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Larry Lessig – Why Can’t We Regulate the Internet Like We Regulate Real Space?

I’ve known Larry Lessig for more than 25 years, and throughout that time, I’ve looked to him for wisdom – and a bit of pique – when it comes to understanding the complex interplay of law, technology, and the future of the Internet. Lessig is currently the Roy L. Furman Professor of Law and Leadership at Harvard Law School. He also taught at Stanford Law School, where he founded the Center for Internet and Society, and at the University of Chicago. He is the author of more than half a dozen books, most of which have deeply impacted my own thinking and writing.

As part of an ongoing speaker series “The Internet We Deserve,” a collaboration with Northeastern’s Burnes Center For Social Change, I had a chance to sit down with Lessig and conduct a wide-ranging discussion covering his views on the impact of money in government’s role as a regulator of last resort. Lessig is particularly concerned about today’s AI-driven information environment, which he says has polluted public discourse and threatens our ability to conduct democratic processes like elections. Below is a transcript of our conversation, which, caveat emptor, is an edited version of AI-assisted output. The video can be found here, and embedded at the bottom of this article.

Vint Cerf: Maybe We Need an Internet Driver’s License

Vint Cerf is one of the most recognizable figures in the pantheon of Internet stardom – and as he enters his ninth decade of a remarkable life, one of its most accomplished. I had the honor of interviewing Dr. Cerf last month as part of the “Rebooting Democracy in the Age of AI” lecture series hosted by the Burnes Center for Social Change at Northeastern University. The conversation also served as the kick-off to my own Burnes Center lecture series, “The Internet We Deserve” where I’ll talk with notable business, policy, technology and academic leaders central to the creation of the Internet as we know it today (last week I spoke with Larry Lessig).

Universally recognized as one of “the fathers of the Internet,” Cerf’s many awards include the National Medal of Technology, the Turing Award, the Presidential Medal of Freedom, the Marconi Prize, and membership in the National Academy of Engineering. Dr. Cerf received his PhD from UCLA, where he worked in the famous lab that built the first nodes of what later became known as the Internet. He has worked at IBM, DARPA, MCI, JPL, and is now Chief Internet Evangelist at Google. Cerf has chaired, formed, and participated in countless working groups, governing bodies, and scientific, technological, and academic organizations.

Predictions 2024: It’s All About The Data

Let’s talk 2024.

2023 was a down year on the predictions front, but at least I’ve learned to sidestep distractions like Trump, crypto, and Musk. If I can avoid talking about the joys of the upcoming election and/or the politics of Silicon Valley billionaires, I’m optimistic I’ll return to form. As always, I am going to write this post with no prep and in one stream-of-conscious sitting. Let’s get to it.

The AI party takes a pause. The technology industry – and by this point, the entire capitalist experiment – is addicted to boom and bust cycles and riddled with blinkered optimism. In 2023 we allowed ourselves to dream of AI genies; we imagined trillions in future economic gains, we invested as if those gains were a certainty. In 2024, we’ll wake up and realize – as we did with the web in the early 2000s – that there’s a lot of hard work to do before our dreams become a reality. I’m not predicting an AI crash – but rather a period of digestion, with a possible side of Tums. Corporations will find their initial pilots less impactful than they hoped, and when told of the sums they must spend to course correct, insist on cutting back. Consumers will become accustomed to genAI’s outputs and begin to rethink their $20 a month subscriptions. Growth will slow, though it will not stagnate. Regulators around the world will take the year to move past Terminator nightmares and into the hard work of deeply understanding AI’s societal impact. IP holders – artists, newspapers, craftspeople – will press their lawsuits and infuse the market with uncertainty and hesitancy. In short, society will take a pause that refreshes. And that will be a good thing.
But Progress Continues… It may feel like a pause, but below the tech media scorekeeping narrative, a growing ecosystem of AI startups will make important strides in areas that will matter beyond 2024. AI is driven by data, and as a society we’re not particularly good at structuring, governing, or sharing data. It makes sense that big companies with access to unholy amounts of structured data pioneered the AI era. (Of course, if you’re not a big company, and you want access to massive amounts of data, it helps to just take it without asking permission). But the AI-driven startups that will make waves in 2024 will do so by structuring discrete chunks of valuable information on behalf of very specific customers. It won’t make many headlines, but taken collectively, it’s this kind of work that will lay the groundwork for AI becoming truly magical. Read More
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The Sites That Never Get Built: Why Today’s Internet Discourages Experimentation

