The concept of ‘Big Tech’ is one that fascinates me – especially given the propensity to which we have come to rely on digital. We’re almost one year into this pandemic and the virus is still rife. As countries around the world bounce in and out of lockdown, there’s no doubt that our devices and their accompanying network connections remain a huge part of what has kept us sane.
But as the UK fast approaches the anniversary of its first national lockdown (please, hold your fanfare…), the moral ‘elephant in the room’ surrounding the growing dominance of Big Tech (a term which generally refers to the likes of Amazon, Apple, Google, Facebook, Twitter and Microsoft – but more on that later on) is almost impossible to ignore.
While the general population have been confined to their homes, tech’s industry juggernauts have been cashing in. It’s no secret that Jeff Bezos, Amazon CEO and founder, raked in a hefty US$70bn in 2020 alone, swelling his net worth to a staggering US$185bn. The global economy may be in tatters, but as of Q3 last year, Amazon’s total profits rose almost 200% on figures from 2019. Given that Bezos now owns more money than any one man could spend in his life, it’s surprising that his company still struggles to uphold safe and fair working conditions for employees – but alas, I digress…
Amazon is by no means the only corporation profiting from the pandemic; Google’s value has surged by 60%, and Facebook’s has grown by 30%. Even Apple, which actually experienced a slight downturn last year, came out the other side with a hearty profit of US$12.7bn.
While we were aware of Big Tech’s industry dominance pre-COVID-19, now the lingering question is whether this oligopoly will come to define the world’s digital future.
One man who has conducted an extensive exploration of the subject is Jean-Philippe Vergne (otherwise known as JP), an associate professor at UCL School of Management who has studied the rise of Big Tech. His recent report, titled Decentralized vs. Distributed Organization: Blockchain, Machine Learning, and the Future of the Digital Platform, deep dives into the impact of these mammoth AI-driven business structures, laying out a series of recommendations to end the supreme authority of technology’s industry heavyweights.
Examining the intersection of technology and organisation, JP aims to provide some perspective for the evolution of capitalist societies. Strangely enough, his interest in tech began with a history of piracy exhibition he visited at the Maritime Museum in ‘old’ Amsterdam around 15 years ago. He’d been reading about pirates in cyberspace just a few days before, and, while at first, he thought that same term – ‘piracy’ – being used in two entirely different contexts was merely a coincidence, he soon began to realise this simply wasn’t the case. Here, he was witnessing evidence of a much deeper pattern at play, involving the development of technology and the intricate ways in which societies form around it.
And thus began his expedition into the influence of Big Tech…
Q.‘Big Tech’ – otherwise known as the ‘Tech Giants’ or the ‘Big Five’ – is a term used to define the most dominant companies in the technology industry, commonly referring to the likes of Amazon, Apple, Google, Facebook and Microsoft. As someone who has extensively researched the topic, how would you define ‘Big Tech’ in your own words and why is the term so significant to society today?
I like your question a lot as it implies that it’s not obvious at all what the term ‘Big Tech’ actually means –and I agree with you. I find the term misleading and I wish we would stop using it. First, it’s unclear why we should consider Amazon to be part of Big Tech but not Alibaba or JD.com. Or why Netflix is sometimes part of the club, but not Tesla. This is not only arbitrary but also reflective of a US-centric view that does not address the big picture issues, which are global.
Second, there are many firms out there that use cutting-edge technology and I don’t see why Silicon Valley should have a monopoly on the use of the ‘tech’ descriptor. For instance, aren’t the firms that came up with the COVID vaccines ‘Tech’ firms? Some of them, such as Pfizer, also happen to be quite ‘Big’!
I’m afraid that the ‘tech firm’ label came about as part of a PR effort by a few digital platform corporations aimed at eschewing regulation. See, if Uber is not a ‘taxi company’ but a ‘tech firm’ instead, it can justify bypassing taxi and limousine regulations.
