Mission Log

A recent Devex article raises a question that deserves a serious answer: when a frontier AI company partners with a developing nation, what does genuine capacity building actually require? Anthropic's engagement in Rwanda has been framed as an investment in AI talent and infrastructure. Rwanda has positioned itself as a continental tech leader, with strong digital governance ambitions and a track record of coordinated, state-led development. On the surface, this looks like s

We just finished Karen Hao's Empire of AI. For a company dedicated to helping nonprofits use technology for good, the book landed HARD. Hao documents how a nonprofit founded to "benefit humanity" became one of the most strategically important companies in the world. The transformation wasn't driven by bad intentions. It was driven by the logic of scale. From nonprofit to $90 billion valuation in eight years OpenAI began in 2015 with commitments to openness and shared benefit.

Between Us and the Machine | Episode 2 There's a number that's hard to accept. In 2004, the average person could focus on a screen for about 150 seconds. By 2021, that had dropped to somewhere between 44 and 50 seconds. That's not distraction. That's structural change and it happened without most of us noticing, let alone consenting to it. This is what Episode 2 is about. Not just what's happening to our attention, but who's responsible, who benefits, and whether we have a r

Your staff are already using AI to draft, analyze, code, and iterate. The data shows clear patterns in how adoption spreads and where productivity shifts first. Institutions that map those patterns early gain control over workflow design, accountability, and infrastructure strategy. We help organizations turn real AI usage into deliberate governance and structural advantage.

When Anthropic's safety lead resigned and published an open letter describing a world in peril, it landed differently depending on the room you were in. Some froze. Others accelerated. In Episode 1, Juliet and Margot set the stage for a series built around that tension — who's deciding, who benefits, and what it actually takes to build AI that serves people rather than the other way around.

When we call automated systems "intelligent" or say they "learn" and "understand," we're not just being imprecise. We're shifting responsibility from the people who build and deploy these systems to the machines themselves. This research paper by Nanna Inie, Peter Zukerman, and Emily M. Bender provides the first systematic taxonomy of how we anthropomorphize AI and concrete strategies for changing that language to make power and accountability visible. Eight ways we anthropo

Why Mission AI is sharing this Mission AI is sharing this OHCHR issue brief because it translates human rights principles into operational governance for digital systems that rely on data and AI. The document provides concrete guidance for institutions using data-intensive technologies at scale. It treats human rights as something that must be embedded into processes, decision points, and accountability structures across the full technology lifecycle. This approach aligns wit

Why Mission AI is sharing this Mission AI is sharing this publication because it shows what serious AI governance looks like inside a global public-interest institution. The World Food Programme’s framework translates responsibility into operational structure. It treats AI as something that shapes decisions at scale and therefore requires continuous oversight, clear authority, and institutional accountability. We see this work as a necessary foundation for broader governance