I wrote this brief note for my 4th-year Global Political Economy class as a way to bring them up to speed on the knowledge economy. Because it’s intangible, and because it can raise all sorts of questions we usually get into via drunken 3 a.m. dude, is-anything-even-real discussions, it can be difficult to understand what knowledge is in a political-economy sense. Those of you who live this stuff will note the influences of Foucault, Berger and Luckmann, and Bourdieu, among many others, such as Srnicek’s Platform Capitalism and Powers and Jablonski’s The Real Cyber War (in Rule 7).
At the end, I’ve also added three helpful tips for thinking through the political economy of knowledge that follow from these ground rules.
I’m aware that I’m using “knowledge” and “information” in slightly different ways than others, but this distinction works for me. Comments welcome, on this and the rest of the list.
The seven ground rules
Although we have supposedly been in the “information age,” or the “knowledge economy” since the mid-1990s, these terms, as well as related concepts such as “data” and “technology” tend to be used loosely to describe many different phenomena. It can all be a bit confusing. In order to make sense of our object of study, we will observe the following seven ground rules.
- “Knowledge” and “information” refer to two different things.
In our phrasing, information refers to phenomena that exists in the world independent of whether or not someone observes it.
Knowledge refers to whatever phenomena humans decide to observe. The act of deciding to observe something, and then observing it, transforms information into knowledge. Put another way, knowledge involves giving social meaning to phenomena.
From this perspective, forms of knowledge include, but is not limited to, the following:
- Technology (recognized ways of doing things);
- Intellectual property (including drug compounds, music, the Golden Arches, and so on);
- Culture (stories, giving meaning to sounds or colours applied to physical materials); and
- Data collected by your Fitbit.
- Deciding that some piece of information counts as knowledge is a conscious, political act.
The world is filled with information, but we must make a conscious decision, informed by politics, culture, economics, morality, and so on, to turn this information into data, or knowledge. In other words, political debates over how to treat data that do not question whether this information should be collected in the first place, that assume this “data” was just hanging around to be collected, already has a profound bias toward collection and use.
- Knowledge is intangible.
Unlike material goods, which serve as the economic foundation of a manufacturing economy, commodified forms of knowledge (such as intellectual property, or personal data) do not have a material manifestation. One of the consequences of this fact, as we will see, is that knowledge-based economies function very differently than do manufacturing-based ones. For example, it is very easy, under current laws, for transnational corporations to engage in tax arbitrage by moving the “value” attributed to knowledge across borders. Similarly, the nature of knowledge production means that they produce much different types and levels of employment than traditional manufacturing companies, and have different spillover effects into the local economy. To understand their economic effects, they must be studied on their own terms. Furthermore, the characteristics of knowledge mean that currently it is easy to absorb smaller companies’ knowledge/data and export its value. However,
- There are always rules governing knowledge. They always benefit some groups and practices, and impede others.
People tend to assume that knowledge, absent legal protections, can be used by anybody – in other words, that it is non-rivalrous. For example, if there were no copyright laws, anyone could download as much music as they wanted, and could remix that music in any way they pleased.
This is not exactly correct. In practice, the creation and use of knowledge is always and everywhere subject to rules, both formal and informal. These rules determine what knowledge can be used, and by whom. Put most bluntly, there is no such thing as free speech, in the sense of “speech unrestrained by rules.”
At the most trivial level, these rules (such as grammar) render coherent the communication of knowledge. Social taboos against the use of profanity or the discussion of politics at Thanksgiving regulate speech, or a stand-up comic mimicking another’s act. The most formal rules are those such as intellectual-property or hate-speech laws, or governmental freedom of information acts. Speech and data use can also be governed by companies’ terms of service – for example, Twitter’s (unevenly applied) rules against hate speech. Rules and norms may be more or less permissive, but they are always there.
These rules will always benefit some groups over others. A private company that collects data on road use but is forced to turn it over to the state loses the monopolistic benefits it might gain from selling that data even as the state benefits, and vice versa.
- New knowledge builds on existing knowledge.
The creation of new knowledge invariably builds on existing knowledge, be it a well-footnoted textbook or a patented algorithm. This reality explains why intellectual property laws are always limited in time and scope, as we will see in Week 3. Failure to include these safety valves would provide current owners of knowledge with a de facto monopoly over the creation of new knowledge. Following from this observation, we can conclude that:
- Those who control the definition, creation, and use of knowledge also control the future direction and development of knowledge.
As a result, the control of knowledge shapes not only the economic development of society (e.g., by determining what new technologies get produced), but also its social, cultural and ideological development (e.g., by shaping who gets to tell what stories, and what stories get told).
- A society based on the exploitation of knowledge requires constant surveillance in order to function properly and efficiently.
A data-driven economy implies that the activities from which data are being extracted must first be monitored. Non-monitoring results in a loss of efficiency. In a competitive environment, for example, companies seeking maximum efficiency will be driven to maximize their surveillance of workers and production processes lest their competitors get the upper hand via more-intensive monitoring, as we will see in Week 9. Similarly, with respect to intellectual property, any unauthorized uses of IP imply a potential loss for the IP owner, which explains the enduring interest by copyright and trademark owners in coercing internet intermediaries such as Google to surveil their users for IP infringement. This is not only an economic issue; even liberal-democratic states like Canada have engaged in ever-growing surveillance of their citizens. The logic in the security and economic cases is the same: in a knowledge economy, anything less than total surveillance is seen as a potential threat or economic loss.
Three helpful tips
- Knowledge is always partial.
- Data is never unbiased.
- Technology is not a substitute for politics. You can’t tech your way out of politics.