There is a war going on. Humanity and nature are on one side and Big Tech is on the other. The two sides are not opposed. They are orthogonal. The human side is horizontal and the Big Tech side is vertical.*

The human side is personal, social, self-governed, heterarchical, open, and grounded in the physical world. Its model is nature, and the cooperative contexts in which competition, creation, and destruction happen in the natural world.

The Big Tech side is corporate, industrial, hierarchical, competitive, mechanistic, extractive, and closed, even though it produces many positive-sum products and services that are good for people and good for nature. It is also, being competitive and rewarding toward winner-take-most outcomes, dominated by giants.

This war has been fought over many other things in the past, especially in tech. But AI is the big one right now—and perhaps the biggest one of all time.

Over the long run, both sides will win, because we need the best of what both bring to the world’s big round table. In the past, this has happened in countless markets, countries, polities, societies, and other contexts. In tech it happened with the conflict between PCs and mainframes, between the open and public Internet and closed private networks, and between open operating systems and closed ones. None of those conflicts have final outcomes, but they have arrived at stable and cooperative states. They arrived at those states because everyone recognized that people can do more with their own tools than those big entities can do on theirs, or by using people as extracted resources.

This conflict is perhaps best represented by the ironies that have been at work within OpenAI and Sam Altman, its prior and current CEO. We can also see it with sparkling clarity in something amazing that Sam said near the close of his keynote at the first OpenAI Developer Conference, in November of last year:

Lets unpack that.

Individual empowerment means exactly what it says. Agency is the ability to take action or to choose what action to take (Cambridge Dictionary). Scale means growth toward ubiquity.

You have individual empowerment and agency when you ride your bike, drive your car, mow your lawn, or button your shirt. You also have it when you work on your laptop, phone, and other smart rectangles. Scale means your power and agency will grow to the max while the same will happen for nearly everyone else. Scale for you alone won’t cut it. When most of us have it, that’s scale.

Technologies extend us. They enlarge our capacities in the world. Intelligence is one of those capacities. So is memory. Your rectangles help a lot with both. That’s why those have already scaled to ubiquity, or close enough.

AI will do the same, but only if it’s personal. Not if it’s  just “personalized.”

As Jamie Smith made clear here a year ago, “your personal AI isn’t really personal.”

ChatGPT4 doesn’t know that yet. I can tell because I just asked:

Me:
What is “personal AI”?

ChatGPT4:
“Personal AI” refers to artificial intelligence systems that are designed to serve individual users through personalized interactions and services. These AI systems learn from the specific preferences, behaviors, and needs of their users to offer more tailored assistance, recommendations, or information. The goal of personal AI is to enhance user experience by adapting to unique personal profiles.

There are various applications of personal AI, including:

1. Virtual Assistants: Like Siri, Google Assistant, and others, these AIs help with daily tasks such as scheduling, reminders, searching information, and controlling smart home devices, all customized to the user’s habits and preferences.
2. Recommendation Systems: Used in streaming services like Netflix or shopping platforms like Amazon, these AI systems analyze your past behavior to recommend movies, shows, or products you might like.
3. Healthcare: Personal AI can track individual health metrics and provide personalized advice, monitor conditions, or even alert medical professionals if needed.
4. Learning and Development: In education, personal AI can adapt learning materials to the pace and learning style of the student, offering a customized educational experience.
5. Gaming: AI in gaming can adapt to provide a challenge tailored to the player’s skill level or alter the game narrative based on choices made by the player.

The development of personal AI focuses on enhancing user engagement by creating more intuitive and responsive interactions that feel uniquely suited to each individual.

For a second opinion, I asked Google’s Gemini the same question.

Me:
What is “personal AI”?

Gemini:
Personal AI refers to artificial intelligence designed to assist and interact with a specific individual. It’s essentially your own AI companion that learns about you and tailors its services to your needs. Here are some key aspects of personal AI:

1. Personalization: Unlike general-purpose AI assistants, personal AI focuses on you. It learns from your interactions, preferences, and habits to become more helpful over time.
2. Focus on Memory and Knowledge: Some personal AI systems aim to become an extension of your mind. They can store your memories, knowledge, and experiences, making them readily accessible and even usable to help with tasks like writing or communication.
3. Varied Applications: Personal AI can have a wide range of applications. Imagine an AI that helps you:
4. Organize your life: Manage schedules, appointments, and reminders.
5. Boost productivity: Assist with tasks, research, and communication.
6. Enhance creativity: Help you brainstorm ideas or generate creative content.
7. Improve learning: Personalize learning experiences and provide targeted information.

