Despite being hailed for its “Don’t be evil” ethos, why does Google, like Facebook, now face the same criticisms of “surveillance capitalism”? Given the identical form of antitrust complaints, what drives Google’s reluctance to conform to Microsoft’s standards, often viewed as the “evil empire” in the earlier technology of computing? Amazon, touted as “the most customer-centric company on earth,” has seemingly abandoned its self-proclaimed ethos by injecting ads into its search results, prioritizing commercial placements ahead of consumer-driven outcomes that its natural algorithms would typically recommend.
While exploring the notion of financial rents, specific attention should be given to the types of rents that corporations collect at various stages of the technology industry’s business cycle. While the economics literature is replete with nuanced categorizations of rent types, for the purposes of this text, it suffices to distill them into two primary categories: “rising tide rents” that foster societal prosperity by encouraging innovation and market development; and “robber baron rents,” which disproportionately benefit those wielding power.
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What Is Financial Lease?
Financial rents arise from asymmetries in ownership, information, or power, generating revenue exceeding an aggressive market rate, distinct from abnormal hires that involve momentary use of property for which a fee is paid.
As economists Mariana Mazzucato and Josh Ryan-Collins argue, “When the returns earned by an actor exceed their value-creating contributions, the distinction can be framed as rent rather than reward.” The potential explanations for this phenomenon include the existence of a rare resource, the development of monopolistic conditions yielding higher returns within a specific industry, or investment choices directly or indirectly benefiting a particular group with interests.
Consider the complexity of drug pricing in particular. Patents, a government-granted incentive for innovation, enable pharmaceutical companies to shield their products from competition and recoup investments through higher pricing. As patent protections lapse, generic versions of medications may emerge, potentially driving down their value. The significance of this valuation disparity, as well as its profound impact on pharmaceutical companies’ profitability, underscores the magnitude of the issue at hand.
In twentieth-century neoliberal economics, the notion of rents has often been viewed as an ephemeral phenomenon that is eventually eroded by market forces. Investments in research and development are a value that we pay for the rising tide of innovation. For classical economists such as Smith, Ricardo, and Mill, who operated within a societal framework characterized by inherited wealth and privilege, the concept of rents has long been associated with a pervasive and persistent manifestation of inequality. At the dawn of economic understanding, agriculture remained the primary source of wealth generation, with a substantial portion of that wealth being extracted from the labor of serfs and tenant farmers, ultimately flowing into the hands of those who controlled the land. As the native baron dispatched his troops to collect what he perceived as his rightful portion of the harvest, there was little choice but to comply. In a profoundly unfair society, the outcomes are determined not by individual endeavour or financial investment, nor even groundbreaking ideas, but rather by entrenched power imbalances rooted in unequal access to resources.
Not every rental property necessarily implies a misuse of power. Innovations, regardless of whether they are safeguarded by patents, commercial secrecy, or merely achieved through swift and agile execution ahead of competitors, present an opportunity to capture a disproportionately large share of earnings until the innovation is disseminated more widely.
As a market leader emerges during a transformative innovation cycle, its success stems from solving novel problems and generating value not only for customers but also for a diverse network of suppliers, partners, and even competitors. As market leaders capture an outsized portion of profits by disrupting traditional industries and dominating emerging markets, the value created tends to be a broad-based phenomenon that benefits all players.
Unfortunately, however, a virtuous rising tide that lifts all boats does not ultimately prevail. As soon as the brand-new market’s expansion slows, powerful innovators find themselves no longer reliant on new user adoption and collective innovation from a thriving ecosystem to sustain their extraordinary revenue levels? As the old economic cycle reaches its final stages, firms at the pinnacle of success turn to extractive tactics, leveraging their market dominance to maintain their accustomed level of profitability in the face of macroeconomic headwinds and competitive pressures that should otherwise be eroding their advantages. As they start to amass robber baron-like rent payments. Companies like Google, Amazon, and Meta are quietly reshaping the digital landscape to their advantage.
The cycle restarts with a fresh cohort of competitors, compelled to pioneer novel, game-changing innovations that redefine the industry. Enter OpenAI, Anthropic, and their kindred spirits.
Consideration is all you want
The supply of huge tech market energy is abundant. What’s the coveted asset that they tightly control and dominate? It’s not our information. The value of the companies we purchase from is irrelevant – they generously offer these services at no additional cost to us. .
In 1971, Herbert Simon, a renowned political scientist, observed that the true cost of information extends beyond the monetary expenses incurred in gathering it – it also encompasses the time devoted to consuming and processing it.
