AI has begun to reshape every part of our digital experience. I keep coming back to Kranzberg’s first law of technology: “Technology is neither good nor bad;…
AI Is a Product of Humanity. Humanity Should Own AI.
Big Tech has looted humanity’s creative output to create artificial intelligence. We don’t just deserve a share of AI’s profits — we deserve control over it.
Something Big Is Happening
A personal note for non-tech friends and family on what AI is starting to change.
AI demands more engineering discipline. Not less
If you lived through the shift from handcrafted server pets to immutable infrastructure, you should sense something oddly familiar about what's happening now.
A Real Political Economy of Technology - The Ideas Letter
Two technological futures are competing for political and material priority: generative AI and the green transition. Benanav argues that while AI is marketed as a world-reordering breakthrough, its productivity gains…
The Arguments Against Open Source AI are Very Bad | Tom Bedor's Blog
The release of Kimi K3 has opened a fresh round of angst and confused discourse. There's a loud cohort of journalists, business leaders, and politicians arguing that open source AI is a dangerous threat. OpenAI's Dean Ball:
Mark Zuckerberg's AI manifesto is exactly why people don't like AI | TechCrunch
On Monday, Mark Zuckerberg published a 6,500-word manifesto about personal AI, largely about the possibilities for the "personal superintelligence" systems Meta AI is building.
AI, I tried to love you – Writings and rehearsals by Nathan Schneider
Among my peers who study the cultures and economies surrounding technology, I often find myself more tech-positive than most. On the whole I like computers, like the internet, and like in general the emergent human creativity that these things have enabled and revealed. A source of my appreciation is that I expend a lot of effort on the practice of “slow computing,” which is to say, choosing tools and technical communities that I can feel in right relationship with. I tend to approach new socio-technologies (like gig economies, blockchains, and social media) not from a perspective of why is this so bad? so much as asking how could we do this right?
Millions of Volunteers Are Keeping the Internet Human. For Now.
We’re never going back to the human internet we had. But we can hope for a better internet than the AI-dominated one that is emerging, writes Sarah Gilbert.
Resetting on engineering expectations in the age of AI
I’m accepting new sponsorships for The Modern Leader for 2026. If you’re interested (or you think your company may be interested), you can learn more here.
The Future Is Not Tech-Forward
On artificial intelligence, data centers, technological politics, and who gets to build the future.
</> htmx ~ Yes, and...
In this essay, Carson Gross discusses his advice to young people interested in computer science worried about the future given the advancements in AI.
The machines are fine. I'm worried about us.
On AI agents, grunt work, and the part of science that isn't replaceable.
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
Andrew Ng: The Biggest Opportunities in AI Aren't Where You Think
AI as Normal Technology
The normal technology frame is about the relationship between technology and society. It rejects technological determinism, especially the notion of AI itself as an agent in determining its future. It is guided by lessons from past technological revolutions, such as the slow and uncertain nature of technology adoption and diffusion. It also emphasizes continuity between the past and the future trajectory of AI in terms of societal impact and the role of institutions in shaping this trajectory.
Field Theory: AI as Social Science Question, Object & Tool
Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.