I’m a member of the Long Now Foundation, whose mission it is to “…provide a counterpoint to today’s accelerating culture and help make long-term thinking more common. We hope to foster responsibility in the framework of the next 10,000 years.”

One of their main activities is producing Seminars about Long Term Thinking, which are available as podcasts, and are my favourite listen on a long drive or trip to the supermarket.

The latest episode is Brian Christian on Algorithms to Live By, which covers recent developments in computer science. He spends much of the talk discussing the “Optimal Stopping Problem“, in which you try to determine the optimum time to stop looking for the ideal house, partner, or similar. It turns out there’s a mathematical answer to this question – if you determine how long you’re prepared to engage in the search process, then you should spend the first 37% (1/e) of the search period examining the choices, and then select the next option that is better than any of the previous choices. There are a significant number of other gems in this talk, but Christian’s parting shot really cracked me up.  According to Computer Science he says, we can rethink rationality in a mathematical way that includes the following principles:

• Don’t always consider all your options
• Don’t necessarily go for the option that seems best every time
• Make a mess on occasion
• Travel light
• Let things wait
• Trust your instincts and don’t think too long
• Relax
• Toss a coin

It leaves me tempted, for a few milliseconds anyway, to retake my Computer Science degree.

See the video at: http://longnow.org/seminars/02016/jun/20/algorithms-live/