What I'm reading now

• M150 Data, Computing and Information: Unit 5 Storing, getting and sending your data, OU.


• T173 Block 3 Patents: The engineer as innovator, OU.


• The Quark and the Jaguar: Adventures in the Simple and the Complex by Murray Gell-Mann.


• Sams Teach Yourself Java 6 in 21 Days by Rogers Cadenhead and Laura Lemay.


• Economics for Dummies by Sean Masaki.


• Four Laws That Drive the Universe by Peter Atkins.

I recently (and finally) finished reading Arthur Koestler’s The Sleepwalkers. It was referenced in The Black Swan by Nassim Nicholas Taleb.

Taleb said that Koestler highlighted how the idea that science has progressed in a straightforward fashion is wrong. Science has evolved through a series of sudden breakthroughs, and with much time wasted in intellectual dead-ends.

Taleb describes the most valuable property of the scientific method and the free market as “stochastic tinkering.” Having lots of people messing around with different ideas and business models increases your exposure to potential breakthroughs.

The idea that history is a series of clear and well defined developments inevitably leading to some outcome is a canard. History is a random and chaotic process.

Science and the free market are also random and chaotic. However it is precisely because of this randomness that science and the free market are so powerful.

Because the free market encourages new ideas and methods and allows successful ideas to achieve success at the expense of less successful ideas the ultimate outcome is a system that maximises the potential for good ideas to achieve widespread adoption.

Similarly with science. Good ideas succeed at the expense of bad ones. However in the scientific method the ideas are judged on the basis of the successful predictions they make, or the fact that they have yet to be disproved by experiment.

In the free market good ideas are judged on the basis of how profitable they are (theoretically).

Gell-Mann touches on many of the same ideas as Taleb, particularly regarding complexity and what Gell-Mann refers to as “complex adaptive systems.”