Privacy Concerns: Storing personal data on an AI raises concerns about privacy and security.

Overall, personal AI holds promise for a future where technology seamlessly integrates with our lives, offering personalized assistance and support.

To both companies, personal AI is a personalized service—from them. It’s not something you own and control. It’s not about individual empowerment and agency. It doesn’t extend you. It’s hired prosthesis: an extension of them rather than of you.

Let’s name the category: AIaaS—AI as a Service.

But hats off. OpenAI and Gemini do amazing jobs. So do lots of other AI services by wannabe giants. I use AI every day to improve what I write, to generate and fix images, to answer questions that old-fashioned search engines can’t answer or suck at. I even pay extra for some of it (such as ChatGPT4 and Adobe’s Creative Suite). And it seems they all get better, all the time, at everything. Won’t personalization be good enough, eventually?

No. Because they aren’t you. They also aren’t yours, so they can’t extend you. They can seem to. But they don’t. They also don’t have access to most of your private life. Nor should they.

But your private life could use some AI help. For example—

• Schedules, including on your calendars, past and future
• Health data, including all your medical reports, prescriptions, appointments, insurance information, past and present providers, plus what your watch, phone, and other devices record about you
• Financial records, including bills, receipts, taxes, and anything called an account that involves money
• Travel, including all the movements your phone (and phone company), watch, and car record about where you go and where you’ve been
• Work—past and present, including whatever HR systems know or knew about you
• Contacts—all the people, businesses, and other entities you know
• Business relationships, with brokers, retailers, service providers, whatever
• Subscriptions, including all those “just $1 for the first four weeks” offers you’ve accepted, plus other forms of screwage that are stock-in-trade for companies selling subscription systems to businesses.
• Property, including all the stuff on your shelves, floors, closets, garages, and storage spaces—plus your stocks and real estate.

It’s not easy to visualize what a personal AI might do for those, but let’s try. Here’s how Microsoft’s Copilot (or whatever it’s called this week) did it for me before I got rid of all its misspellings and added my own hunks of text:

All that stuff is data. But most of it is scattered between apps and clouds belonging to Apple, Google, Microsoft, Amazon, Meta, phone companies, cable companies, car makers, health care systems, insurance companies, banks, credit card companies, retailers, and other systems that are not yours. And most of them also think that data is theirs and not yours.

To collect and manage all that stuff, you need tools that don’t yet exist: tools that are yours and not theirs. We could hardly begin to imagine those tools before AI came along. Now we can.

For example, you should be able to take a picture of the books on your shelves and have a complete record of what those books are and where you got them. You’ll know where you got them because you have a complete history of what you bought, where and from whom. You should be able to point your camera in your closets, at the rugs on your floors, at your furniture, at the VIN number of your car that’s visible under your windshield, at your appliances and plumbing fixtures, and have your AI tell you what those are, or at least make far more educated guesses than you can make on your own.

Yes, your AI should be able to tap into external databases and AI systems for help, but without divulging identity information or other private data. Those services should be dependent variables, not independent ones. For full individual empowerment and agency, you need to be independent. So does everyone else with personal AI.

Now imagine having a scanner that you can feed every bill, every receipt, every subscription renewal notice, and have AI software that tells you what’s what with each of them, and sorts records into the places they belong.

Ever notice that the Amazon line items on your credit card bill not only aren’t itemized, but don’t match Amazon’s online record of what you ordered? Your personal AI can sort that out. It can help say which are business and personal expenses, which are suspicious in some way, what doesn’t add up, and much more.

Your personal AI should be able to answer questions like, How many times have I had lunch at this place? Who was I with? When was it we drove to see so-and-so in Wisconsin? What route did we take? What was that one car we rented that we actually liked?

