Tag Archives: economics

Netscape and the rise of technocapitalism

Only ’90s kids will remember Netscape, the original browser of the Internet before the era of Internet Explorer, Mozilla Firefox, and Google Chrome. But what we didn’t realize was the impact Netscape had on capitalism, and the way it symbolized and perhaps even initiated a recomposition of political economy. I have a hypothetical periodization of capitalism that I’ve been trying to work out, involving a distinction between industrial capitalism, finance capitalism, and technocapitalism, based on what industries are dominating the economy and directing the flow of capital, and studying the Netscape era yields some very useful information.

Netscape was the first real “unicorn”, a tech start-up that becomes valued in the billions of dollars by big investors. It was the brainchild of Jim Clark, an eccentric entrepreneur in the likes of Steve Jobs, whose impact on Silicon Valley has been documented in Michael Lewis’ The New New Thing (1999). Clark had already made a small fortune during the 1980s from his first start-up, Silicon Graphics, which had revolutionized graphic cards and 3-D rendering and paved the way for graphic user interfaces and the personal computer. But as the company grew, it was essentially taken over by Wall St. investors, who pushed out Clark and took control of the the profits.

Bankers taking control of up-and-coming companies wasn’t exactly a novel thing; it was how things were in the 1980s. But with Netscape, Clark was determined to not lose control and money to the bankers again. The new company, and its core product — an Internet browser — suddenly made the Internet more accessible to the average person by many orders of magnitude, and thus also meant a massive, massive market opportunity.

Its not clear exactly what kind of bargaining power Clark had against Wall St. Part of it was probably just a case of information asymmetry, and the bankers having severe FOMO. But in any case, he and his team played hard and fast against selling out the company too early, or for too few shares or seats on the board, and the result was that Netscape was the first tech firm that had engineers and programmers at the top, controlling the lion’s share of capital and the flow of profit. Wall St. made money too, of course, but they were simply following along in the wake. When the company launched its IPO in 1995, it turned the engineers and programmers into millionaires, and the co-founders into billionaires, and forever changed the game for Silicon Valley. Even though the company would be very quickly run off the road by Microsoft and Internet Explorer, the nature of its rise created a new standard for the ambitions and strategies of its entrepreneurs, and flipped the balance of power between tech capital and finance capital.

However, the Netscape era was only the beginning of a larger recomposition and re-balancing of global capitalism. The rise of technocapitalism rode on the Dot-com bubble, which burst in 2000 and eviscerated the industry. The survivors would kneel once again before finance capital — until the latter had its own reckoning in the 2008 financial crisis, after the housing bubble burst. Once the smoke cleared, tech would once again be in the vanguard of capitalism, based on the foundations built by companies like Netscape years earlier.

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Finance capitalism vs. industrial capitalism

What marked the beginning of the modern era of finance capitalism, and what differentiates it from the earlier era of industrial capitalism? There is some good information and arguments on this in David Harvey’s A Brief History of Neoliberalism (2005), and in Gerard Dumenil and Dominique Levy’s Capital Resurgent: Roots of the Neoliberal Revolution (2004) (which is cited extensively by Harvey).

By most measures, finance capitalism arose out of the crisis of the 1970s, and its hegemony has lasted at least until the 2008 crash. There were several factors in why finance capital started becoming so structurally dominant:

  • The collapse of the Bretton Woods system (which regulated international monetary policies and tied the US dollar to a gold standard), thus making most currencies free-floating, and loosening the ability of capital to flow across national boundaries
  • The oil shocks of the 1970s, caused first by the 1973 OPEC embargo and then by the 1979 Iranian Revolution, drastically increased the profits of oil-producing nations, who subsequently invested these super-profits into Western banks
  • The political turn toward financial deregulation in the late 1970s and through the 1980s, which was both a consequence and a cause of the increasing economic power of finance capital
  • The Volcker Shock, which spiked interest rates in 1979 and ushered in an era of high real interest rates through the 1980s and 1990s; this drastically increased the flow of capital toward creditors (financial institutions), and as companies or even whole governments defaulted, sold off assets, and restructured, finance gained more and more direct control over the global economy

One major qualitative change in the era of finance capitalism seems to be the commodification of consumption. This might be a strange way of putting it; after all, isn’t consumption always about consuming commodities? But what I mean here is that under finance capitalism, the very act of consuming — the purchasing goods and services — itself becomes a commodity, to be bought and sold on the market, in the form of various types of consumer debt.

Another major qualitative change was in the nature of corporate governance and the control of profits. After the 1970s, industrial production was increasingly controlled according to the dictates of finance. More and more profits were sucked up into finance companies and to shareholders, rather than reinvested back into production, as was the general trend during industrial capitalism; and on the flip side, many industrial corporations increasingly branched out into finance themselves.

Capital Resurgent, p111

Another way we can describe this periodization is by pinpointing where the center of dynamism was in the economy during different eras. In the era of industrial capitalism, the cutting edge of profit-making was in creating new industrial goods: automobiles, household appliances, houses, gadgets and widgets and doohickeys and whatnot. In the era of finance capitalism, the cutting edge of profit-making shifted toward the creation of new types of debt and other avenues for extracting surplus value from the circulation of capital, rather than just in production and distribution.

