Another reminder that a polished interface is NOT a predictable system.
This is just another reminder that a polished interface is NOT a predictable system.
For context, Tilly Norwood is an AI-generated “actress” created by Particle6. She has been doing interviews to promote a new movie, Misaligned.
In this recent appearance with Piers Morgan and actor Tom Conti, she was asked whether the other actors in the film were real or AI. After struggling with the question, she paused and suddenly started speaking Cantonese for more than 10 seconds. She later described it as a “hiccup.”
This gets at a much bigger question: What happens when AI systems move from generating content to representing people, characters, expertise, and identity?
I’ve been thinking about this firsthand since I built and deployed my digital twin, RamBOT, more than two years ago.
For me, here’s what matters ->
1\ Dismissing this technology is a mistake.
Remember when GPT-3.5 could famously stumble over a question as simple as how many Rs are in “strawberry”? Look at where the frontier is now.
OpenAI recently reported that an internal system significantly more capable than GPT-6 Astra produced a proposed resolution to a Navier–Stokes Millennium Prize Problem using thousands of coordinating agents. GPT-6 Astra was then used to formalize and verify the work in Lean.
The mistake is to extrapolate from yesterday’s limitations to tomorrow’s capabilities. AI is improving too quickly for that.
2\ The Tilly moment shows us a point of fragility.
We should NOT confuse unexpected behavior with intelligence (or for that autonomy, agency or intent). Instead, it is a reminder that increasingly capable systems can still produce outputs their creators did not anticipate.
That means we need to care about provenance, boundaries, evaluation, attribution, and human control.
Especially true when AI is attached to a real person's identity or reputation.
3\ Working with these systems changes your perspective.
You start thinking about what happens when AI can embody knowledge, interact with people, adapt to context, and operate continuously.
The possibilities are enormous, as are the responsibilities.
So what should we build for?
For me the answer is simple -> AI that extends human capability rather than pretends to be human.
A digital twin can allow one person's accumulated knowledge and experience to reach thousands (or millions) of people. It can remove a fundamental constraint of human existence. You no long need to be in one place, have one conversation, and answer one question at a time.
That is both an opportunity and a challenge. We are still figuring out the boundaries. That’s what makes this moment so exciting.
The technology is getting more capable. Our job is to get better at using it well.
Until next time,
Ram
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Ram Srinivasan
MIT Alum | Author, The Conscious Machine | Global Future of Work and AI Adoption Leader published in Business Insider, Fortune, Harvard Business Review, MIT Executive Viewpoints and more.
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Disclaimer:
Ram Srinivasan currently serves as an Innovation Strategist and Transformation Leader, authoring groundbreaking works including "The Conscious Machine" and the upcoming "The Substrate Shift."
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