Way back in 1995, when our family first got on the Internet over dial-up, using the first graphical browsers on our PC, and e-commerce began to take off with Amazon, eBay, and other online retailers, my wife asked an essential question: Why can’t I have my own shopping cart that I take from site to site?

Twenty-nine years later, we still don’t have the answer, because every retailer wants you to use its own. And we’re stuck in that system. It’s the same system that has us separately consenting to what sites ironically call “your privacy choices.” And aren’t.

There are countless nice things we can’t have in the digital world today because we aren’t people there. We are accounts. And we are reduced to accounts by every entity that requires a login and password.

This system is a legacy of client-server, a euphemism for slave-master. We might also call it calf-cow, because that’s how we relate to businesses with which we have accounts. And that model is leveraged on the Web like this:

We go to sites for the milk of content and free cookies, whether we want them or not. We are also just “users.”

In the client-server world, servers get scale. Clients have no more scale than what each account—each cow—separately allows. Sure, users get lots of benefits, but scale across many cows is not one of them. And no, “login with Google” and “login with Facebook” are just passes that let calves of ruling cows wander into vassal pastures.

For individual empowerment and scale to happen, we need to be self-sovereign and independent. Personal AI can give that to us. It can do that by solving problems such as the ones listed above, and by working as agents that represent us as human beings—rather than mere users—when we engage with Big Tech’s cows.

This will be a fight at first, because the cows think they run all of nature and not just their own farms. And $trillions are being invested in the same old cattle industry, with AI painted all over the new barns. Comparatively speaking, close to nothing is going toward giving independent and self-sovereign individuals the kind of power and scale Sam Altman says he wants to give us but can’t because he’s on the big cow side of this thing.

So where do we start?

First, with open source code and open standards. We have some already. Llama 3, from Meta AI, is “your own intelligent assistant,” and positions Meta as a more open and user-friendly cow than OpenAI. Meta is still on the top-down Big Tech side of the war we’re in. But hell, we can use what they’ve got. So let’s play with it.

Here on the ground there are all these (with quotage lifted from their sites or reviews such as this one)—

• MindsDB: “an open-source AutoML framework”
• Alt.ai: “It’s an A.I. which aims to digitize users’ intentions and place it on the cloud to let our clones deal with all digital operations.”
• Keras: “a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch”
• PyTorch: “Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration, and Deep neural networks built on a tape-based autograd system
• Tensor Flow: “open-source framework for machine learning”
• CoreNet: a deep neural network toolkit for small and large-scale models, from Apple
• Haystack: an “open source Python framework by deepset for building custom apps with large language models (LLMs).”
• Image Super-Resolution (ISR): “(an) open source tool employs a machine learning model that you can train to guess at the details in a low-resolution image:
• Blender: “A rich interface and numerous plugins make it possible to create complex motion graphics or cinematic vistas”
• DeepFaceLab: “open source deepfake technology that runs on Python”
• tflearn: “an advanced deep learning library”
• PYTensor: “a Python library that allows you to define, optimize/rewrite, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.” (Was Theano)
• LM Studio: “Discover, download, and run local LLMs”
• HuggingFace Transformers: “a popular open-source library for Natural Language Processing (NLP) tasks”
• Fast.ai: “a library for working with deep learning tasks”
• OpenCV: “a popular Computer Vision and Image Processing library developed by Intel”
• Detectron2: “a next-generation library that provides advanced detection and segmentation algorithm” and “a PyTorch-based modular object detection library”
• Ivy.ai: “an open-source deep learning library in Python focusing on research and development”
• OpenAssistant: “a project aimed at giving everyone access to a great chat-based large language model”
• PaddleNLP: “a popular open source NLP library that you can use to glean search sentiment and flag important entities”
• Delphi.AI: “Clone yourself. Build the digital version of you to scale your expertise and availability, infinitely.”
• Fauxpilot: “This is an attempt to build a locally hosted alternative to GitHub Copilot. It uses the SalesForce CodeGen models inside NVIDIA’s Triton Inference Server with the FasterTransformer backend.”
• Ray: “An open source framework to build and scale your ML and Python applications easily”
• Solid: “Solid is a specification that lets individuals and groups store their data securely in decentralized data stores called Pods. Pods are like secure web servers for data. When data is stored in a Pod, its owners control which people and applications can access it.”
• Sagen.ai: “Your very own AI Personal Assistant to manage your digital life.”
• YOLOv7: “is one of the fastest and most accurate open source object detection tools. Just provide the tool with a collection of images full of objects and see what happens next.”

