Anti-Social Media Platforms & The Erosion of Democracy and Social Justice
(Or, why surveillance capitalism is bad for you and the world)
Part 1 of 3
“Social media, once an enabler, is now the destroyer, building division—‘us against them’ thinking— into the design of their platforms…. It’s time to end the whack-a-mole approach of the technology platforms to fix what they have broken,” – Rappler CEO Maria Ressa
“The past years have offered a wake-up call for those who needed it….Without explicit and enforceable safeguards, the technologies promised to advance democracy will prove to be the ones that undermine it. It is now vital that democracy is made more resilient,” – Marietje Schaake. former EU parliamentarian
Most people, historically, have been alarmed by intrusions of government and its spying into the lives of ordinary citizens. But, while our attentions have been fixated on this, we ‘dropped the ball’ on the far more invasive mining and use of personal data by the large companies we, all of us, have connections to, however deep and pervasive or fleeting and sporadic.
In 2014, based upon the rising amount of captured data large companies, led by “social media” companies, were beginning to harvest and utilize, Shoshana Zubroff coined the term “surveillance capitalism” to describe this mountain of personal data accumulating in staggering quantity each year. It is a business model predicated on harvesting the online user experience and then manipulating human behavior for monetization, that is, a basic move from processing internal to mining external data, a handy and lucrative convergence of enterprise and consumer IT. Now, many of these mega-companies generate more revenue and exercise more power that all but a handful of the world’s nations.
In 2016 the World Economic Forum (the group that meets in Davos every year) reported that of the world’s top 100 global economic entities, (measuring revenue, not GDP) 69 were corporations – meaning only 31 were countries. Here, in order, were the top 10 entries:
- USA
- P.R. China
- Germany
- Japan
- France
- United Kingdom
- Italy
- Brazil
- Canada
- Walmart
This list might strike the sobering thought that economic powerhouses like South Korea, Russia, Switzerland and others were, in fact, further down the list. The trend continues so that by 2018 157 of the top 200 world economic entities by revenue were corporations, not countries.
Here were the top 10 companies in 2016 with their world economic ranking by revenue in parenthesis:
- Walmart (10)
- State Grid (14) [a Chinese company]
- China National Petroleum (15)
- Sinopec Group (16)
- Royal Dutch Shell (18)
- Exxon Mobil (221)
- Volkswagon (22)
- Toyota Motor (23)
- Apple (25)
- BP (27)
Now, for a 2020 country update, using International Monetary Fund data: USA and China are still top dogs, Japan and Germany switched positions, India made an appearance at spot #5, UK and France swapped lanes, followed by the same three, Italy, Brazil Canada, as in 2016. Rounding out the next ten countries – but not revenue generation when companies are tossed into the mix, are Russia, South Korea, Spain, Australia, Mexico, Indonesia, Netherlands, Saudi Arabia, Turkey and Switzerland.
Showing it is difficult to break into the top 20 countries is the fact that 17 of these top 20 were also on the list in 1980, that is, 40 years ago.
For a 2020 update on companies (from Fortune 500 data) we have:
- Walmart
- Sinopec Group
- State Grid
- China National Petroleum
- Royal Dutch Shell
- Saudi Aramco
- Volkswagon
- BP
- Amazon.com
- Toyota Motor
So why are these figures important? Ah… I am pleased you asked.
For one, it means that many sovereign nations cannot rein in companies engaging in bad behaviour within their borders – even if and when they have the desire. Chevron in the Peruvian Amazon comes to mind. Oil exploration is a dirty business and when little recoverable amounts are found there is still a mess to clean up – or not. In a place like the Amazon who is going to see the contamination other than indigenous locals?
But the issues I am getting to here are more about the so-called ‘social media’ giants, companies we used to think of as having a clean footprint.
In the early years of the internet revolution early adopters of the technology bought into services billed as connecting/informing us at the speed of the electron, prepping us for our lives in the 21st century. These services were, in the main, offered for free as companies, including newsrooms, tried to figure out how to monetize their products. The few ads we would see were bothersome but easy to ignore, especially as they lacked personal focus and sophisticated tracking technology. It reminds me of the early hype of the energy companies with their mascot Ready Kilowatt and the 1954 statement of Lewis Strauss, then chairman of the United States Atomic Energy Commission, with his alluring, sloganeering promise to the National Association of Science Writers: “electrical energy too cheap to meter!” – a good example of what we now know as “overpromising & underdelivering.”
In less than twenty years internet coding wizards have made stratospheric leaps and small startups have combined, morphed and advanced into extremely sophisticated entities. At the same time we have come to recognize there is a dark underbelly bolstering the magical kingdom of all-connection, all-the-time. A 24/7 existence, like so much of life’s general intrusions, is a two-edged sword.
I think of surveillance capitalism as a natural outgrowth of a technology and life forewarned in 1956 by the brilliant, if troubled, science fiction writer Philip K. Dick. In his novella (made famous by the Spielberg movie) “The Minority Report” three mutants foresee a person’s propensity for committing a ‘future crime’. Their prescience determines the future and freedom, or lack thereof, of ordinary citizen’s based upon criminal actions before they happen. In the same way, surveillance capitalism attempts to predict our future voting, movie-going, book-reading, food shopping, sexual preference… well… all behavior and, subsequently, influence that behavior in a semi-predictable manner, that is, move us toward a specific purchase.
