Okay so good morning to everybody thank you for being here with us this is the fourth event organized by mark science and technology study group a group affiliated to CNC studio Philosophical Association we would like to think as well the Institute of Advanced Studies of University of San Paolo without which we couldn't have organized these in the other events for today's lecture we are pleased to have with us dr. pol Cockshott who is a retired reader at University of Glasgow in this cutland he's a computer scientist and a political economist who has worked in the
field of computer science on variety of topics from 3d imaging to the theoretical discussions about the limits of computability and in political economy he has advocated the use of modern computers and its algorithm techniques to think and help to shape the other models for measuring economic Value having as a main reference the debates around socialist calculation in Soviet Union and the opposition of economies like von Mises and Hayek towards the socialist approach to economics before starting we have just to explain a little bit the structure of this lecture the first part Paul will expose his
ideas in English and in the second part unfortunately without though we are going to keep discussing his ideas in Portuguese ok and so thank you Very much Paul cockshott for being with us today ok I probably can stay on for a bit little bit of the discussion that's better ok can you see my screen ok yes I can see you can see my screen and have a look ok so I'm gonna be talking about a formal algorithmic approach to the surface calculation problem what's the historical background to this well it starts off with for me
with the Work of Professor knew who was headed sorry for you hear me just a second it's good if you just let your a screen like your slide showing because yeah I'm not sure how I can get rid of this hole if I move that down it's not any better yes move it right across to here that's probably good there the trouble is that Skype shows what shows me what you're seeing at the same time yeah no I think okay I think okay That the professor nerve was the head of Soviet studies at Glasgow University
and in the 80s he published a book called towards a feasible socialism which how does its main theme that the idea of systemic economic planning was a mistake and that you had to have market socialism if you're gonna have any kind of socialism and this was quite influential within the Labour Party in Britain with the then leader of the Labour Party using it as a justification For dropping the long term party program of nationalizing industry he explicitly used it as a justification in a speech I listened to him give shortly after he became head of
the Labour Party and I thought you know this is wrong it should be possible to show on computational grounds that know if it's wrong in the long term the context of it is the work of the Austrian capital theorists von Mises and Hayek led the critique of my Raths idea of a Planned economy operating in kind and the current relevance of it was that from the late 80s Early 90s Hayekian approaches were applied to the Eastern European economies and these led to actually a complete collapse of production and a drastic fall in living standards and
life expectancy so the the effects were not what were promised so how did computers fit into this well starting with von Mises the conservative economists argued that effective social Spanning was impossible for two reasons one Mises said there was no effective cost metric in the absence of a market so you couldn't tell what was the most efficient way of carrying out a production process if you couldn't apply prices to the ingredients which went into the production process secondly he said that if this is more an argument that Hayek made the the there would be millions
of equations to solve in order to work out what the optimal use of Resources was and this is impractical to solve millions of equations well computers have obviously changed this in that they can induce of millions of equations if you listen to the weather forecast you're listening to the results of computer solving many millions of equations but we need to be quite precise about this and say how many million equations are you going to need and just how hard are they to solve and this is a branch of computer science Known as complexity theory and
we said the complexity of an algorithm is measured in terms of how the number of instructions used to compute it grows as the size of the problem grows you need some basic unit of the size of the problem and then you say of the insides of the input data and then you say how long is it going to take as a function of that and I'm gonna give her a simple example first an intuitive example suppose I've got a Phone directory for a some city in Brazil and I am given somebody's phone number I'm given
the number not their name in principle I could look through all the name number pairs in the phone directory until I find who the number belongs to so it's it's in principle a feasible task to do but it will take many days to do that and would be error-prone you might miss the number if on the other hand I'm given someone's name and I have an old-fashioned paper Telephone directory which was a sorted book sorted by alphabetical order I could find someone's name in less than 60 seconds this is because if you've got sorted data
the complexity of looking something up is order log n unsorted data it's of order n when we say something's of order n it means you'll take roughly n attempts before you find the name so you on average you'd have to look at half the numbers before you found someone snap name if you're doing It with a sorted list though you you go and look in the middle of the list and if the name is off vertically before that you go and look a quarter of the way through the list etc and it can be shown