—and lots of others that readers can tell me about. Do that and I will add links later. This is a work in progress.

Below all of those we still need something Linux-like that will become the open base on which lots of other stuff runs. The closest I’ve seen so far is pAI-OS, by Kwaai.ai, a nonprofit I now serve as Chief Intention Officer. I got recruited by Reza Rassool, Kwaai’s founder and chair, because he believes personal AI is required to make The Intention Economy finally happen. So that was a hard offer to refuse. Kwaai also has a large, growing, and active community, which I believe is necessary, cool, and very encouraging.

As with most (maybe all) of the projects listed above, Kwaai is a grass-roots effort by human beings on the natural, human, and horizontal side of a battle with giants who would rather give us personalized AI than have us meet them in a middle to which we will bring personal AI powers of our own. In the long run, we will meet in that middle, because personal AI will be better for everyone than personalized AI alone.

Watch us prove it. Better yet, join the effort.

*I am indebted to Lavonne Reimer for introducing and co-thinking the horizontal vs. vertical frame, and look forward eagerly to her own writings and lecturings on the topic.

This post is for the benefit of anyone wondering about, researching, or going into business on the proposition that selling one’s own personal data is a good idea. Here are some of my learnings from having studied this proposition myself for the last twenty years or more.

1. The business does exist. See eleven companies in Markets for personal data listed among many other VRM-ish businesses on the ProjectVRM wiki.
2. The business category harvesting the most personal data is adtech (aka ad tech and “programmatic”) advertising, which is the surveillance-based side of the advertising business. It is at the heart of what Shoshana Zuboff calls surveillance capitalism, and is now most of what advertising has become online. It’s roughly a trillion-dollar business. It is also nothing like advertising of the Mad Men kind. (Credit where due: old-fashioned advertising, aimed at whole populations, gave us nearly all the brand names known to the world). As I put it in Separating Advertising’s Wheat and Chaff, Madison Avenue fell asleep, direct response marketing ate its brain, and it woke up as an alien replica of itself.
3. Adtech pays nothing to people for their data or data about them. Not personally. Google may pay carriers for traffic data harvested from phones, and corporate customers of auctioned personal data may pay publishers for moments in which ads can be placed in front of tracked individuals’ ears or eyeballs. Still, none of that money has ever gone to individuals for any reason, including compensation for the insults and inconveniences the system requires. So there is little if any existing infrastructure on which paying people for personal data can be scaffolded up. Nor are there any policy motivations. In fact,
4. Regulations have done nothing to slow down the juggernaut of growth in the adtech industry. For Google, Facebook, and other adtech giants, paying huge fines for violations (of the GDPR, the CCPA, the DMA, or whatever) is just the cost of doing business. The GDPR compliance services business is also in the multi-$billion range, and growing fast. In fact,
5. Regulations have made the experience of using the Web worse for everyone. Thank the GDPR for all the consent notices subtracting value from every website you visit while adding cognitive overhead and other costs to site visitors and operators. In nearly every case, these notices are ways for site operators to obey the letter of the GDPR while violating its spirit. And, although all these agreements are contracts, you have no record of what you’ve agreed to. So they are worse than worthless.
6. Tracking people without their clear and conscious invitation or a court order is wrong on its face. Period. Full stop. That tracking is The Way Things Are Done online does not make it right, any more than driving drunk or smoking in crowded elevators was just fine in the 1950s. When the Digital Age matures, decades from now, we will look back on our current time as one thick with extreme moral compromises that were finally corrected after the downsides became clear and more ethically sound technologies and economies came along. One of those corrections will be increasing personal agency rather than just corporate capacities. In fact,
7. Increasing personal independence and agency will be good for markets, because free customers are more valuable than captive ones. Having ways to gather, keep, and make use of personal data is an essential first step toward that goal. We have made very little progress in that direction so far. (Yes, there are lots of good projects listed here, but there we still a long way to go.)
8. Businesses being “user-centric” will do nothing to increase customers’ value to themselves and the marketplace. First, as long as we remain mere “users” of others’ systems, we will be in a subordinate and dependent role. While there are lots of things we can do in that role, we will be able to do far more if we are free and independent agents. Because of that,
9. We need technologies that create and increase personal independence and agency. Personal data stores (aka warehouses, vaults, clouds, life management platforms, lockers, and pods) are one step toward doing that. Many have been around for a long time: ProjectVRM currently lists thirty-three under the Personal Data Stores heading. Some have been there a long time. The problem with all of them is that they are still too focused on what people do as social beings in the Web 2.0 world, rather than on what they can do for themselves, both to become more well-adjusted human beings and more valuable customers in the marketplace. For that,
10. It will help to have independent personal AIs. These are AI systems that work for us, exclusively. None exist yet. When they do, they  will help us manage the personal data that fully matters:
    • Contacts—records and relationships
    • Calendars—where we’ve been, what we’ve done, with whom, where, and when
    • Health records and relationships with providers, going back all the way
    • Financial records and relationships, including past and present obligations
    • Property we have and where it is, including all the small stuff
    • Shopping—what we’ve bought, plan to buy, or might be thinking about,
    • Subscriptions—what we’re paying for, when they end or renew, what kind of deal we’re locked into, and what better ones might be out there.
    • Travel—Where we’ve been, what we’ve done, with whom, and when

