August 3, 1930 was a Sunday with no Journal, so again a little editorial commentary.
The Idea Mortality Curve.
I'm not sure how many share this opinion, but one of the things I find interesting in this record of past news is the occasional glimpse of future technologies. Some of these were developed fairly soon after 1930, some many years later, and some are still mainly fevered dreams of money-burning would-be developers. I'm too lazy to look the dates up on these (if you're interested you can use the search box on the right of the blog web page), but some of the items I recall appearing so far in the blog are:
- Three-dimensional (stereoscopic) film.
- Tunnel under the English Channel (finally built 1988-94, financial disaster).
- Development of Alberta tar sands (first commercial development in 1960's, profitable as long as oil prices not too low).
- Processing of oil shale (not done on significant scale yet).
- Intelligent robots (depends on your definition, but most would agree the autonomous, intelligent robots envisioned then and now are still far away).
One interesting thing that jumps out is the wide variation in how long these things take to develop. And of course, today we see many similar reports on things like stem cells, nanotech, electric cars, and other future wonders or boondoggles of the world.
It may have occurred to you on reading some of these latter-day reports to wonder whether that breakthrough you just read about over your morning cereal is something that will be affecting your life or investments in the near future, or will be something your grandchildren will still be awaiting another 79 years from now. It would, of course, be nice to get a decent way of predicting that, but that may seem unlikely. After all, in most cases you don't know that much about the fields involved, and many of the factors affecting how long development takes are unpredictable even to experts in those fields; also, said experts often have a vested interest in making practical application of their research sound close, particularly if they need external money to continue it. (Thus, for example, articles describing even the most wildly impractical biological research usually open with a paragraph or two on possible important applications to human health, smoothly worded to deemphasize the disclaimers about how remote said applications might be).
I'd like to suggest to your attention a concept that I believe does help in estimating, for many different fields, how long it will take for a research development to have large scale practical application, and does so without requiring expert knowledge of the fields involved. I believe the concept was originated by the great Don Lancaster, and it's called the Idea Mortality Curve. Simply put, this concept says that in any field, there are a number of stages starting with Gleam in Eye (initial idea), and ending at large-scale commercialization, and at every stage but the first, a large proportion of the remaining ideas dies. Thus, the resulting graph of surviving ideas vs. stage winds up looking like an exponential decay curve. Note carefully that we're not talking about separating good ideas from bad here; all the ideas at the start of the curve are assumed to be good ones, but nevertheless each hurdle that must be passed to get from one stage to the next kills off a large proportion of the remaining ideas (or, as Lancaster puts it, the gotchas will git ya).
A consequence of this is that, to a good first approximation, you can say how far a piece of research in a particular field is from large scale commercial application simply by knowing what the Idea Mortality Curve looks like for that field, and what stage on the curve that piece of research is at. Once you have that, simply add at least a couple of years and a 50% probability of death for each additional stage to be reached. Of course, how fast an idea moves along the curve can be affected to some degree by how much effort and expense is being applied to move it along, and by luck or skill in finding solutions to hurdles along the way; but usually the biggest factor is the part in bold letters. Some particular examples of curves in different fields:
Drug discovery: Idea for compound to test (designed for a particular target or by screening); test for petri dish activity (single cells); test in animal models; small human trials for safety; larger trials for safety and effectiveness; long-term tracking for effectiveness vs. other drugs and to find less common and longer term side effects.
Car development: Initial idea; design and modelling; very expensive hand-production of small number of partially working prototypes (this stage can last for many years and generate many photo opportunities, ex. the hydrogen car); small scale production of a few hundred to a few thousand cars; large scale production of hundreds of thousands of cars.
New computer chip technology: Idea for new device design and/or material (ex. transistors using carbon nanotubes); test of individual devices; ability to make functional large-scale test chip with many devices (ex. large-scale memory chip); ability to make functional target chip (ex. CPU chip); ability to do so at reasonable cost (AKA good yields).