that that takes of the order log n steps to find it out now login problems are the best sort of problems from a computing point of view because suppose I have two to two directories of two sorted lists if one's got a thousand Entries and the others got a million entries if I'm looking at the names from the numbers it would take a thousand times as long to look it up in the million entry table but it would only take twice as long for a sorted table so sorting is something which is used a very
extensively in computer databases because it enables you to change something from an intractable problem to attractive problem now let's look at the economic planning problem this is more Complicated than just a list because the basic data structure you're dealing with is is an input-output table I'm showing an input-output table and the standard format that you would get if you go and look at the Brazilian input-output table you have industry headings here and this would say how much rubber is used in the rubber industry how much rubber is used in the steel industry etc this line
says how much steel is used in the rubber industry hammers steel the steel Industry how much still in the oil industry in principle you can construct these tables using natural units so you could measure them in tons or kilograms most countries don't do that they published them in monetary units but that doesn't fundamentally alter the problem now I've given an input-output table and you can compute how much of each intermediate product is required to produce a given amount of the final product and in particular you can Compute the labor content direct an indirect labor content
to be channeled from low data in an input-output table now this is Marie famous equation for labor values suppose you have ten million different types of goods no said there are ten million different types of goods in the Soviet economy the labor content or labor value vector is given by Murray Sheila's equation labor value is a which is a technology matrix which is Equipment the input-output table times labor values plus the direct labor input vector now that's a standard set of linear equations or a matrix equation and it's in principle solvable by inverting the matrix
but it's for a real economy clearly it's too big to invert the matrix is even too big to store in the computer because if you have ten million different types of products you the table a is 10 million by 10 million which is 10 to the 7 by 10 to the 7 so It would have 10 to the 14 cells and you would need a computer with a memory size of 10 to the 14 words which is prohibitively large and the standard method of computing a matrix inverse or using Gaussian elimination to solve the problem
whilst it's tractable for small numbers of industries for a thousand products for example I assume --it one thousand products using Gaussian elimination which is the standard method of solving Linear equations you can obtain labor values by performing ten to the nine multiplications which on a modern processor you could easily do that in ten seconds less than ten seconds probably but as you increase the number of products then the amount of time grows rapidly in seconds so it's 10 to the 7 seconds 400,000 products for the 10 million products is 10 to the 13 seconds and
even if we use a highly parallel computer it's going to take us 3,000 years and this is presumably the kind of argument that nove used when he said it would take thousands of years to completely compute an economic plan for the Soviet Union and therefore even with computers the Mises argument is right but there are simplifications very big simplifications firstly the matrix is sparse most elements are 0 and you can represent it by a much more efficient data structure in a computer in our book published in the early 90s we said that We estimated the
number of inputs used by an average product in the economy will be tend to be of the order of the logarithm of the number of products in the economy now that was an intuitive guess subsequently one of my PhD students did empirical research into into successively disaggregated versions of the United States input/output table this logarithmic law does hold or in fact is slightly better than the logarithmic law but it grows more slowly Now if you have this kind of logarithmic Li growing data structure and you use instead of using Gaussian elimination you use the Jacobi
method for solving equations which is an iterative method the complexity becomes of the order n log n in the number of products and that means you could for an economy the size of the Soviet economy compute the labor value of all products in a few minutes with the modern computer so the huge difference between a few minutes and 3000 years in general each production process would be represented as a list of pairs and saying it used a particular product code and a particular quantity of it a list of such the pairs like that on an
average process you'd expect something like a hundred cells rather than ten million cells to represent it and therefore the whole thing can be loaded into a computer's memory because of the huge saving in memory also you don't need an exact solution you only Need a solution to about three significant figures doing this experimental e on experimental test data we I find that you can solve it adequately in ten iterations you get three significant figures so for a ten million product economy on a contemporary high-end process PC processor and an X high-end x86 64 bit processor
you would take about six hundred seconds to compute the labor values now it has to be said that the Power of a contemporary 64-bit PC processor is considerably in excess of anything that was available to the Soviet Union in the 1970s or 80s so they couldn't have done it to the bat speed if you use a modestly parallel processor with 100 cores you could probably cut get that down to six the problem is such that it lends itself very well to parallelization I haven't yet written a parallel version of the code but I may do
