Interdependence, not innovation

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This month has been about the future, and how we might make it differently. I wrote an essay on the power of utopian thinking, and shared a conversation with Professor Shannon Vallor that — among other valuable nuggets — offered two new premises for imagining the future: 1) start with outcomes and values, and think backward, 2) technology should enhance our humanness, not help us escape from it. Today’s issue offers a third: our imagined futures should center our interdependence with one another, and technology. Let’s dig in.

🔗 First, Some Links

• A summary of research finds that AI still doesn’t exhibit ‘emergent properties.’

• The New Yorker surveys two books — Shannon Vallor’s The AI Mirror and AI Snake Oil by Arvind Narayanan and Sayash Kapoor — to answer the question: what can humans do that AI cannot?

• Yet another research paper finds that training AI systems on synthetic data leads to model collapse.

• A new paper interrogates the limitations of AI agents. The underlying issue? Benchmarks!

Interdependence, not innovation

Interdependence is the idea that we all have needs, and we can’t meet those needs entirely on our own. Did you have a negative reaction to that premise? You’re probably American! Interdependence doesn’t exactly square with rugged individualism. Anyway, interdependence is central to understanding any complex sociotechnical system. As systems theorist Brenda Zimmerman once said, “The most important unit of analysis in a system is not the part (e.g. individual, organization, or institution), it’s the relationship between the parts.” If we can change the relationship between the parts, we can change the system. But that requires first identifying the relationship between the parts— between people, between people and technology, between people and power — and interrogating how these elements interrelate. It requires the lens of interdependence.