On Suleyman’s Conjecture: Should AI Have Rights?

 

Artwork from Reid Hoffman’s “AI For All Americans”

Of all the think pieces, manifestos, hand wringing, and news analysis I’ve read about AI threats and opportunities, the one piece that feels critical to consider is a plea from Mustafa Suleyman, CEO of Microsoft AI. Its subhead lays out its core argument: “AIs do not have rights, feelings, or consciousness. And we must not train them to act as though they do.”

Suleyman opens with a very clear point of view. Let’s call it Suleyman’s Conjecture:

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How Can You Trust the News?

The single most essential ingredient of good journalism is trust. By that measure, journalism is in a very bad way: According to The Reuters Institute’s annual survey, only 37 percent of the global public trusts the news industry, down nearly 20 points from ten years ago. In the US, that figure stands at 25 percent.

Reuters also reported that for the first time, more than half of respondents get their news primarily from algorithmically driven platforms like Instagram, TikTok, and YouTube. And the fastest growing new “surface” for news consumption? AI chatbots like OpenAI’s ChatGPT and Anthropic’s Claude.

The central story of journalism in the digital age is one of collapse. Platforms and their algorithms have cleaved audience from traditional news brands. The industrial-scale AI that runs sites like Instagram and YouTube are tuned for engagement and advertising sales, not trust or truth. Personalized AI of chatbots like Gemini or ChatGPT seem destined for a similar fate.

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Will AI Ever Become a True Platform? Not Without Us….

Yesterday Microsoft CEO Satya Nadella published a fascinating essay that reads as both a rebuke to frontier AI model companies like Anthropic and OpenAI, as well as a call to arms to the entire business community.

Nadella is worried that OpenAI and Anthropic are about to eat everyone’s lunch – Microsoft included. “I’ve been thinking a lot about the future of the firm in an AI-driven economy,” he opines. “The last thing any of us want is a world where every company across every sector is ceding value to a few models that eat everything they see.”

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Wait, Chat Is Dead? Does That Mean OpenAI Is Abandoning Ads?

Over the weekend the Financial Times came out with a report on OpenAI’s latest pivot.  According to a senior OpenAI executive quoted in the piece, the company has decided that “chat is dead.”

Instead, company executives insist, the future lies in a “super app,” an agent (from OpenAI, naturally) that will do everything for us. The “surface” – the interface between a user and OpenAI’s service – will no longer be a fixed chat box. Instead, according to Thibault Sottiaux, who now heads the OpenAI super app project, “what we’re building towards is where you have your own personal agent that is capable of helping you . . . across everything in your life, be it personally or at work.”

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Should AI Be Addictive?

The most interesting piece of news this morning comes from Microsoft’s Satya Nadella, who made a very public point of chastising his own team for saying the quiet part out loud.

That quiet part? In an internal memo leaked to 404 Media, a Microsoft VP said his team’s goal was to “make people addicted” to Microsoft’s new Scout tool, which is fashioned on Open Claw, the AI agent project that went viral early this year. Nadella quickly quashed such sentiments, releasing a memo stating “this is absolutely a non goal! If anything we are doing the exact opposite. We want to make sure AI empowers and adds real value to human endeavor and broad economic growth! We should make our teams clear about this.”

Microsoft then went into damage control mode, with corporate comms chief Frank Shaw piling on that Scout is for “helping people accomplish tasks more effectively—not encouraging dependency. Our goal isn’t more screen time. It’s more time back.”

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Where’s All the AI Magic?

“Hey Google, how are the Giants doing this year?” 

I was standing at my bathroom sink, finishing up my daily ablutions, when a random thought popped into my head. It’s been a minute since I checked in on my favorite baseball team – ever since I moved East, they’ve been in a slump. Maybe they’re pulling back into contention this year? I still have a Google Home plugged in nearby. I’m intimately familiar with the Home’s limitations, but I asked anyway. Perhaps I was hoping one of my annual predictions (voice interfaces for the home) would magically come true.

