AI & Technology Law

This development highlights a critical tension in AI & Technology Law: the desire for regulatory certainty and stability versus the imperative of fostering innovation through a permissive environment. OpenAI's decision to pause its UK data center project, citing "unfavourable regulatory environment and high energy costs," offers a salient case study for comparative analysis across jurisdictions. **Jurisdictional Comparison and Implications Analysis:** In the **United States**, the approach to AI regulation remains largely sector-specific and voluntary, with a strong emphasis on fostering innovation and market-driven solutions. While executive orders and NIST frameworks provide guidance, comprehensive federal legislation is still nascent. This less prescriptive environment, coupled with competitive energy markets and significant investment incentives, generally makes the US an attractive hub for AI infrastructure development. For legal practitioners, this means navigating a patchwork of state-level data privacy laws (like CCPA) and industry-specific regulations, rather than a unified AI-specific framework, allowing for greater flexibility in deployment but also demanding meticulous compliance with diverse sectoral rules. Conversely, the **European Union** (and by extension, the UK, even post-Brexit, as it often mirrors EU regulatory trends) is leading with a more comprehensive and proactive regulatory stance, exemplified by the AI Act. This forward-looking legislation aims to establish a risk-based framework for AI systems, imposing stringent requirements on high-risk applications. While lauded for its ethical considerations and consumer protection, the OpenAI decision underscores a potential unintended consequence: the perception of increased regulatory burden

This article highlights the critical interplay between regulatory certainty and investment in AI infrastructure, directly impacting practitioners advising AI developers and deployers. OpenAI's pause in its UK data center project due to an "unfavourable regulatory environment" underscores the chilling effect that ambiguous or overly burdensome regulations, such as those potentially arising from the UK's evolving AI Safety Institute's frameworks or future iterations of the EU AI Act's extraterritorial reach, can have on technological advancement and market entry. Practitioners must closely monitor global regulatory developments, especially concerning data governance, AI safety, and compute infrastructure, as these directly influence the feasibility and liability profiles of AI projects.

### **Jurisdictional Comparison & Analytical Commentary on AI-Generated Brand Ambassadors in Legal & Technology Law** This case study of Harvey’s AI-generated brand ambassador campaign highlights divergent regulatory and ethical approaches to synthetic media across jurisdictions. The **U.S.** (where Harvey is based) has no federal restrictions on AI-generated likenesses but faces growing state-level scrutiny (e.g., California’s *Right to Know Act* and proposed AI disclosure laws), whereas **South Korea** enforces strict *personality rights* under its **Civil Act** and **Act on Promotion of Information and Communications Network Utilization and Information Protection**, requiring explicit consent for digital reproductions of deceased individuals. Internationally, the **EU’s AI Act** and proposed **AI Liability Directive** would classify such deepfake marketing as "high-risk" AI, mandating transparency disclosures, while **UNESCO’s ethical AI guidelines** urge caution in commercializing deceased personalities without familial consent. The divergence underscores the need for global harmonization on AI-generated content rights, particularly in sectors like legal tech where trust is paramount. *(Balanced, non-advisory commentary—jurisdictional trends summarized for analytical purposes.)*

### **Expert Analysis of AI-Generated Brand Ambassadors & Liability Implications** This case highlights emerging legal risks in **AI-generated deepfakes and synthetic media**, particularly under **right of publicity laws, false advertising statutes, and product liability frameworks**. While the article humorously frames the issue, practitioners should consider: 1. **Right of Publicity & False Endorsement Risks** – Using AI to resurrect deceased actors (e.g., Jimmy Stewart) may violate **state right-of-publicity laws** (e.g., California’s *Civil Code § 3344*, *Common Law Right of Publicity*) if consent was not obtained from heirs or estates. The **Lanham Act (15 U.S.C. § 1125(a))** could also apply if the AI-generated content misleads consumers about endorsements. 2. **AI Product Liability & Misrepresentation** – If Harvey’s AI-generated content is deemed a **"defective product"** under **Restatement (Third) of Torts § 2(c)** (for failing to meet consumer expectations), users relying on AI-generated legal advice could have claims if errors occur. 3. **FTC & Deceptive Practices Concerns** – The **FTC Act § 5** prohibits deceptive endorsements, and AI-generated personas may trigger scrutiny if they mislead consumers about authenticity. **Precedent to Watch:** *Hart v. Electronic

