Philosophy Mondays: Human-AI Collaboration
Today's Philosophy Monday is an important interlude. I want to reveal that I have not been writing the posts in this series entirely by myself. Instead I have been working with Claude, not just for the graphic illustrations, but also for the text. My method has been to write a rough draft and then ask Claude for improvement suggestions. I will expand this collaboration to other intelligences going forward, including open source models such as Llama and DeepSeek. I will also explore other moda...
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Web3/Crypto: Why Bother?
One thing that keeps surprising me is how quite a few people see absolutely nothing redeeming in web3 (née crypto). Maybe this is their genuine belief. Maybe it is a reaction to the extreme boosterism of some proponents who present web3 as bringing about a libertarian nirvana. From early on I have tried to provide a more rounded perspective, pointing to both the good and the bad that can come from it as in my talks at the Blockstack Summits. Today, however, I want to attempt to provide a coge...
Philosophy Mondays: Human-AI Collaboration
Today's Philosophy Monday is an important interlude. I want to reveal that I have not been writing the posts in this series entirely by myself. Instead I have been working with Claude, not just for the graphic illustrations, but also for the text. My method has been to write a rough draft and then ask Claude for improvement suggestions. I will expand this collaboration to other intelligences going forward, including open source models such as Llama and DeepSeek. I will also explore other moda...
Intent-based Collaboration Environments
AI Native IDEs for Code, Engineering, Science
Web3/Crypto: Why Bother?
One thing that keeps surprising me is how quite a few people see absolutely nothing redeeming in web3 (née crypto). Maybe this is their genuine belief. Maybe it is a reaction to the extreme boosterism of some proponents who present web3 as bringing about a libertarian nirvana. From early on I have tried to provide a more rounded perspective, pointing to both the good and the bad that can come from it as in my talks at the Blockstack Summits. Today, however, I want to attempt to provide a coge...
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Went to see Horton Hears a Who with the kids, who had a blast. Afterwards we talked about things that you can’t see, can’t hear, can’t smell and yet exist (despite the kangaroo’s insistence to the contrary). This was great fun with the conversation ranging from bacteria to magnetic fields. But we did not touch on something even more profound simply because it is too abstract for the kids (and as I have come to realize, for most adults too): probability.
We live in a world in which randomness plays a huge factor. I should know, I met my wife in 1991 in a cafe in Paris in a completely chance encounter. Yet we humans have no way to observe probability directly. The best we can do is observe outcomes. This fundamental limitation leads to a lot of mistakes both in planning and in judging outcomes.
A great example of this are financial models for startups companies. I have seen a lot of these over the years and almost all of them (including some that I have been guilty of putting together) make the same mistake. They include a ton of detail but do not account at all for randomness. Sure there is usually a scenario switch to try out different sets of assumptions (pessimistic, base, optimistic), but for a given set of assumptions the model is completely deterministic.
Went to see Horton Hears a Who with the kids, who had a blast. Afterwards we talked about things that you can’t see, can’t hear, can’t smell and yet exist (despite the kangaroo’s insistence to the contrary). This was great fun with the conversation ranging from bacteria to magnetic fields. But we did not touch on something even more profound simply because it is too abstract for the kids (and as I have come to realize, for most adults too): probability.
We live in a world in which randomness plays a huge factor. I should know, I met my wife in 1991 in a cafe in Paris in a completely chance encounter. Yet we humans have no way to observe probability directly. The best we can do is observe outcomes. This fundamental limitation leads to a lot of mistakes both in planning and in judging outcomes.
A great example of this are financial models for startups companies. I have seen a lot of these over the years and almost all of them (including some that I have been guilty of putting together) make the same mistake. They include a ton of detail but do not account at all for randomness. Sure there is usually a scenario switch to try out different sets of assumptions (pessimistic, base, optimistic), but for a given set of assumptions the model is completely deterministic.
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