that at this point I'm Just gonna illustrate a package which I've released on github for doing planning using the mathematical techniques that were available in the Soviet Union can torvik searches techniques now let me see is that visible to people was it too small I can't tell you I'm just gonna go ahead since I that that's too small for me to see okay it's too small okay for me to blow this up unfortunately it's it's I had to write a Text window let me see whether I can know it is insistence okay just bear with
me momentarily I will first show you the data that I'm putting into a planning program here here is a little tiny economy with an input-output table I've got products naught 2 3 I've got a labor row I've got an output row okay this is as a CSV file which the standard spreadsheet file format because you can take you could take the input output table for the Brazilian economy and get The Microsoft spreadsheet to save it as a CSV file with a little bit of editing you'd be able to feed it into the software you also
would need data on the capital stock of each type required by each industry which is slightly harder to get hold of from standard input output Atlas this is data which the Soviet Union had access to you have to infer it if you're going to work with real data published in Western countries now if I want to plan that what I'm Doing is I specify the outputs I want in future years and I then run a program for it if I became an example of running it here you get an indication of the time it takes
to run it it's not it's not a it's not creating a new economy which is what my error message there so that's easy for for industries for three years and it took me half a second the computer plan using the algorithms that kantorovich was using in the Soviet Union That's quite tractable but kantorovich is algorithms have the same problem that the Gaussian elimination has and I will illustrate what the implications of that in due course if you have however been a lot of changes since the Soviets tried to use their computer technology to deal with
it on the one hand we have the Internet which makes the concentration of data much easier continue okay sorry this is this has gone to the wrong place again okay the the Internet makes the Concentration of dispersed data which goes into Hayek is one of the big problems of planning much easier big data from giant databases exist we have supercomputers which are obviously far beyond the scale of computation that I'm talking about just with a an individual PC so there are computer centers of the sort I'm showing up here with with thousands and thousands of
rack to pcs in them linked to do solve problems in parallel we also Have the ability to get rid of cash by electronic payment cards which didn't exist in the Soviet Union so the Internet allows real-time cybernetic problem solving ix dispersed planning problem big data allows the concentration of the information needed for planning supercomputers can solve the millions of equations in seconds and electronic car payment cards allow the replacement of cash with non-transferable labor credits which is What Marx was proposing now the the model that we have presented in our book for the essential features
of cyber communism are on one hand direct democracy on the other hand an equivalence economy major decisions will be taking democratically such as how much to labor to devote to education to pensions the sick environmental protection defense investment and this can be done by direct voting using computers or mobile phones every year so The whole population can vote on these issues the second aspect is the is what Heinz Dietrich calls the equivalence economy marxist principle non public goods are distributed on the equivalence principle you get back in goods the same amount of labour after-tax if
you perform so goods are priced in labor hours and you have cybernetic feedback from the sales to the plan to just output in an in line with consumer needs we assume a real-time feedback mechanism Which uses sales to provide this output and the planning computers must derive the gross output required to meet the net outputs for set sales purposes broadly this the payment model dates from the early days of socialism from Robert arc that industry is publicly owned and planned in physical units employers are paid in labor tokens one per hour and goods are priced
in labor as proportions in labor required to make them when we say tokens these are Electronic tokens the socialist retail sector is instructed to use market clearing prices for finished goods if stocks of unsold goods grow they reduce the selling price if stocks fall they increase the selling price the planners are told that if the price of a good is above the labor value then increase the output of that good if the price of the good is below the labor value then reduce the output so this is the cyclic a cybernetic structure production takes Place
the goods are sold by the retail sector market clearing prices are adjusted the planners compare the ratios of labor values to price raising or lowering the final output targets from this they compute the gross outputs they then see what are the resources were going to need in terms of labor capital goods and environmental resources can the target output must be met if they're not they're adjusted and once that's done a detailed plan is issued in Principle this can be real-time with detailed plans can be adjusted in real-time but for that to be possible we need
a planning algorithm that shows the same degree of improvement in solving the problem as shifting from Gaussian elimination to a Jacobi solver does for labor times it has again got to be a long linear algorithm in a book we published an algorithm called the harmony method and it's based on the is rate of adjustment for stocks between Different production attempt is guided by the taking the derivative of what we turn the Harmony function for each industry so in a census a margin list optimisation process now if you're looking at I briefly mentioned complexity classes before