Simon underscored that eventually, information will become so abundant that we’ll need machines to help us manage our attention.
In the digital era, having a keen eye for innovation has undoubtedly been the cornerstone of triumph. Founded on the premise of efficiently locating the most relevant internet webpage from a vast array, Google’s core objective is to swiftly deliver users exactly what they’re searching for and then seamlessly guide them onward. Amazon aims to help customers find the best quality and value among its vast array of over millions of products. Initially, social media thrived on the concept of personalized news curation: offering each individual a tailored stream of updates from the specific connections they had carefully curated. These innovative tools significantly enhance our limited capacity for contemplation, fostering a more eco-friendly approach.
During the early years of web development, major corporations capitalized on solving the eye allocation conundrum, reaping substantial profits from their efforts. As the web expanded exponentially, the sheer volume of accessible information surpassed traditional human capabilities for filtering and curating content, rendering conventional methods obsolete. Machines efficiently allocated considerations, streamlining decision-making processes. Innovations in algorithms for search, suggestions, social media feeds, leisure, and information have spawned a boundless new economic system.
By exploiting the vast amounts of data available to them, the web giants initially achieved success. Google didn’t simply crawl and index each website online, but also analyzed how websites linked to one another, tracked the most popular links, and evaluated which ones drove users back for more exploration or sent them satisfied with their experience. Using location-specific data and historical search patterns allowed for the creation of highly tailored and relevant solutions. Amazon leveraged a comprehensive approach combining value-based product recommendations, individual customer reviews, recognitions, and purchase history to suggest products that best aligned with customers’ needs. In my 2005 essay, I argued that the companies that endured the dot-com crash had evolved to adopt a multifaceted approach or transitioned into specialists adept at harnessing collective intelligence.
Companies like Amazon, Google, and Facebook have cultivated a set of innovative strategies for creating financial value through their businesses, which can be distilled into key takeaways for entrepreneurs seeking to replicate their success.
As time passed, a significant anomaly emerged. As a result, the tech giants have leveraged these proprietary algorithms not for the benefit of their customers and suppliers, but rather to drive self-serving gains. The issue initially became apparent through the proliferation of social media: valuable content was often interspersed with addictive and divisive material designed to keep users engaged and scrolling, thereby generating additional ad revenue opportunities. As Google shifted its focus towards promoting natural search results more prominently, advertising transitioned from a supplementary source of valuable information running parallel to search results to a primary substitute. Amazon arrived belatedly to the party, but once it discovered the value of promotion, it threw its full weight behind the effort. A typical web page of Amazon’s product search results now comprises just 16 advertisements, alongside mere 4 organic outcomes.
By 2010, Google and Amazon remained dominant forces in internet search and e-commerce, respectively, while Meta’s momentum continued to build. However, it was increasingly difficult to ignore the signs that the pace of online growth was beginning to slow. The market was maturing. Between 2000 and 2011, the percentage of US adults who utilized the internet surged from approximately 60% to nearly 80%, reflecting a significant increase in online adoption during this period. By the end of 2012, that percentage had climbed to a remarkable 82%. During the past decade, from 2013 to 2014, a paradigm shift became apparent as the straightforward gains from acquiring new customers started to wane. In Europe, the market experienced a trajectory similar to that of the United States, with profitable penetration ongoing. As for the rest of the world, considerable individual growth still awaited discovery. As behemoths of industry, how must they adapt to maintain the faith of investors, whose expectations are fueled by relentless growth and the promise of ever-rising profits?
Corporations continued to drive innovation. Amazon’s foray into cloud computing, such as its flagship Amazon Web Services (AWS), pioneered massive new market opportunities and a revolutionary business model. As the web giants sought to capitalize on their existing customer bases, they focused on maximizing usage and time spent, ultimately driving increased revenue from loyal users. Companies often achieved this by crafting merchandise that was irretrievably habit-forming, extracting an unfair premium from customers through underhanded tactics. The scourge?
Rapidly accelerating to the present, it’s evident that Amazon has abandoned its pursuit of delivering the most outstanding outcome for its customers. Since introducing its Marketplace model in 2016, Amazon has transitioned into a “pay-to-play” ecosystem where products yielding the greatest returns are those that align with the company’s most profitable interests.
According to Market Pulse’s analysis agency,
It appears that some SEO agencies are implying by “robbing the digital landscape of their competitors” through dubious practices.