Personal AIs are today where personal computers were fifty years ago. Nearly all the AI news today is about modern mainframe businesses: giants with massive data centers churning away on ingested data of all kinds. But some of these models are open sourced and can be made available to any of us for our own purposes, such as dealing with the abundance of data in our own lives that is mostly out of control. Some of it has never been digitized. With AI help it could be.

I’m in a time crunch right now. So, if you’re with me this far, read We can do better than selling our data, which I wrote in 2018 and remains as valid as ever. Or dig The Intention Economy: When Customers Take Charge (Harvard Business Review Press, 2012), which Tim Berners Lee says inspired Solid. I’m thinking about following it up. If you’re interested in seeing that happen, let me know.

A customer looks at a market where choice rules and nobody owns anybody. Source: Microsoft Copilot | Designer

I’m in a discussion of business constituencies. On the list (sourced from the writings of Doug Shapiro) are investors, employees, suppliers, customers, and regulators.

The first three are aware of their membership, but the last two? Not so sure.

Since ProjectVRM works for customers, let’s spin the question around. Do customers have a business constituency? If so, businesses are members by the customer’s grace. She can favor, ignore, or more deeply engage with any of those businesses at her pleasure. She does not “belong” to any of them, even though any or all of them may refer to her, or their many other customers, with possessive pronouns.

Take membership (e.g. Costco, Sam’s Club) and loyalty (CVS, Kroger) programs off the table. Membership systems are private markets, and loyalty programs are misnomered. (For more about that, read the “Dysloyalty” chapter of The Intention Economy.)

Let’s look instead at businesses that customers engage as a matter of course: contractors, medical doctors, auto mechanics, retail stores, restaurants, clubs, farmers’ markets, whatever. Some may be on speed dial, but most are not. What matters in all cases is that these businesses are responsible to their customers. “The real and effectual discipline which is exercised over a workman is that of his customers,” Adam Smith writes. “It is the fear of losing their employment which restrains his frauds and corrects his negligence.” That’s what it means to be a customer’s constituent.

An early promise of the Internet was supporting that “effectual discipline.” For the most part, that hasn’t happened. The “one clue” in The Cluetrain Manifesto said “we are not seats or eyeballs or end users or consumers. we are human beings and our reach exceeds your grasp. deal with it.” Thanks to ubiquitous surveillance and capture by corporate giants and unavoidable platforms, corporate grasp far outreaches customer agency.

That’s one reason ProjectVRM has been working against corporate grasp since 2006, and just as long for customer reach. Our case from the start has been that customer independence and agency are good for business. We just need to prove it.

On April 4, 1968, when I learned with the rest of the world that Martin Luther King Jr. had been assassinated, I immediately thought that the civil rights movement, which King had led, had just been set back by fifty years. I was wrong about that. It ended right then (check that last link). Almost fifty-six years have passed since that assassination, and the cause still has a long way to go: far longer than what MLK and the rest of us had imagined before he was killed.