I’m not sure quite how accurate all of this is; there are some good graphs in Capital Resurgent clearly demonstrating how finance companies become very powerful in the 1980s and 1990s, if you judge by metrics like market cap or rate of profit. However, other metrics — i.e. consumer debt in the US — don’t as strong or clear of a trend. It’d be useful to find some more raw data-sets on such things, to get a stronger quantitative understanding of the transition.

But the real purpose of thinking through this potential framework of industrial capitalism vs. finance capitalism is to consider whether there has been yet another shift, toward an era of technocapitalism, where the cutting edge of profit-making is in the commodification of data. After all, data has been declared to be the new oil, and tech companies are generally understood to be at the top of contemporary capitalism’s pyramid. This also raises the question of how useful the term “neoliberal” actually is, and whether it is specific to finance capitalism and whether we need a more nuanced understanding for technocapitalism. But more on this another day.

Amazon, the decimation of warehouse worker wages, and a warehouse inquiry

In the latest issue of Economist, there is an article with some pretty stunning analysis about the wages of warehouse workers in US counties where Amazon sets up shop — specifically on how they collapse.  The following two graphs speak for themselves.

What’s behind this?  According to the analysis cited by Economist, it appears to be a combination of Amazon workers being younger, more inexperienced, and more unskilled than in other warehouses, and generally not able to find alternative jobs due to there only being a few employers in the area.  Technology also plays a role here, with cutting-edge automation allowing the company to hire younger and less skilled workers in the first place, which is deeply related to the argument that automation doesn’t eliminate the need for work, but rather helps generate the need for less skilled work.

Amazon is growing fast, already worth more than all the major brick-and-mortar retail companies put together.  Its combination of retail, logistics, and tech is allowing it to devour large swathes of the US economy into itself.  Amazon and its low-wage, cyborg workforce is the future — and the present, for that matter.  Engaging in militant labor struggles in Amazon warehouses will only become more and more critical for all those interested in rebelling against the rule of capital.  Thus inquiries and workplace reports, like this one just released by Angry Workers of the World, are a valuable resource that worker militants should use and produce themselves, in order to pick apart the nature of the workplace and reveal the ambient level of worker unrest and struggle.  To quote from the conclusion of the first report:

This all sounds bad, but don’t believe that the workers just sat and took it like the good victims the newspapers like to write about every now and again. In the beginning a lot of people had high expectations of working with Amazon, but after a few weeks they started to realise what working for Amazon really meant. So after a few weeks you started to hear more and more angry and incensed discussions amongst workers around the aisles of the pick tower. Workers who in the beginning tried to run themselves into the ground trying to reach their targets, now having realised it didn’t make a difference in terms of getting a long term contract, stopped stressing about targets and deliberately worked slower than they could. In the beginning we were all worried about even going to the toilet because we might get a warning for “time off task” but after a few weeks when we started to realise we would all be fired soon anyway more and more people started to take “extra” breaks, spending time talking with colleagues, wandering around the warehouse, going to the canteen to grab a cup of coffee, playing a game of ping pong, and of course not giving a toss about ‘power hour’. The permanent staff already know that Amazon don’t care about the workers and the temps quickly learn it, and a lot of us start to do minor individual acts of resistance. That is all a good start, but if we want to change the way Amazon treats us we have to work and resist together!

Data and AI, the core of contemporary capitalism

Last week’s Economist had an excellent report on the data economy and its growing importance to contemporary capitalism.  Data is now the most valuable commodity in the world, ahead of oil, and the five most valuable firms in the world are all technology companies: Alphabet (Google), Amazon, Apple, Facebook, and Microsoft.

It is generally understood that all the free online websites we use aren’t actually “free”, but rather are paid for via data collection on our activities on these sites, which are used for targeted advertisement.  Less understood is the fact that increasingly, the real value is not in data and advertising, but in using the data to improve artificial intelligence programs that are much more valuable and create much more complex services, like language translation and self-driving vehicle algorithms.  Hence, why Tesla is valued so high, despite selling so few cars relative to companies like Ford: the real value is in their massive pool of data that they collect from Tesla drivers, and their increasingly proficient self-driving vehicle AI.

Data-collection and AI has spread across the entire economy, beyond just what we think of as “tech”. Transportation is the obvious sector that is fusing with data/AI, but less obvious sectors include the health care industry, and traditional sectors in manufacturing and industrial processing.

GE, for instance, has developed an “operating system for the industrial internet”, called Predix, to help customers control their machinery. Predix is also a data-collection system: it pools data from devices it is connected to, mixes these with other data, and then trains algorithms that can help improve the operations of a power plant, when to maintain a jet engine before it breaks down and the like.

Of course, creating a system for data acquisition and monitoring is hardly new for plants, its not like you can run a modern plant without some kind of control system; what is actually new here is the application of AI to analyze plant data and suggest improvements that plant operators might not realize could be done.