The Dude knows the pitfalls of scattering a loved ones’ ashes…

Every so often I get an idea for a new website or service. I imagine you do as well. Thinking about new ideas is exciting – all that promise and potential. Some of my favorite conversations open with “Wouldn’t it be cool if….”

Most of my ideas start as digital services that take advantage of the internet’s ubiquity. It’s rare I imagine something bounded in real space – a new restaurant or a retail store. I’m an internet guy, and even after decades of enshittification, I still think the internet is less than one percent developed. But a recent thought experiment made me question that assumption. As I worked through a recent “wouldn’t it be cool” moment, I realized just how moribund the internet ecosystem has become, and how deadening it is toward spontaneous experimentation.

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Digital Is Killing Serendipity

The buildings are the same, but the information landscape has changed, dramatically.

Today I’m going to write about the college course booklet, an artifact of another time. I hope along the way we might learn something about digital technology, information design, and why we keep getting in our own way when it comes to applying the lessons of the past to the possibilities of the future. But to do that, we have to start with a story.

Forty years ago this summer I was a rising Freshman at UC Berkeley. Like most 17- or 18- year olds in the pre-digital era, I wasn’t particularly focused on my academic career, and I wasn’t much of a planner either. As befit the era, my parents, while Berkeley alums, were not the type to hover – it wasn’t their job to ensure I read through the registration materials the university had sent in the mail – that was my job. Those materials included a several-hundred-page university catalog laying out majors, required courses, and descriptions of nearly every class offered by each of the departments. But that was all background – what really mattered, I learned from word of mouth, was the course schedule, which was published as a roughly 100-page booklet a few weeks before classes started.

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If We Pay for GPTs like We Pay for Internet Service, What Will We Really Get?

“A swarm of genies in the sky, digital art” via DALL-E

Would you pay $200 a month for generative AI services? It may sound crazy, but I think it’s entirely possible, particularly if the tech and media industries don’t repeat the mistakes of the past.

Think back to the last time you decided to fork over a substantial monthly fee for a new technology or media service. For most of us, it was probably the recent shift to streaming services. If you use more than a few, that bill can add up to nearly $100 a month. But streaming is a (not particularly good) replacement for cable – it’s not a technological marvel that changes how we live, work, and play. To find a new service that rises to that level, we have to go back to the introduction of the smart phone – a device we were willing to spend hundreds of dollars to obtain and an average of $127 a month to keep.

But what made the smart phone great was that it gave us the Internet in our pocket. It was the Internet itself that created an entirely new category – and the Internet Service Provider who was more than happy to charge us for the hookup. Each of us spends an average of $64 a month to stay connected to the Internet. Combine that with the average cost of cell service (and let’s be honest, we don’t pay $127 a month to make calls, we pay to be connected to the Internet) – and now we’re paying $191 a month to stay connected to the Web.

$191 a month. $2,292 a year. That’s some serious cheddar. The Internet has become the gold standard for what hundreds of millions of consumers will pay for a truly game changing technology platform.

I know we’re at the apex of the hype cycle when it comes to generative AI, but I tend to agree that it has the potential to dramatically shift pretty much everything in our already digitally enhanced lives. And while some have argued that advertising is going to pay for AI, I’ve come to the conclusion that advertising will be a side show in the AI revolution. Yes, there’ll be ads, and sure, the marketing industry will change as a result, but if generative AI is really going to be as big, or bigger, than the Internet, I think all of us are going to want to pay for it in the same way.