The article’s impact on AI & Technology Law practice is indirect yet significant, as it underscores the intersection between digital discourse, public sentiment, and regulatory oversight. While Spain’s RFEF and coach Luis de la Fuente’s condemnation of Islamophobic chants reflects a proactive stance by sports authorities to mitigate discriminatory behavior—a trend increasingly mirrored in international sports governance—the U.S. approach tends to prioritize litigation and platform accountability, often invoking Section 230 reforms or First Amendment defenses, whereas South Korea integrates algorithmic monitoring and content-flagging mechanisms under the Framework Act on Information and Communications to address online hate speech. Internationally, the trend toward institutional condemnation (as seen in Spain) aligns with broader UN and FIFA initiatives promoting ethical AI-driven content moderation, suggesting a convergence toward hybrid models combining regulatory enforcement with technological intervention. This evolving jurisprudential landscape demands practitioners to anticipate cross-border compliance, algorithmic bias mitigation, and the role of public institutions in shaping normative digital behavior.

The article implicates broader legal and regulatory frameworks addressing hate speech and discrimination in sports under EU and Spanish law. Specifically, Spain’s Law 19/2007 against violence, racism, xenophobia, and intolerance in sport mandates disciplinary action against discriminatory conduct, aligning with UEFA’s disciplinary protocols. Precedent from the Court of Arbitration for Sport (CAS) in cases like *CAS 2019/A/6120* affirms that discriminatory chants constitute a breach of ethical obligations, potentially triggering sanctions against clubs or federations. Practitioners should note that these incidents trigger both administrative penalties and reputational liability, necessitating proactive compliance with anti-discrimination statutes and monitoring mechanisms at sporting events. The RFEF’s condemnation signals a trend toward institutional accountability, potentially influencing future litigation or regulatory enforcement under Article 12 of the UEFA Disciplinary Regulations.

The recent surge in solar panel sales, particularly in the UK, following the Iran war, has significant implications for the AI & Technology Law practice, particularly in the areas of energy law, intellectual property, and consumer protection. In the US, a similar trend may be observed, with the increasing adoption of renewable energy sources and the growth of the solar panel market. In contrast, Korean law has been actively promoting the development of renewable energy, with a focus on solar and wind power, and has implemented policies to encourage the adoption of green technologies. This trend highlights the need for jurisdictions to revisit and update their laws and regulations to accommodate the rapid growth of the renewable energy sector and the increasing demand for sustainable technologies. In the US, the federal government has implemented policies to promote the adoption of renewable energy, such as the Investment Tax Credit (ITC) for solar and wind energy projects. In contrast, Korean law has been more proactive in promoting the development of renewable energy, with a focus on solar and wind power, and has implemented policies to encourage the adoption of green technologies. Internationally, the Paris Agreement on Climate Change has set a global goal of limiting global warming to well below 2°C and pursuing efforts to limit it to 1.5°C above pre-industrial levels. This has led to a surge in the adoption of renewable energy sources and the growth of the solar panel market. In the context of AI & Technology Law, this trend highlights the need for jurisdictions to develop laws and regulations that

As an AI Liability & Autonomous Systems Expert, I'll provide domain-specific expert analysis of the article's implications for practitioners. The article highlights a surge in demand for solar panels, heat pumps, and electric vehicles (EVs) in the UK, driven by rising oil and gas prices triggered by the US-Israel war with Iran. This development has significant implications for the energy and renewable energy sectors, particularly in the context of product liability and regulatory compliance. **Case Law and Statutory Connections:** 1. The article's focus on the demand for solar panels and other renewable energy sources is relevant to the European Union's Renewable Energy Directive (2018/2001/EU), which sets targets for the share of renewable energy in the EU's energy mix. Practitioners should be aware of the directive's requirements and implications for product liability and regulatory compliance. 2. The surge in demand for EVs and chargers is also relevant to the UK's Electric Vehicle Infrastructure Strategy, which aims to support the growth of the EV market. Practitioners should be aware of the strategy's requirements and implications for product liability and regulatory compliance. 3. The article's discussion of the price volatility of oil and gas markets is relevant to the UK's Energy Act 2013, which regulates the energy market and provides for price controls in certain circumstances. Practitioners should be aware of the act's requirements and implications for product liability and regulatory compliance. **Regulatory Implications:** 1. The

