I've been coming across and reading a fair amount of material on the rise of data-driven decision making lately.
In fact, Monday's expert quiz was taken from an FT.com article on the subject, entitled, "How computers routed the experts".
Whether by accident or design, I seem to be stumbling on one piece after another on the subject, as well as some analysis on expert performance.
I thought it might be a good idea to put all of these items into one post, and allow you, the reader, to sort them out. But first, a few words about our latest theme, the expert vs. the machine.
Over at EconLog, Arnold Kling mentions that he is currently reading through Ian Ayres' new book, Supercrunchers.
The book's focus is the rise of statistical decision making, and Kling quotes a relevant passage from an early part of the book to establish this idea's importance.
"We are in a historic moment of horse-versus-locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching."
If you happened to read through the beginning of Michael Mauboussin's essay on expert performance (found in Wednesday's post, "Becoming an expert"), then you'll no doubt recognize the parallels between the essay and Ayres' book.
To illustrate their discussions of data-driven analysis, both writers decided to cite the example of ongoing changes in the field of medicine. Due to advances in medical technology and the advent of the "Super Crunching revolution", doctors now find themselves pitting their judgement (or, diagnosis) against the analysis of a machine.
According to the authors, this type of decision making battle will increasingly play out over the coming years, with the traditional experts and prognosticators pitting their judgement against the findings of data-crunching computers. This conflict will be present in any number of areas in our daily lives.
We already see the onset of this theme in the areas of investing and market speculation. As we noted back in our May 25th "Features", the rise of scientific and quantitative investing is made apparent by the success of James Simons' Renaissance Technologies fund, and the increased adoption of computer-driven trading and artificial intelligence programming.
But will computers be able to successfully mimic or replace human judgement and decision making?
As The Financial Philosoper recently noted, investors seem to forget that computers offer help with strategies and organizing data, but they cannot replace our judgement or learn from accumulated wisdom.
At least not yet...
In fact, Monday's expert quiz was taken from an FT.com article on the subject, entitled, "How computers routed the experts".
Whether by accident or design, I seem to be stumbling on one piece after another on the subject, as well as some analysis on expert performance.
I thought it might be a good idea to put all of these items into one post, and allow you, the reader, to sort them out. But first, a few words about our latest theme, the expert vs. the machine.
Over at EconLog, Arnold Kling mentions that he is currently reading through Ian Ayres' new book, Supercrunchers.
The book's focus is the rise of statistical decision making, and Kling quotes a relevant passage from an early part of the book to establish this idea's importance.
"We are in a historic moment of horse-versus-locomotive competition, where intuitive and experiential expertise is losing out time and time again to number crunching."
If you happened to read through the beginning of Michael Mauboussin's essay on expert performance (found in Wednesday's post, "Becoming an expert"), then you'll no doubt recognize the parallels between the essay and Ayres' book.
To illustrate their discussions of data-driven analysis, both writers decided to cite the example of ongoing changes in the field of medicine. Due to advances in medical technology and the advent of the "Super Crunching revolution", doctors now find themselves pitting their judgement (or, diagnosis) against the analysis of a machine.
According to the authors, this type of decision making battle will increasingly play out over the coming years, with the traditional experts and prognosticators pitting their judgement against the findings of data-crunching computers. This conflict will be present in any number of areas in our daily lives.
We already see the onset of this theme in the areas of investing and market speculation. As we noted back in our May 25th "Features", the rise of scientific and quantitative investing is made apparent by the success of James Simons' Renaissance Technologies fund, and the increased adoption of computer-driven trading and artificial intelligence programming.
But will computers be able to successfully mimic or replace human judgement and decision making?
As The Financial Philosoper recently noted, investors seem to forget that computers offer help with strategies and organizing data, but they cannot replace our judgement or learn from accumulated wisdom.
At least not yet...