دانلود رایگان مقاله الگوریتم ها و زندگی روزمره

Algorithms to Live By by Brian Christian and Tom Griffiths is a book written for a general audience about a number of ideas in computer science and how they are applied in practice. Despite the widespread interest in all things related to computers, very few such books have been written, and I know of no others that cover the particular subjects included here. The book gives clear, almost entirely math-free, accounts of the ideas; narrates their historical development, enlivened with many personal anecdotes1; and describes a variety of applications. The applications fall into three categories. First, there are applications within computer technology itself; unsurprisingly, these form the majority of the applications discussed in the book. Second, there are applications in commercial or institutional settings; for instance, there is a fascinating discussion of techniques for testing new medical treatments which balance the need for control groups in reliable experiments against the problems involved in denying control subjects the new treatments that they need. Finally, there are applications that are presented as solutions to everyday problems that arise for the man on the street. These last seem to me the least successful aspect of the book. A few seem interesting, such as deliberately introducing random elements into projects you are working on. Most of them I find unconvincing, and a couple, which I will discuss below, seem to me completely crazy. Finally, the authors argue that there is reason to believe that people in any case naturally use these kinds of ideas in their ordinary thinking and action. Some of this seems to me reasonable; much of it seems to me overstated. I will discuss this in section 4. The authors’ view of their own work is very different. As the book title indicates, they consider that the central point of the book is precisely the application of computer science to everyday problems. Moreover, Christian and Griffiths claim optimistically that “looking through the lens of computer science can teach us about the nature of the human mind, the meaning of rationality, and the oldest question of all: how to live.” I agree that the ideas are somewhat relevant to the meaning of rationality and to the question of how to act sensibly in various situations (“how to live” is a rhetorical exaggeration). However, I am skeptical that the ideas are very helpful in understanding the nature of the human mind; the problems that they address are a small and rather eccentric selection of the tasks faced by human cognition.

4. Psychological theories

Griffiths is, professionally, a cognitive psychologist and the book contains a substantial discussion of the analysis of human cognition in algorithmic terms. Some of this material I found quite fascinating, even exciting. For instance they discuss a remarkable experiment by Jackson Tolins and Jean Fox Tree that showed that speakers telling a dramatic story to a listener rely on receiving a steady stream of so-called “back-channels” — “uh huh”, “yup”, “sure” etc. — and that if they don’t get it, they may be unable to tell the story properly. However, I disagree with a lot of the psychological discussion here. At this time, cognitive psychologists tend to be divided into two camps. The scientists in the first camp argue that most aspects of human cognition can be understood as rational, perhaps even optimal, when set in their proper context. The scientists in the second camp take the more commonsensical view that human cognitive processes are astonishing in many ways, but often suboptimal or irrational judged against mathematically normative standards. In other words, humans unlike Vulcans make lots of quite unnecessary mistakes. Griffiths is a prominent member of the first camp; I myself am largely in the second camp. Accordingly the book contains many arguments that purport to show that seeming failings in human cognition are actually rational once everything has been taken into account or they are inevitable consequences of following algorithms that are actually provably optimal or at least reasonable. For example: Christian and Griffiths argue that sometimes having trouble remembering things is inevitable if you have a lot of things to remember, and older people forget more things, not because their memory is failing, but because they know so much.