First, a caveat. My use of GPT services has been pretty limited – I’ve played around with Bing Chat, ChatGPT, and Dall-E, and I’ve got an invitation to use Google’s Bard, but so far none have pulled me into the rabbit hole the way Google search did back in 1998, or AppleLink did in 1987, or Mosaic did when the web broke out in 1993. Then again, I was enraptured with the idea of each of those technologies well before they became breakout services – and the same is true for generative AI. It may not be ready for prime time, but when it matures, its impact will be as transformative as any of those predecessors.

Then again, it’s entirely possible we’ll mess it up. In I Dream of Genies – But Who Will They Work For?, I lay out the fundamental problem: If we allow a handful of companies to deliver us our AI services absent the existence of a robust, open platform, those services will fall prey to exactly the same “enshittification” as cable, cell phones, and most of the Internet. We’ve gotten world-beating connectivity platforms right exactly twice in the history of humanity: First with the printing press, and then again with the open Internet. As long as you have access to the tech and a bit of capital, anyone can print a book or launch a website. I very hope the same will be true of what I’ve been calling AI “genies” – magical services that have the potential to disentangle the digital webs in which we’ve become ensnared, paying off the long-promised and unrealized potential of the digital revolution along the way.

So yes, I’d pay $200 to have access to an army of digital genies ready to work on my behalf. But only if they truly work for me.

Back in 2006-7 I wrote a series of posts on “The Data Bill of Rights.” In it I suggested that all of us should have the right to move our data anywhere we wanted to (Portability), the right to demand edits of data about us held by others (Editing), the right to refuse use of our data (Anonymity), the right to know how our data is being used (Use), the right to sell our data to whoever we want (Value), and the right to control how the data is used by others (Permissions). I’d argue we need the same rights as it relates to how we use genies, perhaps with a few additions.

First, I want an open genie ecosystem – the right to use any damn genie I want, even if some might argue my chosen genie could cause me harm. In short, I want an open web model for genies. Anyone should be able to create a genie and post it online, caveat emptor. As I wrote in that last post, I don’t want to use my insurance provider’s AI genie to disentangle my health claims – I don’t trust them to do what’s right for me. But I sure might trust a genie coded by a team of renegade physicians on a mission to change the health care system. Such a company doesn’t exist, but it will – if we create an open AI ecosystem that allows it. Platform-controlled app stores are most definitely not the model I want to see for a world inhabited by genies.

Also, I want genie neutrality. It’s fine for corporations, services, and platforms to refuse to engage with my genie if it’s proven to do harm to their systems or their customers. But don’t throttle my genie because it’s not your genie, or because it’s better than your genie, or because its existence threatens your shitty business model. We pay for cell phone and internet service because it lets us connect to anything and anyone without fear or favor (well, mostly). The core premise behind that assumption is neutrality – a powerful regulatory assumption that’s been much debated in theory, but mainly supported in practice.

And finally, I want the ability to fire my genie at will, and recover every single shred of data, insight, and content I’ve created using that genie in a format that’s usable by the next genie I hire. Seems obvious, but have you ever tried to get your data out of Twitter or Facebook? Just keeping your mobile number from one carrier to another took decades of lobbying and a Federal policy – so maybe we can learn from all that and get it right this time.

If generative AI truly represents a major shift in the architecture of our relationship to technology and we’re all about to fork over more than $2,000 a year for the privilege, then let’s ask ourselves: What are we really getting in the trade? We should all expect that it will be entirely legal for every one of us to employ AI genies to monitor and optimize all of our data flows, and to leverage those flows as we see fit, regardless of the policies of the platforms and services we might be interacting with.

PS – I think it’s entirely possible that in ten or so years, Internet search – and the billions of ad dollars it represents – might be seen as the equivalent of over-the-air broadcast television. Free, but not worth the rabbit ears. More on that another time.

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Bing, Google, and Conversational Search – Is OpenAI an Arms Merchant, Or a Microsoft Ally?

The Mac represented a new interface paradigm for computing, one that Microsoft ignored – until it couldn’t. Will Google do the same?

Just last week I predicted that Google would leverage ChatGPT to create a conversational interface to its search business, and that Microsoft would do the same in the enterprise data market. I briefly considered that I might have gotten it exactly backwards – Google has a robust enterprise data business in its cloud business (known as GCP), and of course Microsoft has Bing. But I quickly dismissed that notion – figuring that each behemoth would play the GPT card toward their strengths.