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Data Is Non Rivalrous. Why Have We Enclosed It?

One of the many reasons I’m a fan of reading history is its ability to offer frameworks for understanding the present. I recently finished Sven Beckert’s Capitalism: A Global History, a 1,300-page monument to scholarship that The New York Times praised as “generational” in its importance. I tend to agree. Its pages contain foundational truths which enliven today’s debate around the role of technology in society.

Beckert argues that over the past millennium, capitalism’s amoral ideology of “accumulation above all else” has become so deeply embedded in the global political economy that we no longer question its core assumptions.

We are the fish, capitalism is the water.

But as Beckert demonstrates, capitalism’s march to omnipresence was a jagged one, filled with reprehensible and often horrifying demonstrations of state, corporate, and personal opportunism at a global scale. If, for example, you had any doubts about the central role slavery played in the creation of the modern industrial economy, Capitalism should dispel them*.

But this post is not a review of the book – I highly recommend it, should you be so inclined. Instead, I want to think out loud about a concept central to its argument: enclosure.

The formal definition of “enclosure” is “the removal of common rights that people held over farm lands and parish commons.” The term is usually associated with the evolution of English society from the late 1500s through the early 1800s, a time when the country transitioned from subsistence-based farming to a market- and export-driven economy. In the name of productivity and profit, and with the enthusiastic support of the monarchy, capitalists enclosed lands formerly held as public commons, forcing a new class of tenant farmers and wage laborers to produce agricultural products for markets opened by the rise of global trade.

While the English may have invented enclosure, they certainly did not have a monopoly on the practice. If we redefine enclosure as leveraging law, violence, or economic pressure to acquire commodity and/or free inputs to drive capitalist outcomes, the list grows well beyond agriculture. Throughout his work, Beckert delivers example after example of capital enclosing nearly all natural resources, including minerals, water, timber and fossil fuels.

Crucially, the practice of enclosure was not limited to commodities. By the mid 1800s, human labor had also been violently enclosed, either through slavery, indenture, indebtedness, or the relatively new practice of wage labor. Beckert demonstrates that the industrial revolution – and our heritage as a capitalist economy – is a byproduct of this enclosure. The modern state, with its ability to wage war and coerce compliance through lawfare, was central to enclosure’s success.

Reading Beckert helps us understand powerful and largely invisible forces driving assumptions behind today’s technology- and information-driven political economy. We learn that capitalism loves nothing more than inexpensive (and if possible, free) inputs which it can turn into profitable market goods. For centuries capitalism built a global economy based on these inputs: labor, cotton, saltpeter, indigo, coal, iron, and oil, among countless others.

These resources all share one critical characteristic: they are rivalrous. A ton of coal or the labor of a worker may power my factory or it may power yours, but it cannot power both. Once it’s used, it’s gone. The same can be said for an acre of land, a bushel of corn, or a roll of steel. Capitalism was built on the concept of rivalry – an endless competition for the non-renewable resources upon which wealth is built.

Beckert’s examination of capitalism necessarily ends just as the information age is gathering strength. But his work leaves me certain that regardless of the changes that digital technology has wrought, one thing remains constant: Capitalism covets and encloses valuable inputs – and once enclosed, capitalists fights like hell to maintain that enclosure.

WHAT ABOUT DATA?

In data, capitalism has found a novel, elastic, and invaluable new input. In an astonishingly short amount of time and just as it did with physical commodities, capitalism has enclosed this new asset and claimed it as its own**.

Whether you are nodding your head or rolling your eyes at that sentiment, it’s hard to argue that the aggregate value of the world’s data is anything but central to our information economy. That we’ve ceded this power to corporations without fully investigating alternative architectures of control will be seen as one of the greatest mistakes of the post-digital era, and the apotheosis of regulatory capture via mechanisms that capital has long used to dominate the state.

Why label our current approach to managing data as a societal asset a historic mistake? It’d likely take at least 1,300 pages to definitively argue that point, but in this post I’ll focus on this one fact:

Data is non-rivalrous.

