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Interview: Dan Goldstein on Decision Science

Decision Science News is a website about decision research in Psychology, Economics, Business, Medicine, Law & Computer Science. Dan Goldstein is the editor of Decision Science News.

What are the biggest misconceptions business and technology people have about the science of decision–making?
Dan Goldstein: Business people interpret decision making with two extreme views. One view is that optimal solutions exist and that expensive software can get a company closer to them. The other extreme is that the best intuitions come from the gut, without decision aids. Both views are misinformed.

The optimizers fail to realize that the space of problems that have optimal solutions is rather small, and that optimal solutions are easy for competitors to imitate. But tough problems have no optima.

What are the optimal acoustics for a concert hall? What's the optimal speed to drive to work? No one can say. The intuiters, in contrast, think that nothing beats instinct. This is long been proven wrong. In many domains, simple linear models (a basic form of decision aid) can outperform even the intuitions of experts.

Can you list some key decision science books for business managers to read, and explain why they are important?
Dan Goldstein:

  1. Rational Choice in an Uncertain World – Reid Hastie & Robyn Dawes – Yes, it’s a textbook, but it is the best introduction to the field
  2. The Black Swan – Nassim Taleb – To drive home the lesson that the world is less predictable than our models suggest
  3. How To Lie With Statistics – Darrell Huff –To help realize that “the data” are never univocal
  4. Gut Feelings: The Intelligence of the Unconscious – Gerd Gigerenzer – To learn when intuition works and doesn’t
  5. Meditations – Marcus Aurelius – To keep everything in perspective

Can technology design improve through the study of decision science, and if so how?
Dan Goldstein: I don’t know if decision science can improve technology design, but technology design could certainly improve decision making. Good decisions need knowledge, and knowledge has been, until recently, hard to come by.

Remember back in the 80s when we had to slug to the library, make photocopies, or spend the day on the phone to gather information? Now the internet connects us to information very quickly, but the problem is now the reverse, there's simply too much. What I see as a primary challenge for technologists is getting the right information to decision makers in the form that they need it. Google is the world champion at this, but there is a long way to go.

Google gives you rank–ordered search results, but it takes specialist sites to break information into fields that are useful. Right now you can’t ask Google to show you two bedroom apartments within 3 miles of the West Village with dishwashers (well you can, but don't expect much more than agency advertisements). However, if the world were tagged up properly, all manner of devices could return you the same tables of information you now have to pay for. But we can’t (and shouldn’t) expect people to tag everything up. An automated way to add metadata to the world would be darn useful to people making decisions.

Is there any software out there today you would consider outstanding in its implementation of decision science?
Dan Goldstein: Bill Sharpe, Eric Johnson and I have created a cognitively–friendly tool to help people express their preferences in a complex domain: that of investments. We grounded the tool in psychological principles. For example, instead of bombarding people with probabilities, we allow people to deal with simple counts, or frequencies. Instead of expressing these quantities with numbers, we express them graphically.

This allows people who don’t know the first thing about probability theory to communicate what sorts of risks they are willing to take by expressing them in a purely visual way. We have a paper on it, and think it could really change how investing is done.

What is one thing businesses can do today to improve decision making?
Dan Goldstein: Companies make lots of mistakes when it comes to hiring people. They tend to put too much weight on interviews and not enough on past performance. There are some in my field who recommend dispensing with interviews altogether. I have found over a number of years that simply testing people on the job they are to perform is a much better predictor than betting on their “promise,” yet amazingly few companies do this.

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