freedom from choice / is what you want*
by John at 4/26/2004 01:39:00 PM
An article in Scientific American discusses the penalty some people pay for being Maximizers as opposed to Satisficers. I can't actually read the article, because it is paid subscription only (my company library may have a copy, but I haven't wandered up there yet). However, there are some articles about the article on the web. This one, for instance, is from UPI.Maximizers, in short, try to optimize the decisions they make, to maximize (get it?) personal happiness, whatever that might mean for them. Satisficers, on the other hand, use a short cut optimization - they settle for good enough. The author's finding is the ironic result that Maximizers tend to be less happy than Satisficers, because they are likely to expend more energy worrying over their decisions than enjoying the decisions they make.
I think I am a Maximizer on the inside, but I act like a Satisficer because I am too lazy to put in the work required to be a real Maximizer. Additionally, there have been several times in my life when I decided that I was just better off not knowing much about what I was buying. E.g., I wanted an inexpensive scanner - not one review I read of any scanner was positive, so I was pre-dissatisfied with any choice I was likely to make. When I was in the market, I heard a similar thing being said about buying diamonds; the less you know about them, the happier you will be with your purchase. All in all, laziness and bad experiences have conspired to make me act like a Satisficer. I almost always pick the good enough choice, even if I have to spend a little extra time convincing myself that it's really the best thing to do. My guiding principle in consumer spending has come to be "buy the mid-priced item."
In my research right now I am doing some work with optimization. Bearing in mind that I'm not an expert on optimization, two problems I keep running into are 1) local minima, and 2) a flat objective function surface.
The first one is the easiest to describe - the optimization algorithm gets stuck in a valley surrounded by hills. It works hard to find the lowest point in that whole valley. The problem is that, in some direction, just over the hills is a valley with an even lower floor. The algorithm was unable to find the best solution, despite working very hard at it.
The second problem is a bit different. Instead of hills and valleys, the objective function surface looks like a mostly flat plain. The algorithm searches all over the place, but can't find a minimum that is significantly better than any other point. It learns eventually to settle on whatever low point it can find, and then runs into the problem of local minima. The difference this time is that there are a whole lot of solutions that look very different, but have essentially the same objective function value.
Where am I going with this? I think Maximizers face the same basic problem. They are either hindered by an inability to see all the options and are therefore likely to fail at their optimization task, or they are faced with a variety of options that are superficially different but are actually barely discernable. Both problems seems like they would be common occurences in our consumer culture. A Satisficer, happy to settle for good enough, avoids both problems.
If anyone can get a copy of the SciAm article, I'd like to see it. (Fair Use - educational purposes, or maybe criticism, comment, and news reporting?)
* "Freedom of Choice" by Devo.