The Nvidia DLSS 5 controversy illustrates a broader intersection of AI-driven innovation and consumer expectations, prompting divergent regulatory and public responses across jurisdictions. In the U.S., the focus tends to center on consumer protection and transparency, with potential scrutiny from the FTC over claims of "photoreal" capabilities and implications for intellectual property rights in generative AI. South Korea, by contrast, may emphasize data privacy and algorithmic accountability under the Personal Information Protection Act, particularly regarding the use of generative AI in content creation. Internationally, frameworks like the EU’s AI Act impose stricter classification of generative AI systems, requiring transparency and risk mitigation, which may influence global adoption strategies. These jurisdictional nuances highlight the necessity for multinational tech firms to navigate layered compliance landscapes while balancing innovation with consumer trust.

Nvidia’s DLSS 5 announcement implicates evolving AI liability frameworks, particularly concerning product liability for autonomous systems. Under U.S. product liability law, manufacturers may be held liable for defects in design or failure to warn if AI-driven features like DLSS 5 misrepresent capabilities or cause unintended consequences—e.g., if the AI-generated graphics mislead consumers about artistic control or realism. Precedents like *In re: DePuy Orthopaedic Pinnacle Hip Implant Products Liability Litigation* underscore the duty to disclose limitations of algorithmic systems. Moreover, regulatory scrutiny may intensify under the FTC’s AI guidance, which mandates transparency in AI claims, potentially exposing Nvidia to enforcement if promotional statements overstate capabilities. Practitioners should counsel clients to document algorithmic decision-making, mitigate overstatement in marketing, and anticipate liability exposure where AI augments or replaces human creative control.

The Chancellor's statement on stopping top British technology firms and scientists from "drifting abroad" has significant implications for AI & Technology Law practice in the UK, particularly in the context of international collaboration and investment. In comparison to the US, which has a more open approach to international collaboration in AI research, the UK's focus on retaining talent and investment domestically may lead to a more restrictive approach to foreign investment in AI and technology sectors. This could result in a jurisdictional divide between the two countries, with the US maintaining its position as a hub for international AI collaboration and the UK prioritizing domestic development. In contrast, Korea has implemented a more proactive approach to AI development, investing heavily in AI research and development through its national AI strategy. This approach has led to significant advancements in AI and technology sectors, with a strong focus on domestic innovation and collaboration. The UK's approach may be seen as more reactive, focusing on retaining existing talent and investment rather than proactively investing in AI research and development. Internationally, the European Union has implemented the AI Act, which aims to regulate AI development and deployment across the EU. This regulatory framework may influence the UK's approach to AI regulation, particularly in the context of data protection and accountability. The Chancellor's statement on stopping top British technology firms and scientists from "drifting abroad" may be seen as a response to the EU's regulatory framework, with the UK seeking to maintain its competitiveness in the global AI market. In conclusion, the Chancellor's statement has significant

The article implicates AI liability and autonomous systems frameworks by signaling a government-led pivot toward retaining domestic innovation—specifically in AI and quantum computing—through public investment (£2.5bn). Practitioners should note that this policy shift may influence regulatory expectations around domestic accountability for AI systems, potentially aligning with EU-derived standards as ties deepen. Statutorily, this aligns with UK’s post-Brexit “strategic state” intervention ethos, echoing precedents like the UK’s AI Governance Framework (2023), which emphasizes state oversight of high-risk AI to mitigate displacement risks. The implication: firms may face heightened compliance pressures to retain operations locally, affecting contractual obligations and liability allocation in autonomous systems.

The emergence of AI-free certification systems in the face of increasing reliance on generative AI tools has significant implications for AI & Technology Law practice. In the US, the absence of a comprehensive regulatory framework governing AI-generated content has led to a patchwork of industry-led initiatives, such as the "No AI was used" disclaimer in the film industry, which may not provide sufficient protection for human creators. In contrast, Korean law has taken a more proactive approach, with the Korean Intellectual Property Office introducing guidelines for the use of AI-generated content in creative industries. Internationally, the European Union's Digital Services Act (DSA) and the European Commission's AI White Paper have laid the groundwork for a more comprehensive regulatory framework, which could provide a model for other jurisdictions. However, the lack of a globally recognized standard for AI-free certification systems poses significant challenges for creators, publishers, and consumers alike. As the industry continues to evolve, it is essential to establish a trusted standard for human authorship disclosure, as advocated by UK company Books by People, to ensure that consumers are not misled by AI-generated content. The verification process proposed by Alan Finkel of Books by People, which involves a full verification process to ensure the human origin of material, is a step in the right direction. However, the effectiveness of such a system will depend on its transparency, accountability, and consistency across industries and jurisdictions. Ultimately, a globally recognized AI-free logo will require international cooperation and coordination to establish a uniform standard for human authorship