The Corporate Finance Institute defines non-rivalrous goods as “public goods that are consumed by people but whose supply is not affected by people’s consumption. In other words, when an individual or a group of individuals use a particular good, the supply left for other people to use remains unchanged. Therefore, non-rivalrous goods can be consumed over and over again without the fear of depletion of supply.”

Data are like ideas – if I give you a copy of mine, you gain, but I do not necessarily lose. Centuries before the concept of “data” took root, Thomas Jefferson wrote of ideas:

“That ideas should freely spread from one to another over the globe, for the moral and mutual instruction of man, and improvement of his condition, seems to have been peculiarly and benevolently designed by nature, when she made them, like fire, expansible over all space, without lessening their density in any point, and like the air in which we breathe, move, and have our physical being, incapable of confinement or exclusive appropriation.”

Only 20 years after the British passed the Inclosure Act of 1773, which enabled enclosure of land and the removal of the right of commoners’ access to that land, Jefferson laid the groundwork for an enlightened approach to data.

Shame on us if we decide to ignore him.

*And if you want to go deeper, read Beckert’s widely praised history of the cotton trade, Empire of Cotton. 

**I’ve written about this practice continuously over the past 20 years, but I’ve not definitively linked it to the concept of enclosure. In future writings, I’ll detail how the technology industry, with the full throated support of most western governments, has used Terms of Service and Privacy Policies to enclose data for its own enrichment, and to the detriment of a more flourishing society. 

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What’s Up With DOC? 2026 Program Launches Today

A sampling of the DOC 2026 Faculty

Today my partners and I are launching the program driving our third annual DOC summit, to be held in Sonoma, CA later this fall. When my close friend Dr. Jordan Shlain brought me his idea for a new kind of gathering back in 2023, I had no clue how much I would learn. It wasn’t just about medicine and healthcare science, but also about creating a community. It’s been a great journey so far, and in year three, it will really take off. 

One reason is that while I’ve been the acting CEO for DOC’s early years, we now have a full-time, seasoned pro taking over: Dr. Neil Parikh, who joined us last month. Not only is Neil an entrepreneur, a physician, and an MBA, he’s also got the even temperament and quiet intelligence that commands a room through earned respect. With Neil at the helm, Jordan and I can focus on what we most love to do: bring a community together through the expression of a fantastic program. 

The magic of DOC isn’t in its headliners or its location, though both are fabulous. It’s in the care we take in assembling the people who gather each year. Among the 300 members of our community are scores of physicians, scientists, investors, and business leaders who all share a passion for identifying, scaling, and supporting the highest-quality science behind the medical breakthroughs that have the potential to effect meaningful change, right now. They all are accustomed to keynoting conferences and events around the world. That’s why we consider each DOC program a conversation, not a dictation – and why every participant may interrogate the proceedings at any time with questions or insights that add to that conversation. 

We have something of a “dinner party rule” at DOC – we only invite people we’d want to sit next to at a table filled with fascinating folks. We find these unique individuals via word-of-mouth – through our advisors, colleagues, past participants, and friends. It may not be the most efficient way to build an “events business,” but it’s certainly the best way to build a lasting community. 

This year we’ll be focusing on a host of topics and issues at the forefront of our community’s minds: The impact of AI on medicine. The state of our healthcare system. Breakthroughs in neuroscience that push the boundaries between our minds and the emerging intelligence of artificial intelligence. Advances in women’s health. Joining us to push our thinking will be leaders from government, science, business, and finance, including:

    • Alicia Jackson, Ph.D., Director of ARPA-H. Dr. Jackson is responsible for determining where her agency will place billions of dollars in long term bets on the future state of medical science. 
    • Eddie Chang M.D., Chair of Neurological Surgery at the University of California, San Francisco, whose pioneering work on brain-computer interfaces is redefining the field. 
    • Laura Esserman M.D., MBA, Principal Investigator of the WISDOM Study and Director of the UCSF Carol Franc Buck Breast Care Center, who will report on the initial findings from her ground breaking research on breast cancer detection and risk reduction. 
    • Travis Zack M.D., Ph.D, Chief Medical Officer, OpenEvidence. Zack is the medical mind responsible for the astonishing rise of OpenEvidence, one of the fastest growing and most respected AI companies in the world.  
    • Helen Messier M.D. Ph.D., Chief Medical Officer of Bioscope.AI. Dr. Messier is a physician-scientist and leader in precision and longevity medicine, working at the intersection of molecular biology, clinical care, and new models of care delivery.
    • Larry Brilliant, M.D., a renown epidemiologist, technologist, philanthropist, and author, now CEO of Evity.AI, a startup integrating artificial intelligence with epidemiology and precision medicine.
    • Nicole Gaudelli Ph.D., a life science entrepreneur in residence at Google Venture best known for her work in creating the Adenine Base Editor, a significant advance on the CRISPR gene-editing framework. 
    • George Yancopoulos, M.D., Ph.D., Co-founder, Board co-Chair, President and Chief Scientific Officer, Regeneron. Dr. Yancopoulos is widely recognized as one of the most successful entrepreneurs, scientists and drug discoverers in biotech history. 
    • Divesh Makan, General Partner, Iconiq Capital. Makan is credited with being one of the tech elite’s most trusted investors, and is one of the most savvy and influential investors in the artificial intelligence industry. 

And that’s not even half of the leaders that will join us for the extended conversation this year at DOC. We’re extremely proud of the community we’re building, and if you’re interested in joining us, please let us know! I hope to see at least some of you in Sonoma this Fall. 

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OpenAI Plans on Marketing Its Way To Glory. Bonne Chance!

The cookies have it.

Early this past Saturday morning I got an email from OpenAI titled “Update to our privacy policy and more controls.” I don’t recall ever getting email from the company – I signed up for ChatGPT when it launched, but haven’t used the service much since switching to Claude several years ago. But the email reminded me of a story I read from The Information last week, and I think it’s fair to say the two are related: OpenAI Sees $8 ChatGPT Driving Consumer Subscribers to 122 Million This Year.

I’ve written several posts about OpenAI’s jaw-dropping advertising ambitions, which I believe history will judge as the most audacious and potentially damaging expansion of the Internet’s data-driven advertising model since the invention of AdWords, Google’s original cash cow. OpenAI plans on scaling its advertising revenue from zero in 2025 to more than $100 billion by 2030. As I pointed out earlier, it took Google nearly two decades to reach that milestone.

The Information’s reporting gives us some insights on how OpenAI is planning to hit those lofty goals. Step one is to build out as much advertising inventory as possible by leaning on its free and low-cost subscription models. According to The Information, OpenAI is forecasting that “consumer subscribers to ChatGPT Go, which costs $8 a month in the U.S. and around $5 monthly in other countries such as India, would surge about 36 times to 112 million this year.”

If those numbers make you shrug, pull those shoulders down, and let’s do a bit of math. Two months ago, OpenAI announced it has around 50 million paying subscribers – 62 million fewer than its goal of 112 million for this year. That’s quite a mountain to scale.

But OpenAI is the fastest growing consumer application in the history of the Internet, no? Well, yes, it was. Now? Not so much. Over the past few quarters, OpenAI’s subscriber growth has hit a wall. A report in the Wall Street Journal last week put it starkly: “OpenAI missed an internal goal of reaching one billion weekly active users for ChatGPT by the end of last year, according to people familiar with the goals. The company still hasn’t announced that milestone, unnerving some investors. It also missed its yearly revenue target for ChatGPT as well after Google’s Gemini saw massive growth late last year and ate into OpenAI’s market share.”

So how does OpenAI plan on adding 62 million new paying subscribers this year? That’s where that Saturday morning email comes into play. The email main point is to inform us that OpenAI is now using cookies, those much-maligned pieces of code that drive programmatic advertising across the Internet. “We wanted to let you know that we’ve updated our Privacy Policy to include how we use cookies and other similar technologies,” read the first line of the email.

