There will always be power and profit in being able to monitor and control what people are going to do. This is a scary fact of life in the human arena. And though this is not the first time that technology has advanced so far so fast, some pretty scary basic concerns about governance and fundamental rights have been raised in recent years.
Eventually, in the midst of the well-wishers there will come those souls who are not good actors, and they do seem to seem to spoil the bunch sometimes - don't they?
Given enough power, anything is worthy of unusual inspection. Similarly, the current success of Uber is no different. Regardless of whether the social, political and market narratives about Uber are currently accurate, fair or not, it is the sudden nature of company power and the driving essential questions around the nature of new economies that compel articles like these. Uber and AirBnB are challenging fundamental labor and property rights shibboleths, and demanding real consideration from people across the philosophical, commercial, and political realms.
Similarly, the 20th century spread of dictatorial socialism was incredible. No matter how much I try to sympathize with the promises of various ideologies, I always return to the premise that in all circumstances, it is the CONCENTRATION OF POWER that is the problem. It is even more disturbing for pragmatists and empiricists when they see something moving fast that is denying anyone the chance to scrutinize, test and debate the merits of the method, the motives, the means.
As a good friend says though - it is easy to make these conceptions "heuristics" and see someone's intent as globally bad. Some people's intentions can be good and means and methodology sound. Yet with data as with literacy at large, the medium by which the person't intent is made manifest is the very means by which the power will be exercised and the rules challenged. In this case, massive volumes of data are being generated that have multi-dimensional consequences for all humankind. This IS a concentration of power. Even though a witch hunt is far from a beautiful thing, the world citizen has very real reason to be concerned, and truly should be immediately concerned, about the very topics that are daily discussion here on HN. Matters of technology, privacy, rights, commerce and liberty are not weak, and neither are musings on the mating habits of whales.. from time to time.
HN is a fount of a certain kind of literacy. How does that literacy get expanded to all, and seen as a human right?
Another good read on related subjects (i.e. data-driven management, and the dilemma faced by Socialist state in trying to remove prices - i.e. market forces - as self-regulating mechanisms) is "Red Plenty" by Francis Spufford. Here is the website: http://redplenty.com/Red_Plenty/Front_page.html but I heartily reccomend reading the book.
One thing the often bugs me is when management demand more analytics on the work flow of a department. This usually entails more manual logging by the staff, which takes time out of their day. 'But we need this information,' they say, 'otherwise we're just flapping about in the dark not knowing the full picture.' Or something to that effect.
The thing is, how is it that we seemed to manage just fine without all those business analytics in the past? Somehow people were able to exercise their judgement and run the department effectively. Not that there's no room for improvement of course, but maybe you'd be better skipping straight to diagnosis/solutions rather than spending time logging and collecting indicators.
I believe this is a result of the shift from production of physical goods to a more service-oriented economy.
If your main concern is "manufacturing X" it is usually fairly simple to tally "Number of X produced" (even "Number of X produced by operator #128") number of defective parts, number of returned items after sale...
If you deal with software development, translations, advertising, copy editing getting an idea of "productivity" is far more complicated.
Do you count "lines of text written by operator #128"? This might make marginal sense for translators (and you are still missing any idea of quality/defects, because even if a customer rejects your work as "completely wrong" you won't get any specific metrics) but completely misses the mark for the other examples I listed.
So yeah, we are stuck with the idea that "you cannot control what you cannot measure", but we have a serious deficit in terms of measures.
Big Data is getting better at giving us lots of odd correlations -- people buy poptarts before a hurricane. Uber knows where people are going to go. This information is extremely useful.
But what we're missing here is this central fact: correlation data is only good inside a very limited set of preconditions. Once you have a WalMart or an Uber, it helps them operate better. It does not have the ability to create the next WalMart or Uber.
That means that Big Data, as it is now, will always be able to continue to optimize within a limited system, but will not be able to see outside of that system. Big Data will not be able to create the next paradigm-changing thing like Uber, because paradigm-changing things are by definition outside the scope of the data already collected.
Recently there was a a study published by some MIT students about startups. It ran a bunch of numbers and gave you advice: pick a small name, operate outside the valley, use older workers, and so on. But as somebody pointed out, you really need to have a great idea, spot-on execution, and market traction. If you have that, the rest of it doesn't matter. More to the point, if you have all of those things the MIT guys came up with, they're not going to give you the other things you need. As it turns out, the things you need for a great startup are still fiercely debated -- hence the MIT study in the first place. Correlation does not equal causation.
I see this in big companies all of the time. Our projects are running, on average, 100% late! So somebody looks at the data and finds that most of the time is spent testing. What do we need? Better testers, of course!
Simply because you can point to a couple of different things that track together does not mean you understand anything. And in IT, unlike Big Data, we do have to worry about causation, because we're inventing the universe every time we ship.
You always optimize complex systems from the bottom-up, never from the top-down. Otherwise you're just fooling yourself in various interesting ways. That's true no matter what the system is.
The article doesn't show that the Cybersyn experiment actually influenced the modern big data movement (or anything for that matter). I think that "The socialist origins of the Big Data nation" is much more accurate, since even though the article didn't show any influence on current government big data initiatives, at least there is a lot of similarity.
In spite of being a free market supporter, I think that command economies have been useful at times, e.g. the PRC and the USSR in their early stages. Both these countries practiced something similar to what Chile tried, in the 70's and early 80's. My theory is that before communism these countries were practicing a a very corrupt state capitalism. So a logical step before capitalism, was to rationalize state capitalism by making government decisions based on utilitarian goals instead of corruption.
EDIT: modified my request for title change after I read the original title more carefully.
Prior to their communist revolutions, both the USSR and PRC were actually practicing something not very different from feudalism. In fact, one of the reforms of the last Tsar was to unbind (legally, if not in practice) serfs from their estates.
I used the term state capitalism very loosely. What I meant was that success in the economy was primarily a matter of getting the government to grant you privileges.
Shortly after their "communist revolutions" both the USSR and PRC were still practising something not very different from feudalism.
Totally unsurprising, given that their "communist revolutions" were revolutions in name only, and happened in conditions Marx had spent decades explaining why would not lead to successful transitions to socialism, much less communism (first, as far as I know, in "The German Ideology", 1845, Part I, section A, 5: " And, on the other hand, this development of productive forces [...] is an absolutely necessary practical premise because without it want is merely made general, and with destitution the struggle for necessities and all the old filthy business would necessarily be reproduced").
Both the Bolsheviks and the CCP quickly re-established near feudal structures in response to opposition or failures - soon only the titles and names were different.
Cybersyn influenced modern big data inasmuch as .. in its time .. big government was the only real way to get big data, so the proponents and the principles of the subject were perpetuated all through the 80's and 90's and trickled into the commercial sphere in the same way that the technology to support the effort made its way into industry, and the public sphere in general.
That's in interesting viewpoint, but I didn't see that expressed in the article. It did describe the people involved going on to do other things, but it did not show that they were actually influential. As I pointed out, the original title didn't claim that Big Data had its roots in Cybersyn.
Well for those of us who have been doing computing for 30+ years, the Cybernetics movement has been very much key in developing the big data analysis process, industry, and academia .. one could 'do a grep' for all the Cyberneticists in the field and discover what they're up to now, and undoubtedly they'd be out there. I remember in the 80's at least, while working at a database vendors bunker/retreat, seeing Jay Forresters' books and papers scattered in the library, discussing Beers' techniques, and so on. Cybernetics seems to have flown under the radar of many in the modern age, but that doesn't mean it hasn't been seriously influential. This 'wave' of relevance/irrelevance is something the computer sciences deals with on a regular basis, but though the wave may be choppy, the undercurrent still flows on ..
You're right though, this isn't really adequately presented in the article. Cybernetics is definitely worth investigating, though, for anyone doing big data today. So many lessons learned, forgotten, and re-learned, over and over again in the big ocean of human consciousness ..
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[ 3.2 ms ] story [ 45.2 ms ] threadEventually, in the midst of the well-wishers there will come those souls who are not good actors, and they do seem to seem to spoil the bunch sometimes - don't they?
Given enough power, anything is worthy of unusual inspection. Similarly, the current success of Uber is no different. Regardless of whether the social, political and market narratives about Uber are currently accurate, fair or not, it is the sudden nature of company power and the driving essential questions around the nature of new economies that compel articles like these. Uber and AirBnB are challenging fundamental labor and property rights shibboleths, and demanding real consideration from people across the philosophical, commercial, and political realms.
Similarly, the 20th century spread of dictatorial socialism was incredible. No matter how much I try to sympathize with the promises of various ideologies, I always return to the premise that in all circumstances, it is the CONCENTRATION OF POWER that is the problem. It is even more disturbing for pragmatists and empiricists when they see something moving fast that is denying anyone the chance to scrutinize, test and debate the merits of the method, the motives, the means.
As a good friend says though - it is easy to make these conceptions "heuristics" and see someone's intent as globally bad. Some people's intentions can be good and means and methodology sound. Yet with data as with literacy at large, the medium by which the person't intent is made manifest is the very means by which the power will be exercised and the rules challenged. In this case, massive volumes of data are being generated that have multi-dimensional consequences for all humankind. This IS a concentration of power. Even though a witch hunt is far from a beautiful thing, the world citizen has very real reason to be concerned, and truly should be immediately concerned, about the very topics that are daily discussion here on HN. Matters of technology, privacy, rights, commerce and liberty are not weak, and neither are musings on the mating habits of whales.. from time to time.
HN is a fount of a certain kind of literacy. How does that literacy get expanded to all, and seen as a human right?
The thing is, how is it that we seemed to manage just fine without all those business analytics in the past? Somehow people were able to exercise their judgement and run the department effectively. Not that there's no room for improvement of course, but maybe you'd be better skipping straight to diagnosis/solutions rather than spending time logging and collecting indicators.
So yeah, we are stuck with the idea that "you cannot control what you cannot measure", but we have a serious deficit in terms of measures.
Big Data is getting better at giving us lots of odd correlations -- people buy poptarts before a hurricane. Uber knows where people are going to go. This information is extremely useful.
But what we're missing here is this central fact: correlation data is only good inside a very limited set of preconditions. Once you have a WalMart or an Uber, it helps them operate better. It does not have the ability to create the next WalMart or Uber.
That means that Big Data, as it is now, will always be able to continue to optimize within a limited system, but will not be able to see outside of that system. Big Data will not be able to create the next paradigm-changing thing like Uber, because paradigm-changing things are by definition outside the scope of the data already collected.
Recently there was a a study published by some MIT students about startups. It ran a bunch of numbers and gave you advice: pick a small name, operate outside the valley, use older workers, and so on. But as somebody pointed out, you really need to have a great idea, spot-on execution, and market traction. If you have that, the rest of it doesn't matter. More to the point, if you have all of those things the MIT guys came up with, they're not going to give you the other things you need. As it turns out, the things you need for a great startup are still fiercely debated -- hence the MIT study in the first place. Correlation does not equal causation.
I see this in big companies all of the time. Our projects are running, on average, 100% late! So somebody looks at the data and finds that most of the time is spent testing. What do we need? Better testers, of course!
Simply because you can point to a couple of different things that track together does not mean you understand anything. And in IT, unlike Big Data, we do have to worry about causation, because we're inventing the universe every time we ship.
You always optimize complex systems from the bottom-up, never from the top-down. Otherwise you're just fooling yourself in various interesting ways. That's true no matter what the system is.
In spite of being a free market supporter, I think that command economies have been useful at times, e.g. the PRC and the USSR in their early stages. Both these countries practiced something similar to what Chile tried, in the 70's and early 80's. My theory is that before communism these countries were practicing a a very corrupt state capitalism. So a logical step before capitalism, was to rationalize state capitalism by making government decisions based on utilitarian goals instead of corruption.
EDIT: modified my request for title change after I read the original title more carefully.
Serfs were freed in 1861[1]. A year before slaves were freed in the USA[2]. By Alexander II - the grandfather of the last Tsar.
[1] http://en.wikipedia.org/wiki/Emancipation_reform_of_1861
[2]http://en.wikipedia.org/wiki/Emancipation_Proclamation
Totally unsurprising, given that their "communist revolutions" were revolutions in name only, and happened in conditions Marx had spent decades explaining why would not lead to successful transitions to socialism, much less communism (first, as far as I know, in "The German Ideology", 1845, Part I, section A, 5: " And, on the other hand, this development of productive forces [...] is an absolutely necessary practical premise because without it want is merely made general, and with destitution the struggle for necessities and all the old filthy business would necessarily be reproduced").
Both the Bolsheviks and the CCP quickly re-established near feudal structures in response to opposition or failures - soon only the titles and names were different.
You're right though, this isn't really adequately presented in the article. Cybernetics is definitely worth investigating, though, for anyone doing big data today. So many lessons learned, forgotten, and re-learned, over and over again in the big ocean of human consciousness ..