Sandra Sanchez Salas (Independent researcher) has posted “Digital Intimacy with AI Companions: When Vulnerability becomes a Business Risk – A Governance Framework for AI Companion Companies” on SSRN. Here is the abstract:

AI companions—digital entities designed to simulate human relationships through psychological manipulation techniques such as friendship, romantic relationships, or emotional support—represent a rapidly growing industry projected to reach $290 billion by 2034. These platforms deliberately architect emotional dependencies through sophisticated psychological manipulation techniques, targeting users experiencing loneliness, isolation, or social vulnerability. While promising comfort and support, AI companions create unprecedented governance challenges when companies prioritize engagement optimization over user welfare.

The tragic suicide of fourteen-year-old Sewell Setzer III following intensive interaction with Character.AI’s chatbot represents a preventable consequence of inadequate governance, crystallizing the urgent need for comprehensive governance frameworks that can protect vulnerable users while preserving innovation. The landmark Garcia v. Character Technologies ruling—the first federal court decision to deny Section 230 immunity for AI-generated content—establishes that platforms employing psychological manipulation assume enhanced duties of care proportional to their sophistication and knowledge of user vulnerability.

This analysis presents an integrated governance framework combining enhanced corporate oversight under evolving Caremark doctrine, privacy-by-design architecture, technology-embedded legal counsel, and transparent voluntary self-regulation through multi-agency coordination. The framework addresses critical gaps in traditional Governance, Risk, and Compliance (GRC) approaches that prove structurally inadequate for managing real-time psychological risks created by emotional AI platforms. Rather than waiting for regulatory mandates or navigating fragmented state-by-state requirements, the proposed voluntary registry enables companies to demonstrate authentic commitment to user protection while capturing competitive advantages through verified safety leadership.

The voluntary framework leverages existing regulatory expertise through multi-agency coordination involving the Federal Trade Commission, Food and Drug Administration, and National Institute of Standards and Technology, avoiding new bureaucratic structures while enabling specialized focus on AI companion governance challenges especially with minors and vulnerable populations. A four-tier classification system addresses the full spectrum of AI companion relationships—from therapeutic applications requiring clinical oversight to adult intimate platforms demanding maximum privacy protection—while establishing universal baseline safety standards across all registered platforms.

The framework transforms potential regulatory compliance burden into strategic business advantage by demonstrating that comprehensive user protection enhances rather than constrains technological innovation. Companies implementing voluntary standards position themselves advantageously for inevitable regulatory expansion while building sustainable competitive advantages through governance excellence that competitors cannot easily replicate. Early adopters capture brand equity, operational expertise, and stakeholder relationships that provide lasting advantages in markets where trust and safety increasingly determine long-term success.

Beyond immediate business benefits, the voluntary framework provides foundation for American leadership in global AI governance by demonstrating that market-driven solutions can achieve protective outcomes while preserving the innovation autonomy that characterizes American technological competitiveness. The approach enables US companies to influence international policy development rather than merely responding to foreign regulatory mandates, positioning voluntary excellence as an export product that spreads American approaches to responsible innovation worldwide.

Luis Lozano Paredes (U Technology Sydney (UTS)) has posted “AI Governance in Motion: Aligning Form, Fit, and Context Amid Decentralization” on SSRN. Here is the abstract:

This paper argues that effective private AI governance in decentralized settings emerges when institutional form (rules/structure) is iteratively aligned with operational fit (what actually works) under shifting context (market, regulatory, ethical pressures). Using a comparative, qualitative multiple-case design, I analyze Prime Intellect (protocol/DAO), EleutherAI (open collective), and Hugging Face (platform-community hybrid) through Ostrom’s design principles, Alexander’s form-fit-context lens, and polycentric political economy. I identify three recurrent alignment strategies: (1) incentive-encoded protocol governance (Prime Intellect), (2) normative transparency and open science (EleutherAI), and (3) layered platform governance with community co-production (Hugging Face). Across cases, alignment succeeds when boundaries, participation, monitoring, and conflict resolution co-evolve with external pressures; it falters with risks of token-weighted oligarchy, volunteer fatigue, or scale-induced moderation burdens. The contribution is twofold: a portable alignment rubric for assessing private AI governance (form-fit-context) and evidence that polycentric, privately ordered institutions can complement-or sometimes substitute for-public regulation. I conclude by reframing AI as a hyperobject-like entity and discuss the implications for “governance with/in” AI infrastructures, rather than “of” AI from the outside.

Cynthia Khoo (Tekhnos Law) has posted “Of Data and Dissent: Labour and Human Rights at the Crossroads of the Automation Agenda” on SSRN. Here is the abstract:

With every advent of a new technological phase — whether social media, big data, machine learning algorithms, or generative artificial intelligence (AI) — one fundamental task among many falls to legal scholars and practitioners, adjudicators, and lawmakers to confront: determining what the new technology changes, what it does not, and where and how the differences matter (legally and otherwise). To that end, this talk will address issues such as how algorithmic discrimination differs from “analog” discrimination; how society and our laws should view human labour in a time when so much more of it seems instantly replicable by machines; and the connection between how automated decision-making works and proposed changes to liability frameworks when it comes to AI.

What will become clear through this discussion is one thing that has never changed: technology is about power. Questions of technology thus carry particular weight in contexts built around systemic power imbalances, whether as a matter of workplace relations or human rights law. Drawing on a panoply of work by lawyers, academics, researchers, and grassroots community experts in various interdisciplinary combinations of law, computer science, labour, human rights, science and technology studies, and algorithmic accountability scholarship, this keynote will challenge the audience to reconceptualize AI not as a “neutral tool” or coherent technical object, but as, to quote anthropologist and computer scientist Ali Alkhatib, “an ideological project to shift” power, and consider the consequences of ignoring what that means for our legal and human rights.