a constant complexity algorithm is one which takes the same amount of time whatever you're doing a linear one grows with the order of the number of inputs the next most tractable one is Order n log n then you get polynomial algorithms which grows order N squared like foreign cubed as Gaussian elimination does and then you get exponential ones which are intractable they grow as exponent of the number of elements you're dealing with if planning was an exponential problem it would clearly be completely intractable if it's an order n 3 problem for large n it becomes
intractable but if it's order n log n then it's going to be tractable Now the harmony algorithm we show by argument is n log n but what about the LP solve which was the linear programming package I used before what's its performance that linear programming was invented by Cantor efficient the kantorovich used it to plan for example the the the Soviet oil industry in Siberia what about that package well I've done experimental tests on economies of different sizes and different number of years using the Kantorovich method and this is the number of of industries in
the input-output table and this is the time in seconds taken to computer plan this line is for a 1 year plan that's for a 2 year plan that's for a 5 year plan so what we see is these are growing with a slope of approximately three on a log-log graph here if if it's it's got a slope of 3 and a log-log graph it means the problem is is of order n to the third do people understand why that's The case ok we'll take take it that I don't need to explain that this is still
going to be too slow for big plans so a one-year plan with 50,000 industries which was about the most detailed level of products that were tracked by Goss plan 5000 is more like what they actually planned for a one-year plan would take 33 years to compute without P solve if it was a five-year plan it goes up to 2,400 years so this is computing a Five-year plan with the kantorovich method is intractable so we need something which is near linear and whilst working on the book towards a new socials and we came up with an
algorithm that does this I originally tested the algorithm in the late 1980s on an obsolete Sun computer so the software that was developed in those days is no longer available in response to requests that people have made I've rewritten it in Java and released it on github so It's available for download along with the the software that I Ellis trated thus using kantorovich is method why do we know that a log-linear technique must exist we know that in principle any calculation that humans do can be done by computers and we also know that the complexity
order an algorithm doesn't alter according to whether it's humans or computers doing it And since market economies function and carry out computation it's proof that low complexity core coordination algorithms must exist it's clearly not the case that market economists depend on an algorithm of water n to the 3 n cubed or they would never be able to produce the hundreds of millions of products that are actually on sale in Amazon Amazon's got about 200 million products as I said the Harmony algorithm is an n log n algorithm I had previously Only shown it to work
with n log n complexity for single year plans I have now demonstrated it to work for 5 year plans the harmony function comes from neural net research and it's principal in this case is to mimic the principle of positive but diminishing marginal social utility what you require is a function whose value Rises as planned fulfillment approaches but which rewards ovale fulfillment less than it punishes under fulfillment so this is the shape Of the function I'm using at the moment this part is an N squared gradient and this is a logarithmic gradient and this is the
plan target ok this is the the harmony goes negative there's zero this is harmony in the vertical axis this is degree of output I'm assuming that we had an output target of two as the actual output is negative falls below that the harmony becomes negative going down here if the plan target is exceeded if we exceed the plan the harmony Function goes up Britt goes up with a more gentle slope than this so the under fulfillment of the plan is penalized more than over for fulfillment is rewarded the actual value of the function is s
minus s squared over two for the for the negative part of it and a logarithmic function for the positive part of it and s is the scale of production it's the proportional scale of production the net output minus the target over the target why do we use This well you need to be familiar with kantorovich s method which was to try and achieve an exact equivalence for all sectors with the planned target the Soviet plan would set a target of certain amounts of different outputs which had to be produced and factories aim to produce that
target or oval fulfill it but you had can't orbit said you have to oval oval over fulfill in exactly the right ratio if you're a car factory you have to over fulfill four Times as many wheels as you produce car bodies its no but no point over fulfilling the car bodies by ten percent and still producing only the original number of wheels so for many things it makes sense to have a fixed hard ratio between the outputs but that doesn't apply to the economy as a whole because if you follow contour which is optimization rule
it's acutally on T of demand function in economics and it can lead to unused resources which could Potentially be output and be of some use the second point is the because the function is a continuous first derivative it allows the use of Newton's method for approximation of functions and this allows us to rapidly bring all industries into approximate line up with the planck target suppose we start off with this scheme here here's the harmony there's the plant target and this is the output that's hand-drawn graph of it here's a Harmony function hand-drawn again if we