The finance-data intersection is also important to grasp.  A primary point of discussion in the Economist report was around data markets — specifically, the lack of one.  Despite data being so valuable, there exists no real market for companies to trade data-sets and data-streams; instead, they simply buy up the whole company so that they can silo off data for themselves.  There doesn’t appear to be much enthusiasm from tech companies to create such a market; on the other hand, one would imagine that Wall St. is watering at the mouth at the prospect of financializing data, in the same way that manufactured commodities were in the ’80s and ’90s.  Wall St. already makes use of financial data and AI, to the point where engineers and programmers seem more important than traditional traders, but to bring the data itself into the realm of trading and financial speculation is whole other story.

Lastly, and perhaps most importantly, there is the issue of the amount of control that we average schmucks have over our data.  The report discusses many ideas around how to give us back control, such as tools and regulations that allow us to view and control all the data that is out there about ourselves, and even get compensation for its use.  Amusingly, the report’s final section is titled “Data workers of the world, unite!” and discusses arguments for a “digital labor movement” by those of us (which is basically all of us) whose data is being fed into increasingly powerful AIs, and monopolized by massive and unaccountable corporations.  References are made to Jaron Lanier’s Who Owns the Future?, and the way immense amounts of value is being spun out of day-to-day activities– mostly online, but increasingly offline as well.

This idea is a callback to the Marxist analysis of machines and labor, where technology is said to be “dead labor” insofar as it is a mechanized interpretation of what living labor (the human worker) does.  The power loom took the labor of weavers and interpreted it through a machine, locking in the knowledge and skills of the workers into a system controlled by capitalists.  Machine-tool automation did the same for machinists and metal-workers.  Today, we can imagine this trend reaching toward its logical conclusion, where capital soaks up human knowledge and skill in general and uses it to build AI that could perhaps for people entirely — and beyond.

All of this should emphasize the importance of organizing within the tech industry.  All of these data and AI-centered processes are not driving themselves.  They are dependent on armies of engineers, programmers, scientists, and all the other workers within the tech industry.  They are also increasingly political, even radical.  Contemporary movements to overthrow capitalism will necessarily have to synthesize the workers who are laboring at its core.

Monday Interesting Links (On Climate/Environment)

  • Essay on industrial agriculture, ecological alternatives, and class struggle, via Jacobin
  • Article on the deep divides within the AFL-CIO over the issue of DAP and other climate issues

Sunday Interesting Links

  • Lengthy essay on prison labor, mass incarceration, and labor market dynamics
  • Book reviews on the history of Angola, Cuba, and apartheid South Africa
  • Old essay from 2004 on a radical left environmental strategy in southern conservative states, from the IWW Environmental Unionism Caucus
  • Reportage on Indian oligarchs and the arms industry
  • Article on the racial advocacy of New York City’s Health Commissioner, and her old ties with the Black Panther Party

Machine tool automation and economic distortion from the military-industrial complex

Apologists for the bloated military budget of the US will often raise the point about how military spending supports technological development.  Aside from depending on a religious understanding of technological progress as inherently “good”, this argument is flawed given the fact that military spending has sometimes deformed scientific and engineering R&D into more inefficient and ineffective directions.

Take numerical control (N/C) machine tool automation systems developed in the 1950s and deployed throughout the 1960s and 1970s.  N/C development was chosen by the military and their partners in select universities and corporations, and thus ended up crowding out alternative technology pathways. According to David Noble’s Forces of Production: A Social History of Industrial Automation (1986) N/C systems were 1) far more expensive and complicated than the competing technology of record-playback (R/P), which was easy to program and use, and 2) expensive compared with the benchmark system because of how the unique needs of the military industries crowded out cheaper, general-purpose N/C systems.  As a result, domestic production of N/C systems lagged for the civilian market (which dominated the metal work industry), and allowed for the domination of foreign machine tool firms.

Fujitsu Fanuc, a leading Japanese machine tool builder, in 1973 alone produced more N/C machines designed for the commercial market than all US machine tool firms combined.  Likewise, in West Germany, machine tool builders concentrated upon the commercial market.  According to Paul Stockmann of Pittler–a central figure in German N/C development–German manufacturers were locked out of US military contracts and the APT Program and found, besides, that “no one was interested here in a highly sophisticated program which required access to a big computer.”  Instead, manufacturers focused upon less expensive and less demanding programming methods, and designed their cheaper machines accordingly.  Not surprisingly, with domestic machine tool builders tied up with military and aerospace industry orders and specifications, foreign manufacturers were able to gain a significant foothold in the US commercial market.  Between 1960 and 1975, US imports of machine tools increased 300 percent.  By 1978, the US had become a net importer of machine tools; Japanese machines accounted for one-third of these imports and West German machines accounted for one-fifth (222).

Here’s something else to ponder: how much did the dominance of Japanese and West German firms in the machine tool industry affect the decline of American manufacturing in the 1970s and 1980s, and the subsequent collapse of industrial communities across the Midwest?  Perhaps not much, given that factories should have still had access to the higher production rates of foreign machines, but this still demonstrates how the dominance of military interests in a critical field of technology in fact stifled the development of better, general-purpose systems.