The pain inflicted on customers goes beyond mere time wasted while browsing through ads in search of relevant results. At College Faculty London’s Institute for Innovation and Public Policy, my colleagues and I found that consumers still tend to select the top-rated products, even if they’re not necessarily the most relevant or optimal outcomes. Amazon exploits the trust customers have placed in its algorithms, substituting personalized attention and clicks with inferior-quality sponsored content. According to Amazon’s proprietary quality, value, and recognition optimization algorithms, the top-performing sponsored products saw a 17% price increase, while those ranking lower experienced a 33% decline. As product suppliers are forced to compensate Amazon for the ratings they previously garnered through product excellence and reputation, their profits plummet while Amazon’s surge, and expenses escalate as some of the cost is passed on to consumers.
It appears to have stabilised for the time being. As of this autumn, 2023, the company’s latest quarterly results demonstrate a notable 9% increase in online sales revenue year-over-year. Meanwhile, expenses have risen by 20% for third-party vendor companies and a substantial 27% for promotional sales. As historic IBM mainframe monopolies and Microsoft’s dominance over private laptops have crumbled, corporations are now forced to redirect their focus towards creating value or risk decline in the face of emerging, innovative market entrants that offer a new type of value to customers and suppliers reminiscent of Amazon’s early success. The potential impact of an Amazon setback could manifest as either a steady decline or a precipitous drop-off. When does poor product quality and inconsistent shipping damage Amazon’s reputation so severely that customers lose faith in the platform, decrease their purchases, and experience frustration exploring alternative options? Will history repeat itself? It’s likely that Amazon will ultimately raise its rates once more.
A strikingly similar darkened exemplar can be observed in. Since 2011, a promotional strategy has emerged, distinguished by distinct color-coding, gradually gaining prominence while the signals it conveys have become increasingly subtle. On cellular devices, users often need to scroll extensively to reach the top organic search result. While the results are significantly less intrusive compared to those found on Amazon, this is largely due to the fact that a substantial majority of Google searches do not display ads at all. In industrial searches, a satisfying outcome for local businesses, such as a neighborhood service provider, is often only achievable after meticulously navigating through numerous online advertisements from both regional vendors and national chains, requiring a significant amount of time and effort to uncover the most suitable option.
While the harm to customers may appear less severe at Amazon, where algorithms intentionally distort search results, there remain significant concerns. Google and Amazon operate as gatekeepers, exercising control over the visibility of a vast supplier ecosystem within their respective platforms. These suppliers are not merely commodities to be exploited by the platform, but rather entities with their own interests, needs, and goals that must be taken into account. Content creators are its companions in generating the value that draws customers to the platform. Without physical infrastructure, the need for Google’s search capabilities or raw data for its outputs is rendered meaningless; without brick-and-mortar establishments, the very notion of an Amazon-like marketplace becomes obsolete. Similar observations are also applicable to various web custodians. Without the contributions of app developers and users who create and consume content, there would be no App Stores and no social media platforms.
If suppliers are harmed, customers may ultimately suffer as well in the long run? The success of these collaborative ecosystems relies on the platform’s ability to fairly distribute value and recognition to those driving the most impactful results? As platforms replace organic outcomes with paid ones, prioritize their personal agendas, products, or services, or provide information directly to customers at the expense of original creators, the entire ecosystem risks losing its motivation and rewards for continuing to deliver value. As a direct consequence, the diminished value has far-reaching implications for both individual users and the platform as a whole, leading to a catastrophic collapse of the intricate virtuous cycle that once fostered creativity, content gathering, and expert curation.
While the corporation’s efforts at self-improvement may appear laudable, they can inadvertently impede the organization’s overall growth by prioritizing short-term gains over long-term development? Google’s innovations include the development of the Massive Language Model architecture, which serves as the foundation for today’s AI disruptors, including cutting-edge startups. It debuted in 2017 under the enigmatic title “Consideration is All You Want,” but it wasn’t until late 2018 that it launched an open-source implementation, stopping short of building and releasing something akin to OpenAI’s groundbreaking GPT series. Uncertainty surrounds the motivations behind this move: was it a genuine shortage of creative ideas or a strategic ploy? One thing is evident, however – outside observers were acutely aware of the profound impact BERT’s introduction had on Google Search. When I launched my company’s innovative plain language search engine in 2020, leveraging BERT’s technology for content analysis, I was astonished to discover that we could query our own data more effectively than Google itself.
Startups were left to unlock the vast possibilities of generative AI and chatbots.
Will Historical past Repeat Itself?