Also, since MLK was the world’s leading activist for peace and nonviolence, those movements were set back as well. (Have they moved? How much? I don’t have answers. Maybe some of you do.)

I was twenty years old when MLK and RFK were killed, and a junior at Guilford College, a Quaker institution in Greensboro, North Carolina. Greensboro was a hotbed of civil rights activism and strife at the time (and occasionally since). I was an activist of sorts back then as well, both for civil rights and against the Vietnam War. But being an activist, and having moral sympathies of one kind or another, are far less effective in the absence of leadership than they are when leadership is there, and strong.

 Alexei Navalny was one of those leaders. He moved into the past tense today: (1976-2024). His parentheses closed in an Arctic Russian prison. He was only 47 years old. At age 44 he was poisoned—an obvious assassination attempt—and survived, thanks to medical treatment in Germany. He was imprisoned in 2021 after he returned to Russia, and… well, you can read the rest here. Since Navalny was the leading advocate of reform in Russia and opposed Vladimir Putin’s one-man rule of the country, Putin wanted him dead. So now Navalny is gone, and with it much hope of reform.

Not every assassination is motivated by those opposed to a cause. Some assassins are just nuts. John Hinkley Jr. and Mark David Chapman, for example. Hinkley failed to kill Ronald Reagan, and history moved right along. But Chapman succeeded in killing John Lennon, and silence from that grave has persisted ever since.

My point is that assassination works. For causes a leader personifies, the setbacks can be enormous, and in some cases total, or close enough, for a long time.

I hope Alexei Navalny’s causes will still have effects in his absence. Martyrdom in some ways works too. But I expect those effects to take much longer to come about than they would if Navalny were still alive. And I would love to be wrong about that.

After 17 years and 761 episodes, FLOSS Weekly ended its run on the TWiT network yesterday. I hosted the last 179 of those shows. My career as a professional (meaning paid) advocate of open source also ended with that show. The full span ran from 1996, when I first appeared on the Linux Journal masthead, until yesterday: about 27 years.

I still participate in market conversations around the many topics I covered in that span, but I’m mostly working on other stuff now. For example, in random-ish order:

• a commons-based approach to news,
• a history (and archive) based approach to journalism in the Digital Age,
• the Digital Age itself (such as what we make of digital tech and the Internet, and what they make of us),
• blogging, such as in my three blogs here (this one, plus ProjectVRM and Trunkline), and supporting what Dave Winer is doing with Feedland and allied work,
• freeing e-commerce from the grips of giants like Amazon,
• fighting surveillance online and off,
• self-sovereign identity,
• infrastructure old, new, and in the future,
• saving the Internet, and
• making an intention economy happen.

All of those are cars in a cluetrain, about which more below.

They are also featured now and then on Reality 2.o, the podcast Katherine Druckman and I have been doing since our Linux Journal days.

For many decades now, I’ve been spoiled by success. For example, open source, an expression whose current meaning was born in 1998, is now beyond huge. Here’s VentureBeat:

Today, open-source software underpins almost everything: A whopping 97% of applications leverage open-source code, and 90% of companies are applying or using it in some way.

GitHub alone had 413 million open-source software (OSS) contributions in 2022.

“Open-source software is the foundation of 99% of the world’s software,” said Martin Woodward, VP of developer relations at GitHub.

By covering open source for Linux Journal from the start, I helped make that happen.

Same with The Cluetrain Manifesto. “Markets are conversations,” a one-liner of mine that became the first thesis in the manifesto, grew to become a meme that hasn’t gone away. The word cluetrain also appears almost daily in tweets on X, almost a quarter century after it was coined. (When Twitter was still itself, cluetrain was mentioned in tweets several times daily. The decline in cluetrain mentions is one small measure of how lame X has become.)

Also blogging!

