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Generative AI as a New Platform for Applications Development
Preprints and early-stage research may not have been peer reviewed yet.
Tracing the trajectories of several semiconductor manufacturers.
Computers are the catalyst for bigger changes.
Assessing the ascent of NVIDIA.
How data-network effects create opportunities and inflate expectations.
This article explores some of the critical challenges facing self-regulation and the regulatory environment for digital platforms. We examine several historical examples of firms and industries that attempted self-regulation before the Internet. All dealt with similar challenges involving multiple market actors and potentially harmful content or bias in search results: movies and video games, radio and television advertising, and computerized airline reservation systems. We follow this historical discussion with examples of digital platforms in the Internet era that have proven problematic in similar ways, with growing calls for government intervention through sectoral regulation and content controls. We end with some general guidelines for when and how specific types of platform businesses might self-regulate more effectively. Although our sample is small and exploratory, the research suggests that a combination of self-regulation and credible threats of government regulation may yield the best results. We also note that effective self-regulation need not happen exclusively at the level of the firm. When it is in their collective self-interest, as occurred before the Internet era, coalitions of firms within the same market and with similar business models may agree to abide by a jointly accepted set of rules or codes of conduct.
Tracing the trajectory of management and engineering decisions resulting in systemic catastrophe.
Amazon is the titan of twenty-first century commerce. In addition to being a retailer, it is now a marketing platform, a delivery and logistics network, a payment service, a credit lender, an auction house, a major book publisher, a producer of television and films, a fashion designer, a hardware manufacturer, and a leading host of cloud server space. Although Amazon has clocked staggering growth, it generates meager profits, choosing to price below-cost and expand widely instead. Through this strategy, the company has positioned itself at the center of ecommerce and now serves as essential infrastructure for a host of other businesses that depend upon it. Elements of the firm’s structure and conduct pose anticompetitive concerns—yet it has escaped antitrust scrutiny. This Note argues that the current framework in antitrust—specifically its pegging competition to “consumer welfare,” defined as short-term price effects—is unequipped to capture the architecture of market power in the modern economy. We cannot cognize the potential harms to competition posed by Amazon’s dominance if we measure competition primarily through price and output. Specifically, current doctrine underappreciates the risk of predatory pricing and how integration across distinct business lines may prove anticompetitive. These concerns are heightened in the context of online platforms for two reasons. First, the economics of platform markets create incentives for a company to pursue growth over profits, a strategy that investors have rewarded. Under these conditions, predatory pricing becomes highly rational—even as existing doctrine treats it as irrational and therefore implausible. Second, because online platforms serve as critical intermediaries, integrating across business lines positions these platforms to control the essential infrastructure on which their rivals depend. This dual role also enables a platform to exploit information collected on companies using its services to undermine them as competitors. This Note maps out facets of Amazon’s dominance. Doing so enables us to make sense of its business strategy, illuminates anticompetitive aspects of Amazon’s structure and conduct, and underscores deficiencies in current doctrine. The Note closes by considering two potential regimes for addressing Amazon’s power: restoring traditional antitrust and competition policy principles or applying common carrier obligations and duties.
If you listed the blockbuster products and services that have redefined the global business landscape, you'd find that many of them tie together two distinct groups of users in a network. Case in point: The most important innovation in financial services since World War II is almost certainly the credit card, which links consumers and merchants. The list would also include newspapers, HMOs, and computer operating systems-all of which serve what economists call two-sided markets or networks. Newspapers,for instance, bring together subscribers and advertisers; HMOs link patients to a web of health care providers and vice versa; operating systems connect computer users and application developers. Two-sided networks differ from traditional value chains in a fundamental way. In the traditional system, value moves from left to right: To the left of the company is cost; to the right is revenue. In two-sided networks, cost and revenue are both to the left and to the right, because the "platform" has a distinct group of users on each side. The platform product or service incurs costs in serving both groups and can collect revenue from each, although one side is often subsidized. Because of what economists call "network effects," these platform products enjoy increasing returns to scale, which explains their extraordinary impact. Yet most firms still struggle to establish and sustain their platforms. Their failures are rooted in a common mistake: In creating strategies for two-sided networks, managers typically rely on assumptions and paradigms that apply to products without network effects. As a result, they make many decisions that are wholly inappropriate for the economics of their industries. In this article, the authors draw on recent theoretical work to guide executives negotiating the challenges of two-sided networks.
This initial idea for this paper was to build on Michael A. Cusumano
This initial idea for this paper was to build on Michael A. Cusumano, "Generative AI as a New
Innovation Platform," Communications of the ACM 66, no. 10 (October 2023), 18-21. ↩
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