The notion that the dominance of Amazon and Google is no longer a pressing concern for most consumers. We nostalgically reflect on the excellence of those corporations, mourning their loss of stature. Although we have gradually grown accustomed to the reality that outcomes no longer meet our initial expectations as quickly as they once did.
European and US antitrust authorities have finally taken notice, scrutinizing massive tech corporations’ alleged market dominance abuses with varying degrees of effectiveness. Regulators might pressure higher conduct. Can struggling businesses rise again by learning from their competitors?
Large language models may pose the most formidable competition Google, Amazon, and other established internet powerhouses have faced to date. As users increasingly turn to ChatGPT for answers, it’s becoming clear that its results often pale in comparison to those provided by industry giants like Google and Amazon. Meanwhile, the platform is already fielding inquiries that might have otherwise been directed at a search engine. The initial results often suffer from reduced quality as a characteristic of a nascent disruptive innovation. As a natural progression, it’s essential to address emerging challenges, cater to novel demand, and develop innovative options. As a direct consequence of their innovative approach, their disruptions come in the form of. Their primary objective is to consistently surprise and thrill their clientele, with a relentless focus on crafting unparalleled value from the outset. As mature and declining corporations confront the challenge of extracting value from their assets, they often inadvertently undermine their product offerings. When companies abandon their core values and unique perspectives, they risk losing the trust of their customers and partners, creating an opportunity for competitors to fill the void.
We find ourselves at the beginning of a new era, once again. Effective management involves creating the greatest value for the largest number of customers. Once market consolidation has taken place, the process of extracting value actually commences. As the market continues to evolve, it is likely that traditional extractive practices will regain popularity among innovative market leaders. Will these entrenched players leverage their market muscle to safeguard their accustomed profit levels in the face of macroeconomic headwinds and intensifying competition that’s eroding their dominance?
As regulatory bodies increasingly strive to stay ahead of emerging trends, they must be prepared to adapt and evolve in tandem with the industries they oversee. Current advancements in algorithmic governance enable surveillance over consumers, influencing what they discover, view, buy, connect with, and perceive. Subsequent technologies will significantly enhance human cognition, creativity, and interaction.
While the majority of discussions around AI focus on its technological prowess and potential to surpass human control, there is a lack of consideration for the broader implications of AI development. As concerns about global security evolve, contemporary risk assessments increasingly prioritize social threats such as bias, misinformation, and hate speech, alongside the potential proliferation of conventional and nuclear capabilities.
However, deeply rooted within the financial objectives of organizations managing and overseeing AI initiatives lies a complex web of expectations. Will AI corporations remain immune from the same incentives that have driven present tech giants to prioritize their customers and suppliers, leading financial institutions to peddle toxic assets, pharmaceutical companies to promote opioids, tobacco firms to conceal health risks, and oil companies to deny climate change? I feel not.
Rather than attributing the company’s ethical lapses to the shortcomings of its leadership, consider the financial motivators that drive public corporations’ decisions. Financial markets, along with corporate investors evaluating the performance of their portfolio companies, generously compensate firms handsomely for exceptional growth in revenue and earnings, while mercilessly punishing any signs of stagnation. As inventory choices form a significant component of government compensation, as well as corporate compensation in Silicon Valley, underperforming on expected progress incurs an extremely high cost for both company management and employees.
It’s premature to determine the optimal approach to govern AI. However one factor is definite. . Corporations often veil financial abuses in plain sight, concealing them for years until whistleblowers, researchers, regulators, and attorneys can uncover the truth behind the companies’ denials. That’s likely to be even truer for an enigmatic dark field like AI.
AI security and governance are inherently linked to the establishment of robust and continuous mechanisms for transparency and accountability. To achieve socially beneficial consequences, developers of AI models and utilities must clearly define metrics that specifically aim to promote such outcomes, then meticulously measure and publicly disclose their attainment. Rather than highlighting non-technical summaries of mannequin capabilities, these metrics should focus on the business’s utilization of AI, including the processes and metrics used to mitigate the risks that have been identified.
As the AI development cycle reaches its virtuous stage of innovation, a prime opportunity exists to implement regulatory measures, with market dynamics currently favouring exploration and collaboration between AI builders, regulatory bodies, and industry stakeholders. It is crucial to recognize what constitutes “good” as corporations continue to prioritize growth, striving to delight customers, suppliers, and society alike; thus, if or when incentives to exploit others prevail, we can reflect on how and when things began to unravel.
Let’s not wait until the robber barons are at our gates once more.