Hmmm… I don’t think I ever blogged about my only encounter with Robin Williams. It was at some trade show in the early aughts. There was a scrum of attendees gathered around something or someone unseen in the middle. On the periphery was my old friend Tom Rielly, who quickly grabbed me and pulled me into the middle of the crowd, where stood Robin Williams, with two bags of swag. I almost said, “Hey, you look like Robin Williams, only shorter.” Then Tom introduced me, saying “This is Doc. He’s one of the top five bloggers in the world.” I said, “More like one of the top sixteen, but most of the others are duplicates.” Robin then said something funny, and I responded with something funny of my own, and an all-funny exchange ensued during which my separate self said, “Holy shit! I’m doing humor schtick with Robin Williams and holding my own!” After maybe half a minute of this, I excused myself, saying something like, “I’ll leave you to your private audience here,” and exited the crowd.

Oh, and photography. As of this moment, my photos have had 16,855,107 views on one Flickr account, and 1,470,281 on the other. Visits to those run from the hundreds to thousands per day. A search for my name on Wikimedia Commons also brings up 1850 results, nearly all of which are photos I’ve shared using Creative Commons licensing that encourages use and re-use, which is why many (or most) of them find their way into Wikipedia articles.

I’ve had less luck with the other missions I’ve listed above. But I believe in all of them, and in faith, I truck onward.

By the way, FLOSS Weekly has not slipped below the waves. I expect it will be picked up somewhere else on the Web, and wherever you get your podcasts. (I love that expression because it means podcasting isn’t walled into some giant’s garden.) When FLOSS Weekly becomes re-manifest, I’ll point to it here.

I once said this:

That’s Peter Cushing (familiar to younger folk as Grand Moff Tarkin in Star Wars) pounding a stake through the heart of Dracula in the 1958 movie that modeled every remake after it. Other variants of that caption and image followed, some posted on Twitter before it was bitten by Musk and turned into a zombie called X.

After work started on IEEE P7012—Standard for Machine Readable Personal Privacy Terms, I posted this one:

Merriam-Webster says stakeholder means these things:

1: a person entrusted with the stakes of bettors
2: one that has a stake in an enterprise
3: one who is involved in or affected by a course of action

Specifically (at that second link), a stake is an interest or share in an undertaking or enterprise (among other things irrelevant to our inquiry here).

Do we have an interest in the Internet? In the Web? In search? In artificial intelligence? When “stakeholders” are talked about for any of those things, they tend to be ones in government and industry. Not you and me.

Was anyone representing you at the White House Summit on Artificial Intelligence? How about the AI World Congress coming up next month in London? Or any of the many AI conferences going on this year? Of course, our elected representatives and regulators are supposed to represent us, mostly for the purpose of protecting us as mere “users.” But as we know too well, regulators inevitably work for the regulated. Follow the money.

So my case here is not for regulators to play the Peter Cushing role. That job is yours and mine. We just need the weapons—not just to kill surveillance capitalism, but to do all we can to stop AI from making surveillance more pervasive and killproof than ever.

At this point, just imagining that is still hard. But we need to.

Maybe history will defeat itself.

Remember FreePC? It was a thing, briefly, at the end of the last millennium, right before Y2K pooped the biggest excuse for a party in a thousand years. This may help. The idea was to put ads in the corner of your PC’s screen. The market gave it zero stars, and it failed.

And now comes Telly, hawking free TVs with ads in a corner, and a promise to “optimize your ad experience.” As if anybody wants an ad experience other than no advertising at all.

Negative demand for advertising has been well advertised by both ad blocking (the biggest boycott in human history) and ad-free “prestige” TV, (or SVOD, for subscription video on demand). With those we gladly pay—a lot— not to see advertising. (See numbers here.)

But the advertising business (in the mines of which I toiled for too much of my adult life) has always smoked its own exhaust and excels best at getting high with generous funders. (Yeah, some advertising works, but on the whole people still hate it on the receiving end.)

The fun will come when our own personal AI bots, working for our own asses, do battle with the robot Nazgûls of marketing — and win, because we’re on the Demand side of the marketplace, and we’ll do a better job of knowing what we want and don’t want to buy than marketing’s surveillant AI robots can guess at. Supply will survive, of course. But markets will defeat marketing by taking out the middle creep.

The end state will be one Cluetrain forecast in 1999, Linux Journal named in 2006, the VRM community started working on that same year, and The Intention Economy detailed in 2012. The only thing all of them missed was how customer intentions might be helped by personal AI.

Personal.* Not personalized.