At first, I figured OpenAI was adding cookies to ensure its still-nascent advertising platform would meet with the expectations of nearly all of its potential marketing customers. Regardless of repeated efforts to kill them, cookies still form the backbone of how marketers measure ad performance. Why is OpenAI making such a big deal about using them?

That’s when it hit me: OpenAI plans on marketing itself out of its subscriber growth problem. Here’s another line from that aforementioned email: “We’ll now use cookies to promote OpenAI products and services on other websites.”

Will they ever! Dig into the company’s updated privacy and cookie policies, and you’ll learn even more: OpenAI employs hundreds of cookies, including more than 40 “marketing measurement” cookies placed on six distinct third-party websites. Those sites – LinkedIn, Reddit, Meta, Google, TikTok, and Bing/Microsoft* – form the foundation of today’s Internet advertising infrastructure.

Put another way, OpenAI is going to use aggressive, performance- and data-driven Internet advertising tactics in an attempt to build the world’s fastest growing … performance- and data-driven Internet advertising business. It reminds me of how TikTok built its US business by flooding Facebook and Instagram with ads to drive TikTok downloads. But unlike TikTok, which has a free service, OpenAI has to convince 62 million more folks to pay a subscription fee. Bonne chance!

We all thought OpenAI was using all that recently acquired capital to build more data centers, but at least a few billion of those dollars will certainly be aimed directly at the company’s much more pressing problem: Acquiring customers. Grab some popcorn and get ready for a blitzkrieg of OpenAI marketing, folks. This will be a show worth binging.

*I can only imagine the folks at Apple and Amazon are pissed they’re not included on OpenAI’s initial media plan. Not to worry, I’m sure they’ll get optimized in!

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Your Conversations With AI Are Now On Sale

OpenAI’s early Ads Manager interface, as posted on Search Engine Roundtable.

Data-driven performance advertising built the modern internet, warts and all. Data has become the most valuable resource in our economy, and the world’s most profitable companies have all organized around enclosing, extracting, processing, refining, and exploiting this new asset class.

Yesterday, OpenAI released its first performance advertising product. Marketers can now purchase “cost per click” advertising on ChatGPT, which means they can compare how money spent on OpenAI measures up to similar platforms like Google, Meta/Instagram, Apple, and Amazon, among many, many others. And if OpenAI’s offerings fail to compete, the company will have no choice but to modify its products to drive better performance.

Put simply, the race is on, and it’s one OpenAI can’t afford to lose. The data we create as we pour our hopes, fears, intimacies, questions, and personal narratives into the insatiable maw of an AI chatbot is being enclosed and exploited by the very same business model that bequeathed us Facebook.

It was inevitable that OpenAI would meet the Internet at its most profitable nexus. Now that it has, the incentive structures of performance advertising will forever imprint the fabric of our interactions with AI, and by extension, our understanding of the world.

Google’s introduction of cost-per-click a quarter century ago sparked a revolution in marketing that has shaped every corner of the digital world.  Not only have the search, social, and mobile industries been built on the back of performance-based advertising units, so have the consumer products that shape our culture: Instagram, Amazon, YouTube, Reddit, Twitter, and of course Google search. An obsession with performance birthed the data-driven “surveillance capitalism” now ubiquitous to nearly every business model on the Internet, from Uber to Apple (and yes, Apple collects and leverages truckloads of data to deliver both advertising and other services).

Given this, the question now becomes: How will the incentives inherent in data-driven advertising impact our experiences with AI? To presume nothing will change is to ignore history and the basic tenets of capitalism. OpenAI has declared ambitions to become a $100 billion performance advertising business in less than four years (it took Google almost two decades to reach that milestone). OpenAI also plans on becoming a trillion-dollar public company by the end of this year. Those kinds of expectations will inevitably force Sam Altman and his team to tailor their consumer products toward the collection and exploitation of their company’s most precious resource: The information we all disgorge into billions of chatbot windows each day.

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