X-Message-Number: 13317 From: Date: Sun, 27 Feb 2000 10:58:48 EST Subject: probability, religion,research This stuff is being recycled ad nauseam, but we always have the newcomers to consider, as well as those whose memories need refreshing. So once more into the breach. Very roughly, there is a pro-cryonics camp holding that, while use of present resources for cryobiological research is important, it is not important to the exclusion of other immediate goals. Then there is a semi-pro-cryonics camp holding that most current resources should go into cryobiological research, often saying or implying that cryopreservation by past or current methods is nearly hopeless. Some of these people, at least some of the time, heap scorn on "blissfully ignorant optimists" and even stigmatize optimism about nanotechnology as "religion." Today Thomas Donaldson used the "R" word again, even though he is closer to being pro than semi-pro. Today's reminder is about the foundations of probability theory, concerning which most people, including most mathematicians, are amazingly ignorant. On our web site I have a long discussion of probability and cryonics, which of course will be persuasive to few, but nevertheless is available to anyone who is serious about these issues. The basic premise of probability theory is that what we see is (probably) typical of what we don't see. The sample is typical of the population. There is no alternative. Larger samples reduce the uncertainty, but the uncertainty is always present; yet as long as there is a sample, ignorance is not total. It is also essential to understand that uncertainty is in the beholder, not the world. (I omit a long digression into quantum uncertainties.) The probability of an event is the RECORDED ratio of successes to trials in a FINITE sequence of reasonably well defined experiments. (I omit a long digression into probabilities of probabilities, or second-order probabilities.) A crucial point is that the experiments in the sequence are never perfectly defined, and probabilities are never exact. Yet the theory applies equally to a long series of well defined experiments and to a short series of vaguely defined experiments. In the latter case the results are less precise and less reliable, but no different in kind. So: Consider two extreme cases. 1. Toss a coin. The known sequence is very long (even though not recorded in any one database), and the experiment is rather well defined (even though, if someone wanted to, he could train himself to bias the toss). So we get high precision and reliability; the probability of getting heads on the next toss is , plus or minus a very small number. Important note: The same reasoning would apply to any symmetrical body and any random shove, even in the total absence of directly relevant history. It would apply, say, to the toss of a 12-sided die, even if such a thing had never existed before. We MUST acknowedge the validity of CATEGORIES of experiments. 2. Guess the future of nanotechnology. Here the sequence of experiments is poorly defined, but not vacuous. It could be assigned, for example, to the category of experiments, "Development of Modern Technologies." Very vague and amorphous, but NOT vacuous. Now one could assemble statistics in many ways. For example, one could ask, how often, in the early stages of a technology, have optimists and pessimists made predictions, and how often have each been right at later stages? Many variations are possible, but history tells us that, in most cases, the progress surprises the pessimists. Progress as to goals or ends, that is; it is not unusual for particular means to fail. Yet again, the big picture is often the only useful one in the longer run. In the early days of speculation about rocketry, pessimism was almost totally widespread among "experts" and based on their intimate knowledge of the difficulties in the details. Optimism among experts was based on fundamentals, with details left for later. Optimism among amateurs was based on supposedly na ve recognition of the inexorable advance of technology; but in fact this alleged naivete was at bottom a thoroughly scientific recognition of the sweep of history, or the application of probability theory to areas usually ignored. Now, what about the research priority? It isn't necessary to choose (say) between research and recruitment. Each organization, and each individual, can and will make particular allocations. CI does both. But if we want to look at trade-offs, it may be slightly helpful to make an analogy with startup tech companies. What should they go for-early profit or growth? A case can be made either way, or for a hybrid, but usually they go for growth, on the theory that early growth will be most advantageous for later profit. Many critics scorn companies that accept large current losses to gain customers-but in many cases there is no other way. One writer recently pointed out that the Chrysler minivan line, now hugely profitable, started out for years as a loser, with large investments by the company and very small sales. If the minivans had been a separate company, the criticism would have been deafening, but buried inside Chrysler it was just a small divisional experiment, which had resounding success. Analogies are unreliable, of course, and the discussion could-and doubtless will-go on at great length. I only want readers, especially newcomers, to realize that few things are simple, and in particular that a reasonable degree of confidence in nanotech does not deserve the R word. Robert Ettinger Cryonics Institute Immortalist Society http://www.cryonics.org Rate This Message: http://www.cryonet.org/cgi-bin/rate.cgi?msg=13317