Northeastern University is set to host a free talk in Snell Library on Nov. 10, 2026, examining how artificial intelligence may spread as the next billion people begin to use it and what lessons the mobile phone boom offers for that transition. The event centers on the gap between premium AI products and the free, ad-supported versions that many new users are likely to encounter.
Key facts
- Jonathan Donner, senior director of research at Caribou Digital, is the featured speaker.
- The event is scheduled for Tuesday, Nov. 10, 2026, from 3:30 to 5:00 pm ET.
- The talk will take place at Snell Library at Northeastern University.
- Admission is free.
- Donner’s talk will focus on AI adoption, monetization pressures, and lessons from the mobile boom.
What does this mean for students and researchers?
For students, faculty, and researchers interested in digital inclusion, AI policy, and international development, the event offers a chance to hear how one researcher sees AI adoption playing out beyond the frontier-model market. Donner says many new users will likely access free or ad-supported AI tools, making questions about access, infrastructure, and monetization especially relevant.
The talk also connects current AI debates to earlier patterns in mobile-phone expansion, suggesting a practical frame for studying where adoption may accelerate and where it may stall. That makes it relevant to people working on technology policy, social research, and product design, especially those thinking about how builders, regulators, and practitioners can respond now.
Who is Jonathan Donner?
Jonathan Donner is senior director of research at Caribou Digital. His bio says he focuses on advancing digital inclusion in the developing world and has worked in industry, research, and development-sector roles, including positions at Microsoft Research in Bangalore, Columbia University’s Earth Institute, Harvard’s Berkman Klein Center, and Tufts University’s Fletcher School.
What will the talk cover?
Donner plans to discuss how AI adoption may unfold as more people come online, why monetized digital infrastructure often gets built first for people who can pay, and how users may adapt by appropriating, rationing, or working around what is available. He also intends to close with lessons for builders, regulators, and practitioners, along with the role human and social research can play.
Why compare AI with the mobile-phone boom?
The comparison is meant to highlight how widely used technologies can spread unevenly. Donner’s framing suggests that the most visible products are not always the ones most people use, and that adoption patterns can be shaped by price, infrastructure, and practical constraints as much as by technical capability.
