This whitepaper is a codification of a decade of learning. Not as a definitive model, but as one approach that has been useful for us in practice. It includes what we’ve found to work well, where we’ve struggled, and the kinds of tools and structures we’ve used to support an inquiry-driven orientation in grantmaking.
Your average computer science major seems to now be the poster child for Gen Z college grads unable to secure the sort of jobs that a decade of “top majors” features promised them. CS has until recently been assumed to be a “safe” major that guaranteed employment, often with a high starting salary in a perks-laden workplace, or equity in a fast-growing startup. A decline in demand for recent graduates has led to headlines suggesting the boom is over, and that AI poses an existential threat to all computer science occupations.
Shifting those narratives isn’t just a communications challenge; it’s a question of power. Across regions and sectors, participants described rural places as sites of tech-driven innovation, experimentation, and deep practical knowledge. What is missing is not ingenuity, but the infrastructure, capital, and power of rural leaders to shape how technology shows up in their communities, and how that work is perceived.
Today we’re announcing a partnership with ImpactAlpha to support their Shape the Algorithm beat. The conversation around AI is moving fast. Every day, headlines remind us that the choices we make in technology—what gets built, how it’s governed, who benefits—matter. We’ve long believed that supporting public interest technology and engaging in the future of philanthropy isn’t just about grants. It’s about building the ecosystem that lets good ideas take root, scale, and adapt: capital, governance, knowledge, and strategy.
In our work—with grantees, through firsthand observation, and in the stories we intentionally seek—we’ve witnessed the power of technological innovation in rural communities. It takes many forms across the country, often without a data center in sight. Yet these stories rarely break through mainstream narratives, reinforcing a persistent misconception: that meaningful innovation happens elsewhere.
Data centers are rapidly sprouting across America, with technology companies spending billions to build thousands of facilities nationwide. Rural areas in particular have seen a surge in development as companies seek cheaper land and generous local tax incentives. Many see the trend as providing an entry point into the growing AI sector for communities outside traditional urban centers, with proponents arguing that data centers represent a “new savior” for regions in need of much-needed tax revenue and high-paying jobs. But proponents are missing one key issue: Data center jobs are not AI jobs.
With support from the Siegel Family Endowment, the newly renamed MIT Siegel Family Quest for Intelligence investigates how brains produce intelligence and how it can be replicated to solve problems.
The MIT Quest for Intelligence has been renamed the MIT Siegel Family Quest for Intelligence in recognition of support from David Siegel. SQI’s goal is to understand intelligence — how brains produce it and how it can be replicated in artificial systems to address real-world problems that exceed the capabilities of current AI technologies.
In every era of rapid technological change, there come moments of deliberation: wait for policy or lead through practice?
As we reflect on the past year, it’s clear that artificial intelligence has dominated discussions across various domains. What surprises us, however, is not the volume of conversation but rather its lack of nuance. Having navigated many cycles of technological development, we recognize the urgent need to move beyond the simplistic “gloom vs. doom” narrative. Instead, we must critically examine what these technologies can do, what they cannot, and—most importantly—what we truly need from them.
Read new Siegel In-House Research Fellow Symon Campbell’s latest publication in Journal of Integrated Global STEM analyzing three K-12 Black-oriented EdTech platforms developed by Black women—KaiXR, Reconstruction, and TunTimo—leverage public interest technology principles to address educational inequities and counter racial biases in mainstream EdTech.