While I may have been right about ChatGPT getting a business model this year, it looks like I could be wrong on the details. Here’s The Information with a scoop:

Microsoft is preparing to launch a version of its Bing search engine that uses the artificial intelligence behind ChatGPT to answer some search queries rather than just showing a list of links, according to two people with direct knowledge of the plans. Microsoft hopes the new feature, which could launch before the end of March, will help it outflank Google, its much bigger search rival.

The link is behind a rather expensive paywall (I’m a newly refreshed subscriber), but Engadget and many others have more. Apparently Microsoft negotiated the right to integrate ChatGPT into Bing as part of its $1 billion investment back in 2019, and the fact that Bing’s version could launch as early as March means both OpenAI and Microsoft have been working on this for quite some time.

This leaves so many interesting questions unanswered. Might Google possibly do the same? And more interestingly – can it? Did OpenAI and Microsoft cut an exclusive deal for that initial $1 billion investment – effectively icing Google out? And if they did, is that consistent with the “open” vibe in OpenAI’s very name? In short, is OpenAI going to be an arms dealer, or has it been effectively captured by Microsoft, at least in the search arena? And what about the enterprise?

The Information notes that Microsoft is already repackaging previous versions of OpenAI technology for enterprise clients, and I still think the enterprise is where Microsoft will end up making the most of its partnership with OpenAI. But this news leaves me wondering – what will Google do next?

Partnerships present one of the most consistent strategic conundrums in business. Entire philosophies are built around how companies respond to competitive threat – should we build, or should we buy? Should we partner, or should we compete? Often companies with clear market dominance – like Google in search – will refuse to partner, certain that they have the technical and business scale to beat back new market entrants. In other cases, larger companies will partner for a while, then build their own tech in time (Apple and Intel come to mind).

In the case of OpenAI and ChatGPT, there seem to be two interlocking questions: First, can Google even leverage ChatGPT technology, or has Microsoft boxed them out? And second, if OpenAI is willing to partner, will Google chose to, or will it go its own way?

The answers may lie in another, more abstract question: Is conversational search the future of our information ecosystem, or is it a fad? This all reminds me of the debate around user interfaces in the 1980s. The launch of the Macintosh in 1984 was widely dismissed as a parlor trick by most in the early computer business. While the interface was lovely, and clearly beguiling to the noobs who didn’t matter to “real” computer users, there was no way a clunky “point and click” interface was going to replace the specialized skills mastered by the keyboard jockeys of MS-DOS and Unix.

I’ve long argued that Google represented a command-line interface to the Internet – and over the years, the company (and many others) have labored under that framework, even as they roll out any number of bells and whistles on top of it. But conversational search – a term I’ve been using for nearly twenty years – is potentially as different an experience for the end user as the Mac was to the IBM PC. The rub lies in that “potentially.” For Microsoft, I suppose, there’s not much to lose in trying something radically new. Its search business is less than one-tenth the size of Google’s. For Google, however, it’s fundamentally risky to go all in on a new approach – the old way is simply making them too much money. The company faces a classic innovator’s dilemma – and it will be fun to watch how it responds this year.

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Predictions ’23: Advertising – Netflix, Apple, Amazon, Twitter

I love advertising – particularly digital advertising. There, I said it. Was that so hard? Well, yes, the industry I’ve partnered with for more than three decades can be very difficult to defend – and the past ten or fifteen years have been particularly bad. I’m tempted to say that everything after Google Adwords was a net negative in the world, including Facebook, which was the bastard child of Google, and even the open web and programmatic advertising (a development I’ve previously called “heroic” and “the greatest single artifact of humankind”).

It’s fair to say I have a complicated relationship with what’s come to be called “ad tech” – we developed the first ad servers and banner ads at Wired in the 1990s, I wrote a book about the business and its breakout star (Google) in the early 2000s, I started an advertising-driven open-web business that nearly reached escape velocity around the same time, I still chair an adtech and data-driven descendant of that business today, I’ve work closely with the largest advertiser on the planet for nearly 15 years, I sit on the board of LiveRamp, an essential component of today’s digital marketing ecosystem, I’ve started or advised or invested in countless media companies – most of which are dependent on advertising in one form or another.