and the harmony function is zero addict intercepts the output suppose we have two industries a is exceeding the plant target and B falls short of the plant target the harmony function gives us a slope of each of these industries at that position if we know the slope we can compute the gradients and draw lines to see how much we should produce industry a to exactly coincide with a plan how much should we increase Industry B to meet the plant target so we don't move the whole way or you overshoot the algorithm moves it's roughly a
quarter of the way to where the gradient says it should go so you iteratively adjust all economies or all industries in line with these the derivatives of the Harmony function if yes I've already dealt with the overshooting in this case I share I took the example of taking half they they intercept we sorry what what you try and Do is not aim for zero harmony you try and aim for the mean harmony of all the industries because you don't know what the plan is exactly for fillable at the beginning so you try and bring all
industries towards the mean harmony now because the harmony function has a declining first derivative successive iterations of doing that raise the mean harmony and raise the mean degree of planned fulfillment so each time you do it you get a new mean you moved up to Here and they converge on a mean so you need a you need another stage of the hub was I'm gonna skip over that within the algorithm use the harmony gain as a dummy equivalent of the rate of profit harmony gain rate which is to say how much harmony is lost in
other industries in their youth resources that are used up compared to the harmony that is gained by the output of this industry this is an associate analog of the principle in the capitalist economy Capitalist opposed to shift to areas with higher rate of profit here so in the planning an analog with free resources to where the marginal harmony gain rate is greatest essentially we're using the derivatives near half of the Harmony function as a shadow price and computing a rate of return for each technique so this shows that Mises is wrong you can compute a
metric for different costs that is entirely independent of actual Prices on purely mathematical engineering grounds and this has all the properties that marginalist economics demands of the price system so you expand each industry proportional to its rate of harmony gain there are various problems with this if an industry has a negative harmony game couldn'ta making a loss it could say mean you you attempted to set industries to a negative rate of production so we use another technique which is widely used in neural nets Which is to make the adjust see the adjustment rate through a
sigmoid function function like this which compresses the the range minus infinity to plus infinity into the range minus 1 to plus 1 so that the harmony gain rate is fed through a sigmoid function to vent overshoots I will just illustrate I have you got the mic there can you answer a question is it worth my while attempting to them demonstrate that I can hear you is it worth my while Attending we can answer we check regression is it worth my while demonstrating in real time how much faster the harmony algorithm is then kantorovich is mattered
yes yes we would like to see this but let me say something can you just get this little window in other place cuz it's ok yes it keeps maybe you can close this I think yes but if I close it I've got no means of check are you doing huh okay okay okay The thing I'm going to show is I'm going to run now kantorovich is method which which is linear programming as against the Harmony method which is derived from neural nets okay first I'll run it three industries for three years it'll run very fast
I hope okay oh I've got to close all the spreadsheets I had yeah because there if I've got the input-output tables opening the spreadsheet I can't I can't create new ones each time I'm running this I've Got a random economy generating program which generates an economy with the right statistical properties for an input-output table okay sorry I will just show you this at the end what what I'm intending to get is this is the answer to the planning program it shows for each year what the input-output table is going to be in successive future years
it shows the capital use the flow the amount of accumulation you're going to Need of each type of goods and the harmony that is gonna for each industry and the net output to target ratios for each industry so that it generates a spreadsheet of that form so get rid of this don't save good [Music] just do that again okay execute the Harmony algorithm and that took four seconds that time bit longer than I expected the converting the this spreadsheet into A linear program took to feed into kantorovich methods takes five seconds and then kantorovich is
method here takes point seven of a second to solve the problem so the how many algorithm solves the whole problem in less time than it takes to translate the problem into inputs for a linear program but let's try instead we'll use 30 industries for three years it's always risky doing these tests online so that took four seconds with the Harmony Algorithm the linear program took five seconds to prepare and had seven thousand equations Center six thousand seven hundred equations to solve it's trying to solve the equations now and it took eleven seconds so above 33
above 30 industries in three years already the harmony algorithm is running faster if I increase that to thirty five industries for three years how many solves in 5.1 seconds this time the linear program Tate is prepared in Just over six seconds it's got nine thousand equations probably about 20 seconds out guess it'll take 18 seconds okay so it's easy to demonstrate that the hominid algorithm solves things much faster than your programming method which it hasn't which is good news because the kantorovich method grows intractably oops go back this is data I prepared earlier of the
speed with which so this is the number of industries these are different Numbers of years for which I'm running the Harmony algorithm and you can see the curves for this are much more tractable wrong shooting off like that as a straight line it levels off and the if you fit an equation to the run times you find that it's it's it's dominated by a logarithmic term so it's it really the log of Y is driven by lora is proportional to the log of X so it's close to linear slightly above linear slightly above linear here
but it's it's Not serious there with only two CPU cores on a really cheap computer a five-year plan for fifty thousand industries could be done in ten minutes instead of two thousand four hundred years there are restrictions in the current package because I've prepared the software to work with input/output table because that is the sort of data that people like you who might want to use it for propaganda purposes will have Available to you trouble is that in put out the tables grow in size as the square of the number of industries and therefore a
50,000 sector input-output table occupies a prohibitive amount of disk disk space and you you run out of memory to process the input-output tables readers or viewers of my videos correctly pointed out that what you'd actually use would be a relational database to store the data which is much denser than an input-output table you Can also paralyze the algorithm if you wanted to go to millions of products but the structure of the algorithm lends itself to paralyzing it's not something that I would do this is a software engineering task for a big group of people I'm
not concerned to do that so what can we sum up why are computers better than markets Hayek claims the market is a computing engine or a telecommunication system but it has a very slow cycle time measured In months or years and it arrives if not so by physically adjusting production up and down and it constantly tends to overshoot in an unstable way and there is human cost to these adjustments poverty and unemployment are caused by these and adjustments on the other hand computers can predict where an ideal market economy would get to if it ever
had the chance production can then be adjusted to go directly to this target and the cycle computation cycle time for The computation is just hours not years or months which and ideal even an ideal market economy would take to do it I think I'm going to skip over this section on democratic control there I if you're interested in it read the book towards a new socialism and also do a google scholar search for my publications and you'll find lots of mathematical papers on this I think that is probably enough for me doing the screen sharing
I see how I switch off Screen sharing not quite sure how I do that okay [Applause] so we come back now we're going to have a yes I can start maybe philosophy department so I don't really understand this but I would like to know you know the experience in Iceland I think in the last some years ago the Pirates party they got some seats on the Parliament and that they they they had as main idea to in implementers some Direct democracy with internet using using internet and this kind of stuff so do you know how
was this experience there I haven't followed Icelandic politics well enough to know do you have some other example I don't know of this currently country or region that uses this kind of approach that you maybe you had some inspiration well the it's applied very one-sidedly in California where people are allowed to vote on the taxes but not on the expenditure if you Just allow people to vote on one side of the aspect you get a suboptimal result because it puts an inbuilt bias towards reducing taxes and reducing expenditure the way they do it in California
you have to have people voting simultaneously on how much they want to be taxed and how much they once spent and you then have to resolve the the differences between those two choose the average amount of expansion and Taxation people want but if you did that the way We developed it for our handy vote system was based on a critique of the American electoral practices both both the direct democracy in California where where there is a considerable element of direct democracy and the the way the u.s. voting machine system is very open to hacking but
that's a separate talk on secure voting and and yeah I don't want to get onto that now because there's a lot of maths in that as well I'm official intelligence and computing And my question is relates to the political issues first question is whether you deal with political questions in your book in your other works questions like for instance the failures problems with the Soviet economy where due to technical issues in the planning of the economy or the political questions were dominant and on the other hand I mean are there any perspectives of advances that
sort of approach to economic planning in the Democracies of today in any way that sort of questions that in my mind after finding your exposition very interesting from sorry we're not hearing you're just a second bone I think now it's working let's see no no we can weekend hello I can hear you no it's okay the both of these the the it is both the political question and an economic question the the former state in the USSR starts off as a proletarian aristocracy Or a state of the working-class Vanguard but because the the model of
democracy that is adopted is a highly indirect one with multiple hierarchical layers of delegation it gives a big advantage to whichever party has a slight majority at the base level so you were bound either to get the the bolsheviks of the social revolutionaries having a one-party dictatorship at the top in one way it may have been a matter of chance which won it which of those two parties came Out at having a one-party dictatorship but the constitutional form of Soviet democracy was bound to lead to it because any kind of indirect voting exaggerate the effect
of a majority at a lower level and if you go through two or three layers of this then you get an enormous exponential concentration of of advantage to the biggest party so there is a political issue there there is the the general lack of coming up with a means of increasing democracy which Doesn't just immediately turn into something which the the better off or the more educated can turn to their advantage by restoring the capitalist order to my mind any system of open elections with competing parties in a country like the Soviet Union was a
recipe for restoring capitalism the only thing which kept the the party well kept the state pro socialist was the fact that the the party exercised a set of rules on the class composition of Candidates to the supreme put forward for the Supreme Soviet they tried to aim to have a certain percentage of of collective farmers a certain percentage of manual workers a certain percentage of intellectuals put forward as candidates and this gave you what was a broadly class representative structure in the Supreme Soviet even though they're all from one party as soon as you get
competing parties operating there without this principle of class Selection what you get is the most educated and socially articulate and people in the most prestigious jobs being nominated as candidates so as soon as got off released the Brezhnev ID system of party quotas for different classes and allowed competitive elections to the Supreme Soviet you've got to change in the class composition you've got far more managers and professional people and elected and you've got a drastic decline in the Number of women delegates so the ideas of democratic reform were actually disastrous because they weren't they didn't
increase the democracy but they increased the the privileged class character of those elected and the only way around that the only scientific way around it is to make the the representative bodies like the equipment of the Supreme Soviet just at random from the population any electoral system introduces strong biases towards those With a high social status people with a high social status are much more likely to get elected than people with a low social status so you end up with a statistically very unrepresentative governor body if you have compete competitive elections and I think this
was the big weakness of the Stalin 1936 Constitution it just attempted to replicate the electoral mechanisms that existed in western Bush were states and the only Thing which saved it was the the pre selection of candidates by the Communist Party that was the question that I was thinking about when you were giving your lecture and I was thinking and I was wondering if is that is there a way to keep some kind of democratic method of choosing the politics and the ways that the production and keeping the the economic planning at the same time in
other words how can how can we keep democracy and Institute an economic Planning okay the you have to take into account what do you mean by democracy first and the nature of the mode of production of industrial society the mode of production of industrial society imposes tight coordination between different branches of Industry in a way which isn't a question for pre-industrial society instantly I've stopped being able to see you is the link still working yes we are ok That's not an issue in pre-industrial society that means either the market or the plan has to dictate
what individual production units do they they cannot be autonomous they cannot decide for themselves any apparent autonomy is only is only a parent because there they're either dictated to by the market or they dictated to by the plan if they dictated to by the market they're effectively dictated to by those with money so being Dictated to by the plan is preferable because at least people can vote on what they want the allocation of resources in a plan to be then there's this issue of what is meant by democracy and I think people should go back
and study Aristotle on this they should study Aristotle's politics because it's clear in Aristotle that what is labeled democracy in the modern world is exactly its opposite it's what is labeled democracy is what Aristotle calls Aristocracy it or either oligarchy or aristocracy he's quite explicit that any electoral system is aristocratic and that the only democratic way to run things is how people either vote directly or have random juries so it in that sense our book towards a new socialist Marxist Aristotelian ISM Thanks do you have time for one more question yeah one more yeah i'm
mateus from the institute of physics and sure you presented as a way of Planning how to allocate productive labor right yes but how would you socially allocate in a socialist economy unproductive labor like building infrastructure hiring people for sales [Music] well these are not per se different the the difference occurs in how you set the planned target if you know what your plan target is the same algorithm can be used so if you know that your planned target is to build five new hospitals And star five new hospitals that's no different from saying you're going
to to build an airport and staff an airport from a planning point of view the difference comes in whether or not the thing you're calling unproductive is paid for out of income tax or it's paid for out of the the proceeds of of selling the surface for labor vouchers so it doesn't affect the planning it just affects the decision process or it doesn't affect the internals of planning It just affects the goal setting which is a separate problem goal setting what we're saying is a goal setting has to be a combination of a market in
consumer goods and some form of direct democracy on the budget headings like how many million person-years are going to be expended on health care how many million person-years are going to be expended on education those are things you that need a vote you don't want to have a vote on How many hundred thousand person years are going to be spent on blue jeans versus red jeans okay so I think that's it thank you so much once again and okay opportunities with you okay can you email me a link to the the YouTube for sure we
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