There are at least two systems of achieving productivity growth: path dependence and disruption. What if there is a third way? This post unpacks that paragraph and explores ways through. It will start with explaining lock in and path dependence. We’ll cover the application narrow machine intelligence in a very narrow industry. It will end with a small scenario and a few what ifs. Lock In Consider banner advertising. This is a relatively old industry. Its roots predate the Internet by at least a couple hundred years. It may have started thousands of years ago. It starts out with a person with a problem. They need to get the word out about their product or service. Reframed, they need to[…]

Torben Iversen and Anne Wren wrote (1998) “Equality, Employment, and Budgetary Restraint: The Trilemma of the Service Economy” and published it in World Politics, (50), 4, pp. 507-546. And it’s a good read. And you could read it for yourself right here. Here’s a summary in one image: What It Means What causes the Trilemma itself? It’s the idea that productivity doesn’t really grow in a pure local services economy. A restaurant can only serve so many meals, barber cut so many heads, a teacher so many students, a surgeon so many people, a police officer so many arrests. It’s far harder to get compounded year on year growth in productivity in services. As I’ll argue below, it isn’t impossible.[…]

There are many calls to break up tech. Break up what, exactly? Regulate tech? Regulate what? There’s a lot of polarization about what to do about Facebook, Amazon, Apple, and Google. That polarization is in part driven by anger. Dig a bit deeper and see fear. Maybe you’re feeling it. Here’s how I see it. The Assumptions People are heterogenous. Peoples’ beliefs are heterogenous. Peoples’ willingness to believe are heterogenous. Peoples’ inventiveness and imagination are heterogenous. Peoples’ willingness to tell or repeat stories are heterogenous. Peoples’ susceptibility to stories, and to storytellers, are heterogenous. Peoples’ need to belong are heterogenous. People form networks because they need to belong. Information (Gossip, facts, stories) is transmitted along those networks. These variables (information,[…]