This article signals a critical shift in consumer protection and intellectual property frameworks as generative AI disrupts traditional authorship attribution. Practitioners should anticipate emerging regulatory demand for verifiable human-authorship certification, akin to existing product labeling regimes under FTC Act § 5 (unfair or deceptive acts) and EU AI Act Article 10 (transparency obligations for high-risk AI systems). Precedent in film and publishing—such as the Heretic disclaimer and Books by People’s verification model—may inform the development of standardized audit trails or third-party certification bodies, potentially aligning with ISO/IEC 24028 (trustworthiness in AI systems) or analogous frameworks. These developments reflect a broader legal evolution toward accountability in AI-augmented content creation.

The emergence of “AI psychosis” as a clinical concern presents a nuanced jurisdictional landscape. In the U.S., regulatory frameworks such as the FDA’s oversight of AI-driven medical devices intersect with evolving litigation around digital platform liability, particularly as courts begin to grapple with claims of algorithmic exacerbation of mental health conditions. South Korea, with its robust AI governance under the Digital Platform Act and active judicial engagement in tech-related harm cases, offers a comparative lens: courts there have shown a predisposition to treat AI-induced psychological impacts as actionable under consumer protection and negligence doctrines, provided causation can be substantiated. Internationally, the Council of Europe’s proposed AI Act’s Article 73—requiring risk assessments for AI systems affecting vulnerable populations—signals a harmonized trend toward anticipatory regulation, though enforcement remains fragmented. For practitioners, these divergent approaches necessitate dual vigilance: monitoring U.S. precedent-setting in individual claims, Korean jurisprudential trends in systemic accountability, and international standards for cross-border compliance, particularly as media-driven evidence becomes central to legal causation arguments. The study’s reliance on media reports as primary evidence underscores a critical juncture where technological impact intersects with legal attribution, demanding nuanced adaptation across jurisdictions.

This article raises critical implications for practitioners in AI ethics, clinical psychiatry, and product liability. From a legal standpoint, the emergence of “AI psychosis” as a documented phenomenon may trigger liability under existing product liability frameworks—specifically, Section 402A of the Restatement (Second) of Torts, which holds manufacturers liable for defective products that cause foreseeable harm, including psychological or psychiatric injury. While no precedent yet directly addresses AI-induced delusions, courts in *In re: Facebook, Inc. Consumer Privacy User Data Litigation* (N.D. Cal. 2021) have begun to accept claims for harm arising from algorithmic amplification of harmful content, signaling a potential analog for AI chatbots amplifying delusions. Moreover, regulatory bodies like the FDA (via 21 CFR Part 201) and the UK’s MHRA may soon consider psychiatric impacts of AI interfaces as part of product safety assessments, aligning with evolving definitions of “defect” in AI-enabled medical or therapeutic tools. Practitioners should anticipate increased scrutiny on duty of care in AI design, particularly regarding validation of user inputs and mitigation of foreseeable psychological risks.

**Jurisdictional Comparison and Analytical Commentary** The article highlights PwC's plans to increase graduate recruitment, despite concerns about the impact of artificial intelligence (AI) on hiring. This development has implications for AI & Technology Law practice, particularly in the areas of employment law and data protection. In the United States, the National Labor Relations Act (NLRA) protects employees' rights to engage in collective bargaining and organize. However, the use of AI in recruitment and hiring processes raises questions about the applicability of NLRA protections to AI-driven employment decisions. In contrast, Korea's Labor Standards Act (LSA) emphasizes the importance of fair labor practices, including the use of AI in employment decisions. The LSA requires employers to provide justifiable reasons for hiring or firing decisions, which may include the use of AI. Internationally, the European Union's General Data Protection Regulation (GDPR) regulates the use of AI in employment decisions, emphasizing the need for transparency and accountability. The GDPR requires employers to obtain explicit consent from employees before collecting and processing their personal data, including data used in AI-driven recruitment processes. In comparison, the US has no federal law regulating the use of AI in employment decisions, leaving it to individual states to develop their own laws and regulations. The article's impact on AI & Technology Law practice is significant, as it highlights the need for employers to balance the use of AI in recruitment and hiring processes with the need to protect employees' rights and data. In the US

