Abstract
Social media is a mega-industry built by systematically monetizing the exploitation of human emotions, reactions, and biases. The authors explain how this industry became so profitable by creating a fear of missing out (FOMO) to command our attention, blending news and content in one feed to keep users 'in-app', and using powerful algorithms to promote more provocative posts, filter content, and trigger the reward centres of our brains. The authors examine how decentralized technologies, including cryptocurrencies, tokenization, and blockchain are being developed and deployed into new social media applications. The authors speculate on how these blockchain-backed startups could challenge the status quo and appeal to new expectations of user privacy, tighter regulation, and a more equitable monetization system.
TopIntroduction
The most successful social media companies have extraordinary abilities to extend usage and extract user data without causing alarm. They have profited from what has been called surveillance capitalism. Successful social media companies do not charge users for access as they make their money downstream from providing targeted advertising.
The plain truth is that it is not feasible for a Social Media business to make significant revenues without harvesting user data, predicting preferences and behavior, and using these insights to sell target advertisements. Just as Google is not merely a search engine; it is a digital concierge service attempting to anticipate our requests or interests; Facebook is not a community tool to safely share information and opinions. It is a phenomenally successful tool for monetizing the systematic exploitation of human emotions, reactions, and biases. Social Media is most successful commercially when the information that we, the users, see validates our beliefs and identities. This knowledge has encouraged the platform owners to set their algorithms to promote content that we are most likely to find interesting. This algorithmic practice can create digital content echo chambers that reinforce our opinions and polarize our views. The more we engage with social content, the more personal data we provide to the platform owners. The more data the platform has, the better it can predict our behaviors, intent, and interests. The better these predictions are, the better the value proposition is to advertisers. Facebook has mastered this process; it has grown revenues from $7.87bn in 2013 to $86.7bn in 2020, with 98% of the revenue coming from advertisers. The internet is monopolized by a tiny number of massive corporations. Internet search is essentially wholly controlled by Google, with 90% of search queries going through their data centers. Google's web browser Chrome had a 0.52% market share in 2008, but by 2020 66.59% of desktop and 61.35% of mobile users used it as their default web browser.
Facebook generates 4 petabytes of data per day. Every 60 seconds, 510,000 comments are posted, 293,000 statuses are updated, 4 million posts are liked, and 136,000 photos are uploaded. Google processes over 20 petabytes of data per day, recording every search and every YouTube video watched. Google Maps logs every route and journey.
Google has a centralized data-management strategy, the default strategy for large technology companies. Cloud providers opened 15 million sq. ft of data center space in 2020, and Facebook operates 18 massive data centers in 17 regions. Massive amounts of data require massive amounts of central storage.
History has taught us that too much accountability in a single position of power almost always widens the threat of abuse. As Ben Dickson writes in VentureBeat:
If the servers of these entities go down, we lose access to vital functionality. If they get hacked, we lose our data. If they decide to monetize our data in unlawful ways or hand it over to government agencies, we likely won't learn about it. If they decide to censor or prioritize content based on their interests, we won't be able to do anything about it (Dickson, 2017, para. 4).
Governments around the world are aware of Big Tech data monopolies; they were slow to wake up to this, but once they realized how powerful these companies were becoming, they took steps to try and reduce the control and power the private companies have over user data. Over this decade, global governments will form coalitions with the intent of reclaiming power. The critical role of Governments is to force companies and markets to account for the impact they have on society. Legislations force innovation, and if Governments can successfully force these companies to account for societal impact, they could innovate differently by prioritizing privacy, security, and profit. Technology companies, however, have vast cash reserves and can soak up fines and legal costs for many years to come before we see industry-wide changes.
We may not have to wait, however, for external governance. In the much nearer term, it could be the impact of decentralized technologies powered by blockchain that change the Social Media landscape. Centralized data centers are prone to infiltration, and Web 3.0 is likely to be a decentralized web. A new version of the web that spreads the power load, data, and decision-making across many independent machines.
Dickson (2017) goes on to describe this possibility:
Key Terms in this Chapter
Surveillance Capitalism: A term coined by Shoshana Zuboff in 2014. It describes a market-driven process in which the goods for sale are your personal data captured through mass surveillance of the Internet by means of social platforms and search engines.
Social Network: Websites that allow users to quickly create and share content with each other.
ICO: Stands for initial coin offering, it is a means of crowdfunding that can help start-ups that want to meet short-term financial goals by issuing digital assets called cryptocurrency tokens.
Decentralization: The process of spreading control/authorities/data from centralised governance toward a distributed one.
GDPR: General Data Protection Regulation is a European regulation that governs how companies and other organizations process personal data.
Blockchain: An immutable list of records, called blocks linked each other by means of cryptography.
Bias: The inclination of the mind or a preconceived opinion about something or someone.
Artificial Intelligence: The combined power of available data, algorithms based on learning approaches and computational resources.
Machine Learning: Is a branch of artificial intelligence (AI) and computer science which focuses on the use of algorithms to make inferences from patterns in data.
Tokenization: The process of issuing a blockchain token that digitally represents fractional ownership of a real tradable asset.
XR: Stands for extended realities, it refers to real and virtual world combined realities.
Retargeting: Is a form of online advertising which consists of showing users advertisements based on their previous browsing history on the firm's website.