“I’m afraid that the ‘tech firm’ label came about as part of a PR effort by a few digital platform corporations aimed at eschewing regulation”
Q. How is AI contributing to, or even powering, the industry domination of these corporations?
What do firms misleadingly described as Big Tech have in common? On the one hand, they operate proprietary digital platforms under a centralised corporate structure. For instance, the Facebook Inc. corporation operates, among other digital platforms, Facebook.com, WhatsApp, and Instagram. On the other hand, the ‘tech’ used by these firms is not very diversified; for the most part, we’re talking about software revolving around the implementation of machine learning. Instead of ‘Big Tech’ firms, we should be speaking of ‘machine learning platforms’.
Today, a car manufacturer has to orchestrate a more diverse range of technologies than, say, facebook.com, yet no one on the job market sees working at a car company as ‘tech-y’ enough to be the dream job. Of course, there’s one exception – and that’s Tesla. Its CEO-founder is irreverent, smokes pot on camera, and wants to spend billions building a base on planet Mars…so we might need to update the ‘FAANG’ acronym (referring to the stocks of the five most popular and best-performing American technology companies: Facebook, Amazon, Apple, Netflix and Alphabet – which was formerly known as Google) to welcome Tesla as a new member of the Big Tech club. I’m making propositions – what about FATANG? I heard it means ‘burning hot’ in Mandarin. Perhaps that would be an appropriate name given these firms’ ubiquitous presence in the media and skyrocketing market valuations.
Q. Your research tackles the concept of Decentralised vs Distributed organisations – can you tell us about these business structures and how they have shaped the digital industry?
We fundamentally misunderstood the notion of decentralisation and conflated it with ‘distribution’. Distribution is about dispersing decision-making, whereas decentralisation is about dispersing data, information and knowledge. Something can be distributed without being decentralised. This is in fact how the machine learning platforms mentioned above are organised at the corporate level. Yet, because they have millions of users, they can give the illusion that they promote decentralisation. Ultimately though, they control all the data and aggregate them to derive behavioural predictions then sold to advertisers. It’s a clever business model – and very profitable, too. As users, we don’t control any of the data but we can still make minor decisions online, such as deciding on which ad to click. But this is not decentralisation – a decision-maker without data is just a puppet.
I believe that there is a future for a decentralised Facebook or a decentralised Twitter. In fact, Twitter’s founder has launched a project called Bluesky to build such an alternative. There are also other initiatives out there, such as Mastodon or Steemit.
Q. What makes it so hard for smaller companies in the field to compete with these industry juggernauts?
A digital platform like google.com is a privatised marketplace where users meet advertisers, app developers, merchants and other third parties. Google LLC owns the marketplace and collects data about everyone’s behaviour on the platform. There’s nothing wrong with that – shopping malls are private marketplaces too, after all, and we’re fine with that.
So, where do things become problematic? First, when Google LLC starts collecting data on its platform users’ behaviour when they’re not using the platform. We have a term for this: ‘police work’. I believe that it should remain a prerogative of the sovereign state.
The second issue is having Google LLC use the data collected from their paying customers (say, firms wishing to advertise for new smartphones) to launch and promote competing products (say, a Google smartphone). Imagine a fashion retailer leasing space at a shopping mall only to find out, a few months down the road, that the better retail location just across the food court is now a store for a new fashion brand launched by the shopping mall corporation itself…and not only that, but to optimise their product mix and sales revenue, they’re using data on your customers; for example, data on their browsing behaviour when they visit your store, collected via CCTV with facial recognition and microphones embedded within the walls of the mall. Uh-oh – no wonder the small retailers keep losing and the shopping mall keeps winning.
Q. What does the dominance of Big Tech mean for the education technology sector, specifically?
Corporations that operate digital platforms and control large datasets on web users are in a very good position to offer educational products. Google Classroom’s user base doubled to over 100 million users during the pandemic. Interestingly, Google also started targeting young adults with new online education products that compete with university offerings. The timing was perfect – they launched just when the perceived value of paying university tuition was at its lowest because campuses were in lockdown.
With education now taking place online, who’s best positioned to deliver it? A university with huge legacy costs that has been reluctant to use digital technology or a platform with digital design and machine learning capabilities? Unlike the former, the latter cannot deliver degrees, but it can deliver credible credentials that will help students get jobs. From this perspective, digital platforms represent a growing threat to universities which, for too long, assumed that tuition fees could keep increasing endlessly.
“Corporations that operate digital platforms and control large datasets on web users are in a very good position to offer educational products. Google Classroom’s user base doubled to over 100 million users during the pandemic”
We are now at a crossroads. One of the world’s oldest higher education technologies, the ‘tenure’ system, is under attack at universities that do not have a global reach. The unbundling of research and teaching into decomposable components that can be digitised will put increasing pressure on universities. Many will be tempted to partner with technology companies to improve content delivery. This is appealing and represents a great opportunity. At the same time, universities should be very careful not to give access to student data to their technology partners or they risk ending up like the fashion retailer in the shopping mall with spying walls!
“The unbundling of research and teaching into decomposable components that can be digitised will put increasing pressure on universities. Many will be tempted to partner with technology companies to improve content delivery”
Q. Why have government policies failed to address the Big Tech oligopoly?
Machine learning platforms are an instrument of political power and geopolitical influence. The revelations of Edward Snowden in 2013 and others since then, including in places like China, India, Myanmar and Brazil all point to the mutual interests existing between these firms and politicians in power. To threaten a firm with new regulation can be very valuable for a politician, as long as the firm agrees to share data on citizens with the government and circulate biased political views, propaganda for the ruling party, fake news, and conspiracy theories (from bad to worse). There is no need, in this context, to act upon that threat. The regulatory status quo can go on and on.
“To threaten a firm with new regulation can be very valuable for a politician, as long as the firm agrees to share data on citizens with the government and circulate biased political views…”
Q. In your research, you state the case for the business applications of blockchain and AI as a potential solution to the sovereignty of these organisations. How exactly do you think these tools should be harnessed to benefit the industry at large?
Blockchain technology has the potential to remedy the excessive centralisation of data by making every user in a digital network a ‘root’ user with equal access rights to information as everyone else. The promise of this idea has been demonstrated by the tremendous success of such decentralised platforms as Bitcoin and Ethereum.
However, blockchain technology is not yet ripe. Recently, a prominent Ethereum community contributor emailed me a question about my recent research, pushing me to clarify how one could measure the extent of decentralisation within digital platforms. This is crucial because regulatory doctrine is potentially evolving toward having more flexible rules for decentralised platforms, relative to centralised ones. That’s why we need to find a reliable way to measure decentralisation. But it’s tough. I haven’t replied yet to that email because I’m still thinking about my answer…we need more work on this if it’s ever going to be leverage-able by a regulator.
“Blockchain technology has the potential to remedy the excessive centralisation of data by making every user in a digital network a ‘root’ user with equal access rights to information as everyone else”
Q. You believe that disbanding these companies would do more harm to the sector than good – can you explain the reasoning behind this?
Deciding to disband Google in 2025 at the end of a lengthy court case would be about as arbitrary as the decision to suspend Donald Trump’s Twitter account earlier this month (January 2021). Can such a decision serve as the foundation for consistent and sustainable public policy going forward? I don’t believe so.
The core resource for digital platforms is data. Regulation should thus take place at the data level (e.g. Who can collect data and how? Where is it stored? Who has access and what for?). Breaking up a corporation to make an example is no substitute for a much-needed regulatory overhaul. The idea that the 1890 Sherman Act at the heart of US antitrust policy should be our guide for regulating machine learning platforms in 2021 is simply uncanny.
“The core resource for digital platforms is data. Regulation should thus take place at the data level”
More generally, thinking about global digital platform regulation in the 21st century through the sole lens of US law (1st Amendment, section 230, Sherman Act) is narrow-minded. More than 95% of web users are not based in the US. Most platforms are not US platforms. Perhaps more importantly, we no longer live under the illusion that the standards that shape the exercise of democracy in the US provide a universal template that everyone else should wish to copy-paste.
When I hear experts genuinely interested in balancing free speech with privacy referring to US law at the start of every sentence, I wonder: “Are they here to have a scholarly face-off with their US friends from law school or are they here to think about the future of democracy?”. These are two different goals requiring two different conversational frames. Digital platforms are global so we must think beyond the peculiarities of national legal systems. This is what EU countries and China have started doing.
Q. In your report, you pen four key recommendations to ‘level the playing field’ across the tech industry, which are:
Regulate data from the bottom up
Establishing a platform utility regulation
Education must keep pace with technology
Homing in on your fourth recommendation, why is this so important and how do you advise businesses and educators alike to action this process?
New technology is scary and learning about it is a lot of work. It’s easy to act grumpy and complain about it or to find excuses for oneself (“I’m too old for this”). But technologies like blockchain and AI are not going away – technology is never going away (except for commercial supersonic air travel apparently, which went away in 2003 with the retirement of the Concorde aircraft)! Therefore, it’s safe to assume that we will all have to learn. Education is fundamental.
There are two sides to the education ‘coin’: ‘Edech’ and ‘Tech in Ed’. The former means leveraging digital technology to create and deliver educational content in more engaging ways. The latter means exposing students to new technology as part of their curriculum.
One of the most exciting classes I ever taught was back in early 2014, when I first delivered a new module about cryptocurrency at Ivey Business School. I recall asking every student to pull out their smartphone and download a free crypto wallet app. Then I showed students, using my own phone with the screen on display, how to generate a public-private key pair to receive bitcoin. I then transferred a couple of dollars to the student closest to me and asked them to “pass it on” by transferring most of the balance to the next student, and so on. At the end of the class, every student had used a cryptocurrency wallet, received bitcoin or litecoin inside it, and transferred some to someone else. To this day, I still get emails from former students who recall this experience. Some of them went on to work in the nascent blockchain industry and might have felt a bit more comfortable doing so because of that prior educational experience. That’s why I value bringing new technology to the classroom.
A fantastic initiative that brings ‘Tech in Ed’ and ‘Edtech’ together is UNICEF’s Crypto Fund school connectivity project. On the one hand, they use donations in cryptocurrency to fund digital connectivity in the classroom in such countries as Sierra Leone and Kazakhstan. On the other hand, they use blockchain technology to create accountability and transparency in the donation’s lifecycle, with the hope that it will make future donations more likely.
One thing to keep in mind when it comes to ‘Edtech’ and ‘Tech in Ed’ is neutrality. As an instructor, my role is not to promote this or that technology. My role is to promote knowledge. I don’t tell students “buy bitcoin”. I ask them “how might blockchain technology be used and how could that change the world as we know it?”. That’s a very different process from “instructor activism”, whereby a professor shows up, tells students “this is good and that is bad” based on some value judgment. It’s an important distinction.
“As an instructor, my role is not to promote this or that technology. My role is to promote knowledge”
Q. In an ideal world, and given everything uncovered in your research, where would you like the tech industry to be in 5–10 years’ time?
I would like for tech to be allowed to remain ‘small’ and swarm-like, for those of us who need or want it to be this way. One of my new year’s resolutions going into 2021 was to curb drastically my dependence on digital platform businesses where ‘you are the product’, as the stereotype goes. I’ve managed to live happily without relying on facebook.com, Google Search, or Gmail, but it hasn’t been an easy transition! I use Signal and I still use WhatsApp (may the Lord forgive me) – because it’s end-to-end encrypted, and since I don’t have a Facebook account the metadata can be shared with, I don’t feel so trapped.
In an ideal world, we’d want WhatsApp to interoperate with other messaging systems, such as Signal. With appropriate regulation aimed at enhancing human welfare, we would create the conditions to have more platforms à la Signal, powered by open source and fewer billion-dollar machine learning models à la Facebook ads…
Today, the regulator is the most important person in the room to help us get there.
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