If not a purchase exactly, then other economic considerations come into play. A good example is the selling of ‘spit’ data from the genealogical work performed by the company 23 & Me, a noted seller of DNA info to ‘third parties’. They caused a minor tremor in 2018 when they announced the sharing of consumers’ anonymized genetic data with pharmaceutical giant GlaxoSmithKline. Sharing is, of course, a euphemism for ‘selling’; in this case GSK shared $300-million. While it is hopeful that people with inheritable genetic diseases may well benefit from this deal in the form of future medicines, data security is never distant from my mind, especially as data security is, it appears, never in all ways, secure all the time. Do you really want your health insurance company (who has always been a gatherer of data that could be used in health/mortality actuarial practice) rescinding your coverage because you have a 35% chance of getting motor neuron disease or some other ailment?
Two years ago I was sitting with a friend talking about his new Maserati. An hour later an ad for Maserati popped up on my mobile phone browser during a search for something totally unrelated to cars. That is when I discovered that Google has a division with a huge number of employees developing, listening in and then tweaking their speech and voice components for their algorithms. Turn off your microphones! Siri and Alexa are you listening? (Being highly open to suggestion, I inquired as to whether Google was assisting with monthly car payments but received no answer.)
So, how is all this related to Democracy and Social Justice?
Commercial connections have forever had tentacles entwined with, and embedded into, governmental components. While governments are often slow on the uptake of the new (and, to grant and uphold citizen rights) their bureaucratic nature and love of big data do eventually move the organs of governance to utilize the lessons of commerce. This learning often first makes an appearance to ‘improve’ focus on the big picture of where ‘trouble’ among the rank and file may begin, never mind the trouble may only be citizens engaging in their constitutionally guaranteed rights of assembly and protest.
But, before we go into more detail here let’s sidestep and read a little about the
Big Picture & Big Data
That big picture is assisted by ‘big data‘, a term coined in a 1997 scientific paper by NASA. ‘Big data’ is, by definition, unwieldy. It is defined by Wikipedia (even before the Oxford English Dictionary added it to their list) as “an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications.”
There is a pervasive belief that it is true the more data one accumulates the more answers one has available; that is, quantity is in itself a necessary and sufficient parameter for accurate research. But AnnaLee Saxenian, dean of the UC Berkeley School of Information, one of the leading lights in data and its management, writes that, “We want students and consumers of our research to understand that volume isn’t sufficient to getting good answers… [the] School challenges students in the online Master of Information and Data Science program to approach data with intentionality, beginning with the way they talk about data. They learn to dig deeper by asking basic questions: Where does the data come from? How was it collected and was the process ethical? What kinds of questions can this data set answer, and which can it not?… We run the risk of forgetting why we collect data in the first place: to make our world better through granular details,… The way we talk about data matters, because it shapes the way we think about data. And the ways we apply, fund, and support data today will shape the future of our society.”
The school says this process is part of ‘data science’. A more useful shorthand than big data, the words imply a rigorous approach to analytics and data mining. This view espouses that, “a data set is not so much a painting to be admired but a window to be utilized; scientists use data to see the world and our society’s problems more clearly.”
Another definition of big data, from the McKinsey Global Institute, is “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.” This has been tackled in the past two decades by trimming big data down to size. Data scientists have created new tools for collecting, storing, and analyzing these vast amounts of information. “In some sense, the ‘big’ part has become less compelling,” according to Berkeley’s Saxenian.
A Quick Lesson in Data Volumes: The volume of data in a single file or file system can be described by a unit called a byte. However, data volumes can become very large when dealing with, say, Earth satellite data. Below is a table to explain data volume units (credit Roy Williams, Center for Advanced Computing Research at the California Institute of Technology).
- Kilo- means 1,000; a Kilobyte is one thousand bytes.
- Mega- means 1,000,000; a Megabyte is a million bytes.
- Giga- means 1,000,000,000; a Gigabyte is a billion bytes.
- Tera- means 1,000,000,000,000; a Terabyte is a trillion bytes.
- Peta- means 1,000,000,000,000,000; a Petabyte is 1,000 Terabytes.
- Exa- means 1,000,000,000,000,000,000; an Exabyte is 1,000 Petabytes.
- Zetta- means 1,000,000,000,000,000,000,000; a Zettabyte is 1,000 Exabytes.
- Yotta- means 1,000,000,000,000,000,000,000,000; a Yottabyte is 1,000 Zettabytes
We will return to this later in a discussion of social media algorithms.
Governments have always been nervous about protest of any kind. The validity of such jitters was brought home with the ability of mass movements’ non-violent action in bringing down governments of Warsaw Pact countries and the Soviet Union itself, felling them like phantom dominoes in Southeast Asia. Similar events shook the Islamic countries with the ‘Arab Spring’ uprisings.
Governments like using a scattershot approach to try and corral the proverbial needle in a haystack. Certainly we all want the authorities to catch terrorists seeking to do our country harm. But, is a record of all the telephone calls in the country, in real time, going to assist that endeavor? The ubiquitous use of cellular communications lends itself to lax control even for bad actors. So, as listening to U.S. citizen’s phone calls without a judge’s warrant is illegal, perhaps simply getting a list of all the outgoing and incoming numbers being called by people in the U.S., and the duration of the calls, might be helpful? It is that word ‘might’ that bothers me. I’ve no problem with law enforcement requesting and receiving records after an arrest, or the request for a wiretap with probable cause, but the uncontrolled amassing of the 3Vs (volume, variety, velocity – see graph, below) is troubling. A few years ago I was happy to read that when the administration wanted to monitor the mobile phone records of everyone in the United States all the big companies, except for my carrier, T-Mobile, rolled over without requiring probable cause warrants or even administrative subpoenas.
END of Part 1.
Part 2 tomorrow!