So yeah, I love advertising. And I kind of hate it too. With those caveats now duly noted, let’s get into what might be some of the most important developments in the space over the coming year.

First, let’s talk the elephants in the room: Apple, Amazon, Google, and Meta. Remember when they seemed immutable characters in some Marvel franchise – dubbed “The Four” by Prof. Galloway? Five years in, each of those companies has their share of worldly troubles, but no one paying attention would argue they’re going anywhere soon. They’re still four of the most valuable companies on earth, though Facebook (nee Meta) has really been working hard at failing these past few years. So what will happen with them this coming year?

Throughout 2023, we’ll hear talk of “the new duopoly” – Amazon and Apple. Both have far smaller advertising businesses than either Meta or Google, but Amazon and Apple have strategic advantages that will allow them to steal significant share: They are much closer to the consumer than their rivals. Apple, of course, owns a massive consumer data platform (iOS and the iPhone), and despite the insanely great contradiction inherent in a “privacy” company building a data-driven advertising business, Apple will likely grow past $10 billion in advertising revenues in 2023. (I’d write thousands of words on the hypocrisy of Apple crippling the entire ad tech ecosystem even as it becomes what it claims it hates, but for now others have done a far better job). Regardless, Apple will be a major digital advertising story next year.

So will Amazon. Here’s another player with a superior data – this company knows what you look at, what you covet, and what you buy. That’s pretty much the entire bottom of the funnel, and over the past five years, Amazon has quietly built a $30+billion advertising business on top of it. Expect that to grow to nearly $40 billion in 2023 – and spark a wave of competitors in what is now known as the “retail media” business – advertising networks built on top of retail and consumer data (Target, Walmart, and many others have already built such businesses, and while they are viable, they pale in comparison to Amazon’s capacities).

Combined, Amazon and Apple will likely grow $15 billion or more in revenue in just one year – and that growth will come largely at the expense of its “Big Four” rivals Google and Facebook, each of which need tens of billions in growth each year to support their sagging stock prices. Expect one hell of a war between these four in 2023.

Next up in the advertising related predictions: Netflix. I’m sure you’ve been following the Netflix Finally Capitulates To The Advertising Model story, but just in case, here’s a primer. For more than a decade Netflix stood on holier-than-thou ground, claiming it would never allow advertising on its platform (that’d be the Netflix CEO in 2020). Industry folk predicted Netflix would start selling ads regardless (that’d be me, also in 2020). 2022 proved the year it happened. Given the press loves a good “I told you so” story, initial reviews of Netflix’s advertising business launch were laden with loving spoonfuls of schadenfreude. “Tepid,” wrote Variety, arguably the most important industry voice in Netflix’s world. “Least popular,” sniffed the Wall St. Journal, noting, of course, that Netflix’s stock has plummeted over the past year. “Giving money back to advertisers,” gloated Digiday.

So what will happen in 2023? By year’s end Netflix’s experiment in advertising will be seen as a triumph. No company is more motivated, more data-driven, and has hired more accomplished industry veterans than Netflix, and if anyone is going to figure out what has so far been a total shitshow (that’d be the connected television market), it’s going to be Netflix. They’ll test, experiment, fail, learn, test some more, and figure out exactly how many ads each of us will tolerate, and they’ll translate that consumer sentiment into data-laden, at-scale advertising products that brand marketers will buy on sight. By this time next year, those spoonfuls of schadenfreude will have turned into paeans of praise.

