In the course of working with some of Endeca’s more interesting clients, I started reading up on how the intelligence agencies address the challenges of making decisions, especially in the face of incomplete and contradictory evidence. I ran into a book called Psychology of Intelligence Analysis by former CIA analyst Richards Heuer. The entire book is available online, or you can hunt down a hard copy of the out-of-print book from your favorite used book seller.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don’t always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you’re already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar–especially the third of the book that enumerates cognitive biases. I’m a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I’m very sensitive to how people’s cognitive biases affect their ability to use these tools effectively. One of the HCIR ’07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer’s decision process.
It may be tempting for us on the software side to wash our hands of our users’ cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.