Video: Lauren Celenza – Living Through an AI Takeover Without Losing Your Soul

Lauren Celenza had the one of the harder slots of the whole event: the very last talk, after two days of everything else. And she opened it with a confession that got a room full of raised hands.

She was tired of hearing about AI.

Then she told us this was a talk about AI anyway, but one that would go beyond the hype, beyond the doom, and, as she put it, beyond the sparkles. What followed was a thoughtful hour with a lovely closing talk.

Capability and Consequence

Lauren has spent a decade as a software designer and writer at Google, Adobe, Code for America and the World Resources Institute, and five years writing her newsletter Tech Without Losing Your Soul. Across all of it, one thread kept showing up: every technological breakthrough in human history arrives with capabilities and consequences.

She started with the first transatlantic telegraph cable in 1858. A breakthrough that shrank the world and also electrocuted sharks who bit down on the high-voltage lines. We were so busy building fast communication, she said, that we forgot we were laying those cables in someone else’s home.

The moon became her image for it. A light side and a shadow side. Marjan talked about the sun the day before, Lauren noted. She would take the moon. And as tech makers, we tend to fixate on the bright side. The consequences sit out of view.

A History Most of Us Don't Know

The heart of the first half was a history lesson. In 1956, a group of scientists convened at Dartmouth College to found a new discipline around Alan Turing’s question of whether machines can think. John McCarthy first called it Automata Studies. Nobody paid attention. So they picked something more evocative: artificial intelligence. It sounded good, impressive, sophisticated. Well, and it worked. Funders came. Scientists came.

The term was a marketing move from the very beginning and as Lauren argued, that name has shaped everything since: how we name technology determines how we measure it and what we measure is what we build.

From there: Joseph Weizenbaum and ELIZA in 1964 and his colleague who knew perfectly well it was just a program and still couldn’t be interrupted while talking to it. ImageNet and AlexNet. A dinner in Silicon Valley where two men shared a fear and founded OpenAI as a nonprofit. And November 2022, when a “low-key research preview” hit a million users in five days.

Her conclusion: AI didn’t emerge purely from a desire to create or innovate. It emerged from power struggles, fear and the desire to get attention. Deeply human impulses and what gets built shapes us.

The Question at the Crux

Lauren walked through the promises we’re sold: More decisive, more innovative, faster, more efficient, more productive. Then she put the consequence next to each one. Products converging on the same chatbot and the same sparkles because everyone feels the same existential threat. Slop diluting meaning. Data centres in Frankfurt accounting for 40% of the city’s electricity demand. Productivity gains that are real, alongside pressure that is just as real.

Which brought her to the slide she asked the room to photograph:

Can we really call it intelligence, if it’s built to ignore its own consequences?

That question, she argued, is the point. Right now we mostly aren’t asking questions. We’re picking sides. AI will save us or AI will destroy us. Both sides do the same thing: they collapse our agency into inevitability. Both say the outcome is already decided, so your choices don’t matter.

Five Roles

The second half was the practical turn: five roles to experiment with. Not skills, Lauren was careful to say, but ways of being human that no model can condense into a prompt.

• The catalyst cuts through ambiguity to make the unclear visible. AI can generate endless prototypes, but it cannot generate purpose. The risk isn’t that AI replaces the designer . It’s that we outsource so much thinking that we forget what we actually believe about the problem we’re solving. We become prompt operators. Skilled at extraction, disconnected from conviction.
• The bridge connects what’s been fragmented. AI can synthesise both sides of an argument, but it can’t sit in the tension between them to build trust. Her reframe here was: not human in the loop, but human on the loop.
• The listener brings the outside world in. This is where she told the Google Maps story. Being asked in Seattle to design motorbike navigation for Southeast Asia and deciding to go outside instead. Getting on the back of a bike in Jakarta on a Friday evening. Getting lost for hours to feel the pain. Motorbike mode shipped and Google Maps went from one billion monthly users to two.
• The curator cuts through slop to protect quality and empower human choice. Because your mind becomes what it consumes and a curator with flattened taste has nothing original left to offer.
• The subverter challenges conformity when AI-driven work converges towards sameness. This one requires staying in contact with discomfort. Resisting the pull of frictionless answers, because struggle is where breakthroughs happen.

She nodded to Annie Atkins’ talk from the night before here, on how analog experiences can be the more effective ones. Polaroid’s campaign line said it well: AI can’t generate sand between your toes.

The Closing

Five things to take home: know what is actually yours. Show up for each other. Protect embodied experience. Choose what you let in. Stay in contact with discomfort.

And then the last line:

The stakes are high, but they’re not inevitable. Every choice you make shapes who we are becoming. So what will your choice be?

A great closing talk. Thank you, Lauren.

Links

→ Lauren Celenza’s speaker profile
→ The speaker introduction from before the event
→ Tech Without Losing Your Soul newsletter

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