And finally, Twitter. Oh, Twitter. In past years I’ve focused lengthy posts on Twitter – what the company should do, what it should avoid, who should buy it. Not this year. This year I’m focusing my predictions solely on one thing: Twitter’s mortality. Which is to say, the business that once constituted 90 percent of its revenue base, advertising, is perilously close to death. Given the company is no longer public, it’s impossible to know how badly Space Voldemort has damaged Twitter’s once-sterling reputation amongst many in the advertising business. However, insiders I’ve spoken to estimate Twitter’s US business, which is its largest, is down more than 60 percent year on year. Rough math would therefore put Twitter’s annual revenues – on track to be more than $5 billion in 2022 – at something like $3 billion on a go forward basis. That makes its consumer data business insanely important – Twitter’s data sales are a nearly half-billion-dollar profit driver that almost no one understands. So here’s my prediction: In 2023, Elon will tire of Twitter, driven as much by the reality of his waning wealth at Tesla (prediction #8, here) as by the sheer biological reality of endorphin fatigue. He’ll hire a real CEO who commands respect in the ad world, contractually obligate himself to not meddle, and find some way to claim victory in what will otherwise become a world-class Harvard Business School Case in What Not To Do. Given all this, in 2023 Twitter will rebound, and by the end of the year, the stories will about the miraculous rebirth of The Bird, because, well, that’s always been Twitter’s story.

So there are three more predictions for 2023: A war between duopolies, a Netflix comeback, and Twitter’s phoenix rising. My first post, which focuses on AI-based predictions, is here. My third, focused on markets, is here. And the summary of all of them is right here. Thanks for reading!

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This is the second in a series of posts exploring my 2023 predictions. Previous predictions:

Predictions 2022

2022: How I Did

Predictions 2021

Predictions 21: How I Did

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Predictions ’23: AI Gets a Business Model (or Three)

Let’s start our 2023 predictions off with some thoughts on artificial intelligence. With ChatGPT, Silicon Valley seems to have gotten a bit of its mojo back. After two decades spent simmering the magic of Apple, Google, Amazon and Facebook into a sticky lucre of corporate profit, here was the kind of technological marvel the industry seemed to have forgotten how to make – a magical tour de force that surprised, mystified, and delighted millions.

Even better, ChatGPT didn’t come from any of those corporate titans – not directly, anyway. Instead it came from a non-profit artificial intelligence research laboratory called OpenAI. Founded in 2015 with a mission of furthering “responsible AI,” OpenAI is backed by some of the most celebrated names in Valley technology – LinkedIn’s Reid Hoffman, PayPal’s Peter Theil, Tesla’s Elon Musk among them. Now this was more like it!

ChatGPT seemed to burst from nowhere – but of course, like Google or TikTok before it, its success leverages years of consumer behavioral data and decades of academic research in mathematics, artificial intelligence, and linguistic models. Over the past seven years, OpenAI has evolved its corporate structure to incorporate a for-profit model and more traditional venture investment schemes – with all their attendant complexities. Now owned in large part by the very investors who gave us tech’s last two decades of mixed blessings, it remains to be seen if OpenAI will remain true to its mission of ensuring “that artificial general intelligence benefits all of humanity.”

But let’s be real here: It takes capital to build at-scale AI applications – a lot of it. For all its tickling of the popular imagination, ChatGPT lacks a business model. And one of the most ironclad mandates of money is that money sown must become money reaped. Which takes us to the question driving my first predictions for the coming year: ChatGPT will drive several significant innovations in digital business models. The first will be for ChatGPT itself – it will start to license its technology to at-scale clients, initially to OEMs who will blend ChatGPT with their own offerings. The next two will come via ChatGPTs first big new clients. Google, which played an integral – if largely unsung – role in the technology behind ChatGPT – will launch a ChatGPT-like version of its core search offering. In enterprise markets, Microsoft, which invested a cool billion in the for-profit iteration of OpenAI – will launch a ChatGPT-inspired service aimed at its largest corporate clients.

Google: Conversational Search

“Oh sh*t, Google’s screwed.” That’s the consensus of scores of hot-takes on ChatGPT’s launch. “‘Code Red’ for Google’s Search Business,” declared the New York Times. The NY Post, naturally, took it further: “‘Scary’ AI ChatGPT could eliminate Google within 2 years.” And Casey Newton, one of my favorite tech reporters, said ChatGPT makes Google “feel positively prehistoric.”

