Red Plenty

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It’s worth mentioning that this is a point which Trotsky got right.(I should perhaps write that “ even Trotsky sometimes got right”.)To repeat a quotation: I May Be Some Time: Ice and the English Imagination, 1996 - won literary prizes including the Sunday Times Young Writer of the Year Award, Writers Guild Award for Best Non-Fiction Book of the Year, and the Somerset Maugham Award in 1997. [5] We move to the bosses of the viscose factory, who secretly got their engineer to arrange the accident, as the original machine couldn't make enough viscose to fulfil the plan they'd been given.

It raises real political and philosophical issues that would have to be faced by any future socialist project, and draws attention to a forgotten history that today’s socialists ignore at their peril. Yet there had been a palpable transformation in the way Soviet citizens lived. In 1950, as in 1940 and 1930, they had been wearing hand-me-downs and living for the most part in squalid, crowded "communal flats" carved out of antiquated pre-revolutionary buildings. In 1950, you could be director of a major Moscow hospital and live behind a curtain in 1/17th of a Tsarist ballroom. Ten years later, Soviet citizens were wearing new clothes and moving in ever-increasing numbers into new apartments with private bathrooms; they owned radios and pianos and were beginning to own fridges and televisions too. In 1960, the hospital director would be sitting pretty in a sunny new-build out in the Sparrow Hills and driving to work in a well-waxed sedan with the leaping-stag logo of the Gaz company gleaming on its bonnet. Going by the measure of the capitalism of the 30s, which is what the Soviet Union had first set out to beat in terms of living standards, Soviet life was now spectacularly prosperous. The USSR could now feed, dress, house and educate its people better than depression America or Nazi Germany. If capitalism had remained unchanged, the Soviet Union would at this point have looked like a reasonable, if tyrannous and polluted, version of the earthly paradise. This is a book that should be read by anyone who is seriously interested in the possibility of a different sort of economy from the one we now have. It shows both the strengths, and the hidden weaknesses of the most serious attempt so far to construct an alternative to capitalism, an attempt that was born when the idea of a communist future was taken very seriously by a whole society. To read it is to be convinced that whatever the truth of standard leftist criticism of the USSR as being undemocratic and bureaucratic, there was much more than that at issue in this tragedy.The USSR's pioneering computer scientists were heavily involved, and so was the authentic genius Leonid Kantorovich, nearest Soviet counterpart to John Von Neumann and later to be the only ever Soviet winner of the Nobel prize for economics. Their thinking drew on the uncorrupted traditions of Soviet mathematics. While parts of it merely smuggled elements of rational pricing into the Soviet context, other parts were truly directed at outdoing market processes. The effort failed, of course, for reasons which are an irony-laminated comedy in themselves. The sumps of the command economy were dark and deep and not accessible to academics; Stalinist industrialisation had welded a set of incentives into place which clever software could not touch; the system was administered by rent-seeking gangsters; the mathematicians were relying (at two removes) on conventional neoclassical economics to characterise the market processes they were trying to simulate, and the neoclassicists may just be wrong about how capitalism works. The way computational complexity theory works is that it establishes some reasonable measure of the size of an instance of a problem, and then asks how much time is absolutely required to produce a solution. There can be several aspects of “size”; there are three natural ones for linear programming problems. One is the number of variables being optimized over, say n . The second is the number of constraints on the optimization, say m . The third is the amount of approximation we are willing to tolerate in a solution — we demand that it come within h of the optimum, and that if any constraints are violated it is also by no more than h . Presumably optimizing many variables ( n>> 1), subject to many constraints ( m >> 1 ), to a high degree of approximation ( h ~ 0), is going to take more time than optimizing a few variables ( n ~1), with a handful of constraints ( m ~ 1 ), and accepting a lot of slop ( h ~ 1). How much, exactly?

For a period, in the Soviet Union of the 1950s and 60s, there was a genuine and exhilarating belief not just that communism was morally preferable to capitalism, but that it could actually beat capitalism at its own game. There was even a moment, at least for those with the eyes to see it, when it looked as if that might just be beginning to happen. Spufford was a Royal Literary Fund fellow at Anglia Ruskin University from 2005 to 2007, and since 2008 has taught at Goldsmiths College in London on the MA in Creative and Life Writing there. In 2018 he was made a professor. [4] The author shows real skill as a science populariser, explaining such diverse topics as how the Pentode valve logic of the early BESM computers worked, to the molecular mechanics of the carcinogenesis mechanism that eventually killed its designer. He vividly portrays the enthusiasm and self confidence of the USSR in the late 50s when Khrushchev’s boasts that they would overtake the USA by 1980 and achieve communism seemed plausible. He gives a good didactic account both of the basic mechanisms of the Soviet Economy, and, through the lives of incidental characters paints a picture of its real operation that is more detailed and convincing than any academic history.Planning is certainly possible within limited domains — at least if we can get good data to the planners — and those limits will expand as computing power grows. But planning is only possible within those domains because making money gives firms (or firm-like entities) an objective function which is both unambiguous and blinkered. Planning for the whole economy would, under the most favorable possible assumptions, be intractable for the foreseeable future, and deciding on a plan runs into difficulties we have no idea how to solve. The sort of efficient planned economy dreamed of by the characters in Red Plenty is something we have no clue of how to bring about, even if we were willing to accept dictatorship to do so. Forcing each processor to take some account of what the others are doing, through prices and quantities in markets, removes some of the grosser pathologies. (If you’re a physicist, you think of this as weak coupling; ifyou’re a computer programmer, it’s a restricted interface.) But it won’t, in general, provide enough of a communication channel to actually compute the prices swiftly — at least not if we want one set of prices, available to all. Rob Axtell, in a really remarkable paper, shows that bilateral exchange can come within h of an equilibrium set of prices in a time proportional to n 2log(1/ h), which is much faster than any known centralized scheme. But there was a fatal paradox in this whole notion, one that Spufford brought out in a meeting between Kosygin and a leading reformer: how were these optimal prices to be calculated? The maths was well understood, but the technical problems of handling that much data with 1960s computers were vast. And if Gosplan could concentrate the information and could have done the computations, then the indicative prices would have been unneccessary - the whole process of calculation could have been done in-natura with the Objective Valuations only having a fleeting existence as coefficients within the matrices of the planning computers. Now, we might hope that yet faster algorithms will be found, ones which would, say, push the complexity down from cubic in n to merely linear. There are lower bounds on the complexity of optimization problems which suggest we could never hope to push it below that. No such algorithms are known to exist, and we don’t have any good reason to think that they do. We also have no reason to think that alternative computing methods would lead to such a speed-up 5.