The Custodians of Self: Why Your AI Identity Demands the Same Care as Your Savings Account

by TWR. Editorial Team | Friday, Oct 24, 2025 for The Weekend Read. | 💬 with us about this article and more at the purple chat below-right, our Concierge powered by Bizly. 

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While SB 53 creates legal scaffolding for transparency and safety, its success will ultimately depend on how creators, technologists, and production ecosystems interpret and extend those principles.

Regulation sets the floor. Culture and stewardship set the bar.

For years, creators in digital media operated without protection. Before YouTube’s monetization models matured and before agencies recognized online creators as legitimate artists, creator management companies had to fill the gap.

The push to recognize creators under SAG-AFTRA’s New Media Agreements was one of the first efforts to demand parity: fair rates, 12-hour turnarounds, lodging within contract radius, and union-level protections. That early wave of advocacy reframed the influencer not as a novelty, but as a worker deserving of the same respect as legacy film talent.

Today, as AI redefines what it means to perform, that precedent is more relevant than ever. A new category of artist has emerged: one's AI identity (their HUMAN+ media presence), a digital twin, trained on one’s likeness, voice, or creative patterns, capable of existing and evolving independently. This new form of creative capital demands an off-line framework of ownership and custodianship.

The platforms building these AI counterparts, often under broad, opaque terms of service, are increasingly unreliable stewards. Meta’s recent layoffs across its compliance, ethics, and AI risk divisions underscore the danger of allowing platforms to manage users’ replicas.

These companies are shedding the very personnel responsible for ensuring their systems do no harm. Expecting them to safeguard digital identities is like letting a bank eliminate its auditors and still trusting it to manage your life savings.

As iA argues, AI identity must be managed off-platform, like a financial portfolio, independently audited, contractually protected, and governed by current and forward-looking principles aligned with the individual, not the algorithm. The infrastructure for this already exists in the talent ecosystem: the legal frameworks used to protect name, image, and likeness (NIL) can evolve to govern digital twins. But the moral framework must evolve too. It’s not enough for platforms to promise “safety by design.” They must guarantee ethics by default, and when they don’t, brand stewards like iA must step in to define it.

The stakes go beyond copyright or compensation. A misaligned AI representation can erode public trust, alter reputations, and inflict psychological or social harm. The question is not whether AI will model human expression, but who will be accountable when it misrepresents it.

That is why talent advocates at iA urge unions like SAG-AFTRA to expand their reach to this new frontier beyond that which has been considered and deployed, ensuring that the same protections once fought for on set extend to the data that now defines an artist’s presence.

As the union once adapted to the rise of digital media, it must now recognize AI performance as a legitimate and protectable new form of work (and royalty-driver).

SB 53 may regulate the creators of frontier models, but artists must regulate the creation of their frontier-selves. If the 2010s were about reclaiming credit for the content creators made, the 2020s, and beyond, will be about reclaiming control over the versions of themselves that technology can make.

The next revolution in creative rights won’t happen in a courtroom or on a picket line. It will happen in contracts, codebases, and custodial frameworks built by those who understand both the art and the algorithms.

TWR. Last Word: "As before, California may not just be where that story begins, it may be where the world learns how to write its sequel."

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Insightful perspectives and deep dives into the technologies, ideas, and strategies shaping our world. This piece reflects the collective expertise and editorial voice of The Weekend Read  |🗣️Read or Get Rewritten | www.TheWeekendRead.com

Terms + Vocabulary

Artificial Intelligence (AI) — Computer systems designed to perform tasks that normally require human intelligence, such as perception, reasoning, or language generation.

Frontier AI — A term used to describe the most advanced, large-scale foundation models trained with enormous computing power (10²⁶ FLOPs or more). These models possess broad general capabilities and pose both high innovation potential and high risk.

Foundation Model — A base AI model (such as GPT, Claude, or Gemini) trained on vast datasets and adaptable for multiple downstream applications through fine-tuning or prompting.

FLOPs (Floating Point Operations) — A unit of measurement for computing performance, used to define how much computational power is needed to train an AI system. SB 53 applies only to models above 10²⁶ FLOPs.

Frontier AI Framework — A public document required under SB 53 that details a developer’s safety, governance, and risk management protocols for advanced AI models.

CalCompute — A proposed state-managed AI supercomputing consortium created under SB 53 to promote safe and equitable AI development by public institutions.

CalOES (California Office of Emergency Services) — The state agency designated under SB 53 to receive and investigate reports of “critical AI safety incidents.”

Critical AI Safety Incident — Any malfunction, misuse, or catastrophic behavior in an AI system that poses risk to human life, infrastructure, or causes over $1 billion in damage.

Whistleblower Protections — Legal safeguards for employees who report AI safety risks or violations without fear of retaliation. SB 53 codifies these protections under California labor law.

Catastrophic Risk — Defined by SB 53 as a foreseeable event involving an AI model that could cause mass casualties or over $1 billion in property damage.

Adaptive Oversight — A feature of SB 53 that mandates annual review of AI thresholds and definitions to keep the law aligned with evolving technology.

Preemption — The legal principle under which state law supersedes local laws; SB 53 preempts cities and counties from enacting conflicting AI regulations.

AI Identity — A digital representation or “twin” of a human being, built using their data, likeness, voice, or creative outputs. It can perform or generate content autonomously.

Name, Image, and Likeness (NIL) — Legal concept granting individuals ownership over their personal attributes and how they’re used commercially. Increasingly relevant in the age of digital replicas.

AI Replica / Digital Twin — A synthetic version of a person created using machine learning; may mimic a person’s voice, face, or behavior for commercial or creative purposes.

Custodianship (of AI Identity) — The process of managing, auditing, and ethically governing one’s AI likeness off-platform—independently from major social media or technology companies.

Platform Stewardship — The corporate governance responsibility of platforms (e.g., Meta, Google) to protect users’ data and prevent misuse of AI identities. Often under strain as companies downsize ethics teams.

Unionization of Digital Talent — The organized effort to bring influencers, creators, and digital artists under traditional labor protections, such as SAG-AFTRA’s New Media Agreement.

SAG-AFTRA (Screen Actors Guild – American Federation of Television and Radio Artists) — The union representing film, television, and digital performers. Its 2023 contract introduced rules governing AI-generated likeness and performance consent.

Ethics by Default — A principle promoted by responsible AI advocates that ethical safeguards should be embedded in systems from the start—not added reactively after harm occurs.

AI Governance — The combination of policies, technical standards, and organizational practices that ensure responsible development and deployment of artificial intelligence systems.

Transparency by Design — The proactive disclosure of AI system design, data, and risk evaluation, aimed at building public trust and accountability.

inArtists (iA) — A creative and technology company advocating for AI-augmented storytelling, fair digital identity management, and custodial systems that protect artists’ rights in the AI era.