Ouch. I tend to disagree with all those hot takes, but as the old Valley trope states, only the paranoid survive, and certainly ChatGPT’s success is a reason for the folks at Google to be looking over their shoulders. Or perhaps more fittingly, into the mirror, where they likely see a company that’s developed an unflattering middle-age paunch. Could it really be outrun by a smaller, more agile version of itself? Is that even possible anymore?

I’m quite sure the board and major investors in Alphabet, Google’s parent company, are not only asking these questions, they’re demanding answers. And those answers will most likely take the form of a new product from Google in 2023 that I’ll call “Conversational Search.” (If you’ve read this site for the past two decades, that term will certainly resonate!).

Here’s how I imagine it might work. Pairing the open APIs and source code of OpenAI (assuming the newly for-profit company will allow it), Google’s massive trove of voice data, and/or its own internal chat platform, Google will build a novel conversational interface to its flagship Google search application. Text-based search has always had what I call a “modal” problem: often the first answer to a query isn’t accurate. Many in the search field wish they could pop up a modal dialog after an unsuccessful search, asking “Did you mean…?” This would allow the engine to both refine results, and gather critical data that would allow it to better answer the query next time. But there’s a problem: More than 50 percent of users will abandon their search when they see a modal dialog box.

The ChatGPT model of conversational “prompt and response” solves for this problem, providing a fresh context for how humans like to gather information (in essence, by talking to each other). The company will probably dub its first efforts in conversation search as “experimental” – Gmail was famously in beta for five years – but this will be deadly serious project.

Plus, it’ll be fun. Imagine a mashup of Google’s high-fidelity search with the serendipity and human-like conversational tone of ChatGPT. Unlike the stilted voice prompts of Alexa, Google Home, or (shudder) Siri, Conversational Search would be like talking with endlessly wise, patient, and intelligent guru. Pulling such a feat off would take and extraordinary amount of work, CPU cycles, and scale, but…Google is capable of all that and more. Plus, Google is strongly motivated to figure out a business model for Conversational Search, and it’s the one company both most likely to pull it off, and with the most to lose if it doesn’t. Marketers have been crying out for brand-friendly innovations in digital advertising, and Conversational Search could be just the ticket (for more on that, I’ll link to a future post here, once I’ve written it).

Microsoft: Enterprise Explorer

Microsoft also has a consumer search business (Bing, anyone?) but the company makes its money in enterprise software, and it’s already in the business of selling AI solutions to big companies worldwide. What I’ll call “Enterprise Explorer” could be a hugely successful – and profitable – upsell to its top clients, who wouldn’t mind paying, say, another $10 million or so a year to have a useful, sexy, and energizing new application at their disposal.

So what would Enterprise Explorer (E2, to be corporate cute) be? Built, again, from a mashup of OpenAI technology and Microsoft’s Azure compute platform, E2 would address some of ChatGPT’s most annoying problems – its indifference to truth, for example, or the biases inherent to its Web-scale training corpus. The idea would be this: Train a specific ChatGPT instance on just the body of data owned or operated by a particular corporation. Most large companies have access to petabytes of internal data – everything from customer databases to internal messaging and document management platforms, all accreted over decades. Add in partner data – cleaned and secured through industry-standard methods like data safe havens – and you could hit a tipping point in terms of pattern recognition and results. E2 could spark a revolution in accessing, querying, and delivering enterprise- and industry-specific intelligence – finally paying off decades of empty promises about the power of digitization and “executive information systems.” Imagine every employee being able to – quite literally – ask the enterprise questions about itself. The mind…boggles. As with Google and Conversational Search, pulling off such a feat would require a staggering amount of innovation and work. And again, just as with Google, Microsoft is deeply motivated to do exactly that.

So to summarize, my first three predictions are this: One, that ChatGPT finds a business model, two, that Google launches an initially experimental Conversational Search interface, and three, that Microsoft announces or launches an Enterprise Explorer-like application for its major Azure clients.

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This is the first in a series of posts exploring my 2023 predictions. Here’s a link to the second post, and the third. And here’s a link to the summary post. Thanks for reading!

Previous predictions: