story she co-wrote — Happy Birthd-AI — about a boy who wants to create something meaningful to celebrate his mother but lets an AI system take over, with predictably hollow results. It was a parable, she explained, about the risk of outsourcing the very acts that make us human.

Drawing on Aristotle, Dewey, and Epicurus, she argued that joy does not exist apart from effort — it crowns it. The pleasure of learning comes from struggle and discovery, not from having an algorithm deliver the answer. When AI absorbs too much of the “doing,” she warned, human accountability begins to dissolve. “We must preserve the space where thinking and doing meet,” she told the audience, “because that’s where joy lives.”

Her closing image returned to the boy in the story: he does not give up on his mother’s birthday celebration. He learns to work with the AI rather than handing everything over. That collaboration, she argued, is the vision young people should carry forward: one in which machines extend our reach without replacing our wonder.

Addressing Global Data Leaders: “From Open Data to Responsible Reuse”

Her second UN appearance brought an entirely different audience and a different register. Speaking to senior officials from national statistical agencies and international data bodies, Stoyanovich delivered a technical and policy-focused talk titled “From Open Data to Responsible Reuse: Hallmarks of Data Stewardship in the Age of AI.”

Her argument was direct: responsible AI does not begin with models—it begins with the data those models consume. In an era when official statistics and sustainable development indicators are routinely ingested, summarized, and acted upon by AI systems without attribution or context, the traditional chain of data stewardship is breaking down. A query about a country’s GDP trends, she illustrated, can return a confident-sounding AI answer that silently mixes outdated releases, ignores revisions, strips uncertainty, and loses the institutional provenance that makes the number meaningful.

To address this, Stoyanovich proposed a set of interventions spanning data readiness, organizational readiness, technical infrastructure, stakeholder input, and mechanisms for closing the feedback loop when AI-mediated reuse produces errors. She advocated for machine-readable data “nutritional labels” — clear, standardized disclosures specifying provenance, vintage, uncertainty, and conditions of use — so that AI systems can preserve essential context as data moves through automated workflows.

Looking ahead to increasingly agentic AI systems, in which errors do not merely inform decisions but trigger actions, Stoyanovich argued that the role of national chief statisticians must evolve. No longer simply data providers, they must act as stewards of public knowledge infrastructure. "For many years, our focus has rightly been on openness: making data available, interoperable, and accessible,” Stoyanovich asserted. “But in an AI-mediated environment, openness is no longer the end of the story. Once data is released, it can be scraped, summarized, ranked, embedded, and recombined by systems we do not control. So the question is no longer only how to produce high-quality statistics. It is how to ensure that those statistics remain meaningful, trustworthy, and context-rich as they move through AI systems."

Research with Real-World Impact

These UN appearances reflect the breadth of a scholarly career that extends well beyond the ivory tower. Stoyanovich’s research on algorithmic fairness, AI transparency, and data governance has appeared in leading academic venues and public outlets such as The New York Times and The Wall Street Journal, and has earned recognition, including the Presidential Early Career Award for Scientists and Engineers (PECASE) and an NSF CAREER Award. Her Center for Responsible AI has advanced public understanding of AI, developing widely used educational tools including We Are AI, a public AI literacy initiative created with Queens Public Library, alongside multilingual comic book series and animated shorts that make complex ideas about AI accessible to a broad audience. She has also partnered with institutions in the U.S., Western Europe, Asia, and Ukraine to build research capacity in responsible AI.

That last partnership — the RAI for Ukraine Research Program — reflects Stoyanovich’s conviction that the responsible AI agenda must be global in both ambition and participation. Founded in the wake of Russia’s 2022 invasion, the program mentors Ukrainian undergraduate and graduate students in conducting responsible AI research, providing them with academic credit, stipends, and connections to a network of U.S. and European researchers. (That network now encompasses more than 70 mentors across 35 institutions in 12 countries.) Among the program’s most recent publications is a Nature study documenting the war’s impact on Ukrainian higher education—a testament to what international solidarity can achieve.

The Work Ahead

Whether Stoyanovich is testifying to city officials about algorithmic accountability, advising Ukrainian students building research careers amid war, or addressing the United Nations on the responsibilities of data stewards, her animating question remains constant: how do we build AI systems that extend human capability without diminishing what makes us human?

For her, that question is not merely rhetorical. It grounds a research program, informs a commitment to policy, and—as her recognition from City & State magazine reflects—shapes her ongoing contributions to the field and the world.