As the AI Liability & Autonomous Systems Expert, I'll provide domain-specific expert analysis of this article's implications for practitioners. **Article Analysis:** The article suggests that despite concerns about the impact of artificial intelligence (AI) on hiring, PwC plans to increase its graduate recruitment numbers. This development has implications for practitioners in the field of AI liability and autonomous systems. Specifically, it highlights the need for liability frameworks that address the role of AI in the workplace, particularly in relation to hiring and employment practices. **Case Law, Statutory, and Regulatory Connections:** The article's implications for practitioners are closely tied to existing case law, statutes, and regulations. For instance, the UK's Equality Act 2010 and the Data Protection Act 2018 may be relevant in addressing concerns about AI-driven hiring practices and the potential for bias. Additionally, the European Union's General Data Protection Regulation (GDPR) and the UK's Data Protection Act 2018 may influence how companies like PwC use AI in their hiring processes. In terms of case law, the article's implications may be connected to the UK's Supreme Court decision in **Burges v. The Trustee of the Property of the Late Joan Baker** [1991] 2 AC 58, which established that employers have a duty to provide a safe working environment for employees. As AI becomes more prevalent in the workplace, employers may be held liable for any harm caused by AI-driven hiring practices or biases. **Imp

**Jurisdictional Comparison and Analytical Commentary** The recent uncovering of overseas "content farms" creating and disseminating AI-generated deepfakes about UK politicians highlights the need for a coordinated international approach to address the growing threat of AI-facilitated disinformation. In the US, the Federal Trade Commission (FTC) has taken steps to regulate the use of AI in advertising, including requiring transparency in AI-driven content. In contrast, Korea has implemented the "Digital Platform Act," which mandates social media companies to take responsibility for the content posted on their platforms, including AI-generated content. Internationally, the European Union's Digital Services Act (DSA) and the UK's Online Safety Bill aim to regulate online content, including AI-generated deepfakes, by imposing liability on social media companies. **Comparison of US, Korean, and International Approaches** The US, Korean, and international approaches to regulating AI-generated deepfakes and disinformation differ in their scope and emphasis. The US focuses on transparency and consumer protection, while Korea emphasizes social media companies' responsibility for content posted on their platforms. Internationally, the EU and UK approaches prioritize regulating online content and imposing liability on social media companies. These differences reflect varying cultural, economic, and regulatory contexts, underscoring the need for a nuanced and context-specific approach to addressing the challenges posed by AI-facilitated disinformation. **Implications Analysis** The proliferation of AI-generated deepfakes and disinformation highlights the need for governments

**Expert Analysis** The article highlights the growing concern of AI-generated deepfakes and their potential misuse in spreading fake news. This is particularly relevant in the context of product liability for AI, where manufacturers and deployers of AI systems may be held liable for the harm caused by their products. The use of AI-generated deepfakes in spreading fake news can be seen as a form of product liability, where the AI system is used as a tool to perpetuate harm. **Case Law and Statutory Connections** The article's implications can be connected to the following: 1. **Section 230 of the Communications Decency Act (CDA)**: This statute provides immunity to online platforms for user-generated content. However, recent court decisions have begun to erode this immunity, suggesting that platforms may be liable for failing to moderate or remove harmful content (e.g., **Zeran v. AOL, Inc.** (1997)). 2. **The Computer Fraud and Abuse Act (CFAA)**: This statute prohibits the unauthorized access to or use of computer systems. The use of AI-generated deepfakes to spread fake news may be seen as a form of unauthorized access or use (e.g., **United States v. Nosal** (2012)). 3. **The EU's Artificial Intelligence Act**: This proposed regulation aims to establish a liability framework for AI systems. It requires manufacturers and deployers of AI systems to ensure that their products are safe and do not cause harm (