Tag: artificial intelligence

Advertising Built Generative AI. Now Comes the Remodel.

Don’t worry, Don’s going to take it from here.

Last night my wife looked up from her phone, disgusted. “All I’m getting is Jeffrey Epstein and Peter Attia!” she said. “Why do they think I’m interested in this?!”

As the family’s resident interpreter of digital entrails, I felt responsible to hazard an answer, but given the prurient nature of the Epstein story, I sensed my thoughts might not be well received. So I backed into it a bit: “Have you clicked on any Epstein-related links recently?” I asked. She had, she rejoined, wary of the implicit judgement hovering over my question. “But that doesn’t mean I want my entire feed to be about it!”

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How Search Drove Generative AI – A Passage from “The Search”

It’s been fun to go back to Berkeley, where I first taught Journalism more than 20 years ago. I’m leading a seminar on how technology impacts journalism, with a particular focus on AI. The class asks students to read a bit of history – it’s hard to understand where we are if we don’t know how we got here. Search is a big part of that history, so I included a chapter of my first book – The Search – as a reading assignment.

As I prepared for class last week, I dug through my archives and unearthed The Search’s original manuscript. In the first chapter, “The Database of Intentions,” I opine on how search might lead to the development of AI that passes the Turing Test. Written 22 years ago, the passage anticipates the rise of generative AI. I start by drawing a distinction between data that is on our personal machines and data held in the cloud by large technology companies like Google. Then I think out loud a bit about where that all data might take us. Even though the writing is two decades old, it prompts some interesting questions about the moment in which we find ourselves.

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Thriving in an AI World: The Importance of Good Questions

Every so often I am asked to participate in a survey fielded by Elon University’s Center for Imagining the Digital Future. As you might expect, this year’s survey focuses on the impact of AI, and includes this prompt:

  • If you do think it is likely that AI systems will begin to play a much more significant role in shaping our decisions, work and daily lives: How might individuals and societies embrace, resist and/or struggle with such transformative change? As opportunities and challenges arise due to the positive, neutral and negative ripple effects of digital change, what cognitive, emotional, social and ethical capacities must we cultivate to ensure effective resilience? What practices and resources will enable resilience? What actions must we take right now to reinforce human and systems resilience? What new vulnerabilities might arise and what new coping strategies are important to teach and nurture?

It’s rare that a survey asks its respondents to actually write something cogent and long form, so I figured I’d publish my response here. I’d be curious to hear your thoughts! If you’d like to participate, the link to the survey is here.

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AI and Ads: Here We Go!

Google launched as a free public beta in the Fall of 1998. It was a revelation – a 10X improvement on Internet navigation and research. But from its launch forward, Google’s founders were hounded with questions as to how their company planned on actually making money. John Doerr, one of Google’s earliest backers, famously answered that question by citing Google’s extraordinary growth: With all that traffic, he said, we’ll figure it out.

Google’s founders were famously suspicious of advertising – in their white paper explaining Google’s PageRank technology, Larry Page and Sergey Brin argued that advertising-funded search engines would be “inherently biased towards the advertisers and away from the needs of consumers.”

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Do You Trust The Conjurer? (Predictions 2026, #1)

Cecco de Caravaggio The Conjurer (The Musician) c. 1600-1620

The modern English verb ‘to conjure’ is derived from the Latin conjurare, meaning ‘band together by an oath, conspire.’ Its roots con (‘with’) and jur (‘legal right or authority, law’) echo with questions central to our present day struggle with technology: Who do we trust to determine authority? Why do we believe in them?

Conjuring also evokes magic, sorcery, and wonder, essential elements of the tech industry mythos. My earliest pieces on the impact of generative AI leaned on the metaphor of magical “genies” doing our bidding in a relationship bound by loyalty and trust. Do those genies work for us, or are they the product of conjurers beyond our control? Do they demand faith, or instill it?

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Battle Lines Are Drawn (Predictions 2026, #2)

The 1960s ain’t got nothing on today.

I concluded my post “Magic and Mayhem” with a bit of a tease about the impact of AI on our society:

There will be lots of magic this year. But there will also be plenty of carnage as previously unbreachable moats start to crumble, not only in business, but also in society at large. For more on that, stay tuned for prediction #2. 

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Magic and Mayhem (Predictions 2026, #3)

Magic maker

Do you remember the last time you felt the magic? When you encountered something truly novel, something that was both surprising and at the same time deeply familiar, because you had imagined such a thing, but until that very moment, believed it impossible?

I’ve had only a handful of such moments in my long relationship with digital technology. The first was in 1981, when I programmed a game of tic-tac-toe on an underpowered IBM PC. I compiled the crude lines of code I’d been assigned to write, issued the command “RUN” at the C: prompt, and damned if the thing didn’t actually work.

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Health Takes Center Stage, Open Evidence Acquired (Predictions 2026, #5 and #4)

Yesterday The Information scooped my well laid plans for today’s health and AI-related predictions. If you’ve been following along this past week, you know I decided to write one prediction post a day for the first working week of the year. Today marks #5, which predicts that health will become a central player in society’s debate around AI, and #4, which predicts OpenEvidence will be acquired. I knew that OpenAI was working on health-related product offerings – the company said as much when it hired Fidji Simo from Instacart. But I didn’t know OpenAI would announce its health product so early in the year. Oh, and by the way, Google is expected to quickly do the same.

That said, I think there’s a lot more room to run in this story. OpenAI’s announcement is just the prelude. Health offers the perfect test case of just about every crucial limitation –  and every massive opportunity – that AI represents in society today.

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The Year Tech Gets Even Bigger (Predictions 2026, #7)

If only Nano Banana could spell, AI would be a thing.

For the past many years one prediction has proven reliably accurate: There will be no significant Federal regulation of the technology industry. At times this stalwart prognostication has been tested by major anti-trust actions – but each has proven ultimately toothless. This year, for example, we’ll learn what the DOJ managed to accomplish in its second case against Google – and it’s still possible a judge will rule that the search and AI giant must divest itself of its adtech infrastructure. But I don’t think so. And even if that ruling does come to pass, Google knows it can simply appeal, dragging out any eventual impact until it wins a war of attrition with an increasingly feckless and uninterested DOJ.

Besides, arguing about the past is playing yesterday’s game, and in 2026, the game has reverted to an even older playbook. For the past five or so years, tech giants have had to play defense when it comes to M&A and sweetheart partnerships – Meta was being sued over its acquisitions of Instagram and WhatsApp, Google over its consolidation of adtech and its domination of search distribution through deals with Apple and Samsung, among others. But in 2026, the governors are coming off.

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AI Can’t Cost This Much (Predictions 2026, #8)

That’s some Big Iron you got there, Mister!

Some of you gave disagreed with my last prediction, that Anthropic would file for an IPO, stating, accurately, that OpenAI has a far more pressing need for fresh capital, given its commitments to various partnerships totaling  more than $1.4 trillion and counting. That’s a good point, but I don’t think OpenAI will ever really spend that money, and my next prediction explains why: I think the costs involved with delivering AI will come down significantly in 2026.

I’m not either an economist nor a supply chain expert, so what I’m about to write is informed more by historical rhyming than quantitative analysis. But when I see eye-watering numbers about the cost of data centers, compute, and chips, I start to wonder if innovation has been factored into the calculations. When trillions of dollars are projected to be spent, trillions that would require trillions more in revenue (and profit) to justify, a lot of butterflies start to flap their wings.

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