What we don’t talk about when we talk about ‘Big Tech’

We need to consider framework of free vs monetized products & business vs political problems to better understand & deal with large tech companies

While the world speculates what a Biden administration is likely to look like, those in the technology space, including journalists and researchers, seem to agree that the severe scrutiny of ‘Big Tech’ companies, Amazon, Apple, Google, and Facebook, is likely to continue. As veteran Silicon Valley journalist Casey Newton asserts on the Ezra Klein Show, a heavy-handed approach to regulating Big Tech, through severe antitrust enforcement, enjoys bipartisan support in the US.

Soon, India too will have to wrestle with the issue of regulating these Big Tech companies, which present not only economic challenges but also pose uncomfortable questions about democracy, freedom, and privacy. In addition to the aforementioned ‘global’ Tech Giants, India is likely to face the challenge of ‘domestic’ Big Tech, given the unprecedented rise of Jio. While the economics and politics of regulating Tech firms is a quagmire that India must tread carefully, it should start by contemplating language.

Ferdinand de Saussure, the father of modern linguistics, was the first to articulate the now obvious insight that human language is not merely a passive carrier of information, like radio waves, but is, in fact, an active interplay of signs and symbols that contaminates the information it carries. Language does not merely communicate the reality we experience but also shapes our perception of that reality, often reinforcing stereotypes and implicit biases.

This is precisely why terms like “terrorist”, “insurgent”, “militant” and “freedom fighter” are fraught with political and ideological subjectivity. Therefore it is difficult for those who are used to thinking of certain people as freedom fighters to even begin to consider that that same person could be a terrorist for others. Yet, for a policymaker, journalist, or researcher, it is important to identify these implicit biases and avoid letting them influence their decision making.

Thus, when thinking about regulating ‘Big Tech’, it is necessary to recognize the implicit assumptions at the heart of the term. To my mind, in addition to being a restrictive term that paints select companies as public enemy number one while ignoring grave challenges posed by other platforms like Twitter, 4chan, and Reddit, there are two misleading implicit assumptions at the heart of ‘Big Tech’: 1) That these tech firms are ‘Big’ monopolies and 2) That they are somehow similar and equal to each other.

Stop moaning about monopolies

The first implicit assumption, that these tech firms are monopolies, stems from the ‘Big’ in ‘Big Tech’. Perhaps the greatest challenge for policymakers thinking about technology is to avoid thinking about novel technologies and business models as an extension of past and present frameworks of thought. In Future Politics, a brilliant book that marries political theory with technology, author James Susskind presents the following quote from Henry Ford talking about cars: “If I had asked people what they wanted, they would have said faster horses.” This “faster-horses” thinking repackages the century-old “break up a monopoly” intervention that was enforced on Standard Oil in 1911 as a solution for the less-than-ideal business practices of tech firms.

Indeed, it isn’t self-evident that these companies are really monopolies. Consider Facebook. If we were to think of Facebook simply as a “social networking” site, it can appear to be a monopoly, since it owns Instagram, and is several times larger than Snapchat and Twitter. Yet, this is untrue. Unlike Standard Oil, Facebook does not compete for your money. It competes for your attention. Seen in this way, everything from your spouse to the dozens of unread books in your library are Facebook’s competitors. Facebook, therefore, does not see itself as a monopoly and is rather insecure about its primacy as a social networking giant. I am sure if one were to plot a graph of various products that require our attention, Facebook will not come out on top.

Facebook’s business model is predicated on keeping the user hooked to the app for as long as possible, and yet, given the blessing of capitalism, there are just far too many things today that demand our attention. In order to better regulate Facebook, policymakers must first understand the insecurity at the heart of its business model. All of Facebook’s problems are a product of this insecurity, and thinking of it as a monopoly solves none of them. But even if one were to consider narrow categories and use analogue modes of thinking, TikTok’s spectacular rise in 2018-19 is enough evidence for the fact that Facebook does not enjoy a monopoly even within the narrow category of social networking/social media platforms.

Similarly, Google’s search engine is perhaps closer to a classical monopoly. But the same cannot be said of YouTube. While Youtube is much bigger than Vimeo, it is also in competition with Facebook, Netflix, Amazon Prime Video, and whatnot.

Big Tech is not a singular entity

This brings me to the second implicit assumption, which stems from the “tech” in “Big Tech”. When we use the term “Big Tech” without qualification, we run the risk of thinking of Apple, Amazon, Facebook and Google as more-or-less similar companies operating in a more-or-less similar fashion, and requiring more-or-less similar regulation. But as Rahul Matthan points out different tech products and platforms require different kinds of regulation.

For instance, Amazon and Facebook are fundamentally different companies, presenting very different kinds of regulatory challenges. The only thing they have in common is our inability to comprehend the millions of lines of code that enable their near-magical functionalities. That is not sufficient reason to shove them into the same ‘Big Tech’ bucket.

The major challenge present by Amazon is the lack of platform neutrality as it is both a platform that connects buyers and sellers and a seller on the platform (through AmazonBasics). This is a business problem. On the other hand, the challenge presented by Facebook is rooted in business but has political implications. As I have pointed out in the previous section, Facebook’s business model is contingent on keeping a user on the app for as long as possible. Its algorithms create echo chambers, and reward increasingly extreme content, feeding into base human instincts of tribalism and black-and-white thinking in order to keep the user engaged. While Amazon’s problem can still be characterised as an antitrust one, it is near impossible to do so for Facebook. If anything, bringing an antitrust case against Facebook, and breaking it into several companies is likely to accentuate its insecurity and push it to reward more extreme content in order to keep users engaged.

With Apple, similarly, the problem is largely a business one, as underlined by Epic Games’ lawsuit against it. Apple’s 30 per cent commission rule on all app purchases done on its AppStore fits the framework of antitrust more neatly, while Google presents both business (Google’s search monopoly) and political problems (YouTube’s algorithm). Moreover, both Amazon and Apple are not ‘free services’, and expect users to spend money, while Facebook and Google derive most of their revenue by offering ‘free services’ and hence have very different incentives driving them. This nuance is lost when we simply use ‘Big Tech’ to describe these companies. Sorting tech companies by a 2x2 framework of free vs monetized products and business vs political problems seems much more useful than sorting them by size.

If we begin thinking critically about the language we use to describe our worldviews and communicate our opinions, it will become clear that at the heart of polarisation and poor policy decisions, are the failure of communication, and the ambiguity of language. Perhaps too much damage has already been done in other areas, but in technology policy at least, there is still time to mend them. Let us start by not sorting tech companies by their size and using a one-term-fits-all approach to describe them.

(Atish Padhy is a student of the Technology and Policy programme at The Takshashila Institution)

Disclaimer: The views expressed above are the author’s own. They do not necessarily reflect the views of DH.