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Four prominent horsemen of the Biden administration’s bureaucratic apocalypse—the Federal Trade Commission (FTC), U.S. Justice Department (DOJ) Civil Rights Division (DOJ), Consumer Financial Protection Bureau (CFPB), and the U.S. Equal Employment Opportunity Commission (EEOC)—came together April 25 to issue a joint statement pledging vigorous enforcement against illegal activity perpetrated through the use of artificial intelligence (AI) and automated systems.

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It appears that the emergence of ChatGPT and other artificial-intelligence systems has complicated the European Union’s efforts to implement its AI Act, mostly by challenging its underlying assumptions. The proposed regulation seeks to govern a diverse and rapidly growing AI landscape. In reality, however, there is no single thing that can be called “AI.” Instead, the category comprises various software tools that employ different methods to achieve different objectives. The EU’s attempt to cover such a disparate array of subjects under a common regulatory framework is likely to be ill-fitted to achieve its intended goals.

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The European Union dreams of being a leading hub for tech innovation. But it is increasingly clear this is wishful thinking. Heavy-handed regulation is making the bloc inhospitable to innovation, and investors are looking elsewhere. The EU’s recent pushback against ChatGPT is just the latest sign that this is not going to change.

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In an appearance on the Mobile Dev Memo podcast, ICLE Senior Scholar Miko?aj Barczentewicz outlines the legal impact of the EU’s Digital Markets Act and Digital Services Act, with specific attention paid to the digital-advertising market. He also discusses the latest news related to Meta’s recent fine by the Irish DPC for using first-party data without consent to empower personalized advertising, as well as the temporary ban that the Italian DPA enforced on OpenAI’s ChatGPT. The full episode is embedded below.

It seems that large language models (LLMs) are all the rage right now, from Bing’s announcement that it plans to integrate the ChatGPT technology into its search engine to Google’s announcement of its own LLM called “Bard” to Meta’s recent introduction of its Large Language Model Meta AI, or “LLaMA.” Each of these LLMs use artificial intelligence (AI) to create text-based answers to questions.

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ICLE Director of Law & Economics Programs Gus Hurwitz was a guest on The Cyberlaw Podcast to discuss the U.S. Supreme Court’s Gonzalez v. Google LLC case, the court’s first opportunity in a quarter century to construe the limits of Section 230 of the Communications Decency Act.

Other topics included likely U.S. Justice Department challenges to Adobe’s $20 Billion Figma deal and to JetBlue’s proposed acquisition of Spirit; the Federal Trade Commission’s (FTC) proposed ban on noncompete clauses; the FTC’s challenge to the Meta-Within merger; a European Union consultation designed to make U.S. platforms pay more of European telecom networks’ costs; Apple’s progress in devising a blood glucose monitor; and whether artificial intelligence is coming for lawyers’ jobs.

The full episode is embedded below.

Abstract

Artificial Intelligence (“AI”) and machine learning (“ML”) have the potential to create breakthrough advances in a range of industries, but they also raise novel legal, ethical, and privacy questions that will likely define the next era of technological advancement. Over the last several years, there has been a flurry of AI- and ML-related regulations and guidance issued by international bodies, governments, and regulators seeking to mitigate the risks posed by AI and ML, especially when these technologies are used to make important decisions related to employment or healthcare. Given the proliferation of these technologies across various industries, more regulation is likely to come. Organizations with AI and ML-based products and services should understand and consider how existing laws apply to them, as well as how the changing regulatory landscape may impact their business plans going forward. In this article, we discuss the differing approaches to regulating AI and ML in Europe and at the federal and state levels in the United States and the best practices for building compliance.

ICLE Director of Innovation Policy Kristian Stout appeared on the Mornings with Brian Haldane radio show in Baton Rouge, Louisiana, to discuss what the emergence of generative AI systems means for copyright. The full audio is embedded below.

Counter-positioning is a business strategy in which a company positions itself in a way that its competitors are unwilling to replicate to avoid cannibalization. A well-known example of counter-positioning is Netflix’s policy not to charge late fees. In 2000, Blockbuster was earning a large portion of its revenue ($800 million) from late fees. When Netflix entered the market, the company began shipping DVDs to customers’ homes. Customers could pay for up to three DVDs at a time, and if they didn’t return them, Netflix simply wouldn’t send the next one on the list. This strategy caused Blockbuster to eliminate late fees in 2004, i.e., Netflix essentially forced Blockbuster to cannibalize its business model in order to survive.

By integrating ChatGPT, Bing is poised to put Google in a similarly difficult situation. In 2021, Google earned $148.95 billion (out of $256.74 billion) from search ads. The more users click on different results and reformulate requests, the more advertisers are willing to pay to appear at the top… the more Google generates revenue.

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