In the past, intellectual debt has been confined to a few areas amenable to trial-and-error discovery, such as medicine. But that may be changing, as new techniques in artificial intelligence—specifically, machine learning—increase our collective intellectual credit line. Machine-learning systems work by identifying patterns in oceans of data…. And yet, most machine-learning systems don’t uncover causal mechanisms. They are statistical-correlation engines. They can’t explain why they think some patients are more likely to die, because they don’t “think” in any colloquial sense of the word—they only answer. As we begin to integrate their insights into our lives, we will, collectively, begin to rack up more and more intellectual debt.Jonathan Zittrain – The Hidden Costs of Automated Thinking
We think of AI (artificial intelligence) as being digital, silicon-based; a computer program. But that’s not entirely true. Algorithms don’t have to be written in C or Python. Computers are the most efficient way to run algorithms, but they’re not the only ones…
Capitalism, as a weak AI, is built upon an unbearable abstraction — namely, the reduction of all value of problem-solving to a single criteria: the increasing of shareholder value. That is literally the only metric for success in capitalism. And therefore, to capitalism, anything that does not achieve that goal is either irrelevant or an impediment. That includes every other aspect of existence. Human happiness is not a metric of success for capitalism, or ecological diversity, or even the survival of life.
Preparing for a world without work means grappling with the roles work plays in society, and finding potential substitutes. First and foremost, we rely on work to distribute purchasing power: to give us the dough to buy our bread. Eventually, in our distant Star Trek future, we might get rid of money and prices altogether, as soaring productivity allows society to provide people with all they need at near-zero cost.