Markets will become new and better dances between Demand and Supply, simply because Demand will have better ways to take the lead, and not just follow all the time. Simple as that.

*For more on how this will work, see Individual Empowerment and Agency on a Scale We’ve Never Seen Before.

For sixteen years, ProjectVRM has encouraged the development of tools and services that solve business problems from the customer side. This work is toward testing a theory: that free customers are more valuable—to themselves and to the businesses they engage—than captive ones. That theory can only be tested when tools for doing that are in place.

We already have some of those tools. Our big four in the digital world are the browser, the phone, email, and texting. In the analog offline world, our best model is cash. From The Cash Model of Customer Experience:

Here’s the handy thing about cash: it gives customers scale. It does that by working the same way for everybody, everywhere it’s accepted. It’s also anonymous by nature, meaning it carries no personal identifiers. Recording what happens with it is also optional, because using it doesn’t require an entry in a ledger (as happens with cryptocurrencies). Cash has also been working this way for thousands of years. But we almost never talk about our “experience” with cash, because we don’t need to.

The problem with our four personal digital tools—browser, phone, email and texting—is that they are not fully ours. So our agency is at best compromised. Specifically,

1. The most popular browsers are also agents of Apple, Google, Microsoft, plus countless thousands of third parties inserting cookies and other tracking instruments into our devices.
2. Our phones are not just ours. They are corporate tentacles of Apple and Google, lined with countless personal data suction cups from unknown surveillance systems. (For more on this, see Apple vs (or plus) Adtech, Part I and Part II.)
3. Apple and Google together supply 87% of all email software and services. Apple promises privacy, while Google makes a business out of knowing the contents of your messages, plus every other Google-provided or -involved piece of software reveals to the company about your life. As for how well Apple delivers on its privacy promises, look up apple+compromised+privacy.
4. The original messaging service for phones, SMS, is owned and run by phone companies. Other major messaging, texting and chat services are run entirely by private companies.
5. Among common Internet activities, only email and browsing are based on open and simple standards. The main ones are SMTP, IMAP, and POP3 for email, and HTTP/S for browsing. Those share the Internet’s three NEA virtues: Nobody owns them, Everybody can use them, and Anybody can improve them.

This is important: If a product or service mostly works for some company, it’s not yours. You are a user or a consumer. You are not a customer; nor are you operating with full agency in a truly free market. So, while it is obvious that all of us are made more valuable to business, and to ourselves, because we use browsers, phones, email, and messaging, we can’t say that we are free while we do.

But the Internet is still young: dating in its current form—supportive of e-commerce—since 30 April 1995, when the NSFNET (one of the Internet’s backbones) was decommissioned, and its policy forbidding commercial traffic on its pipes no longer stood in the way. The Net will also be with us for dozens or hundreds of decades to come, with its base protocol, TCP/IP, continuing to support freedom for every node on it.

More importantly, there are many business problems best or only solved from the customer side. Here is a list:

1. Identity. Logins and passwords are burdensome leftovers from the last millennium. There should be (and already are) better ways to identify ourselves by revealing to others only what we need them to know. Working on this challenge is the SSI—Self-Sovereign Identity—movement.  (Which also goes by many other names. The latest is Web5.) The solution here for individuals is tools of their own that scale. Note that there is a LOT happening here. One good way keep up with it is in the Identisphere newsletter.  You can also participate by attending the twice-yearly Internet Identity Workshop, which has been going strong since 2005.
2. Subscriptions. Nearly all subscriptions are pains in the butt. “Deals” can be deceiving, full of conditions and changes that come without warning. New customers often get better deals than loyal customers. And there are no standard ways for customers to keep track of when subscriptions run out, need renewal, or change. The only way this can be normalized is from the customers’ side.
3. Terms and conditions. In the world today, nearly all of these are ones that companies proffer; and we have little or no choice about agreeing to them. Worse, in nearly all cases, the record of agreement is on the company’s side. Oh, and since the GDPR came along in Europe and the CCPA in California, entering a website has turned into an ordeal typically requiring “consent” to privacy violations the laws were meant to stop. Or worse, agreeing that a site or a service provider spying on us is a “legitimate interest.” The solution here is terms individuals can proffer and organizations can agree to. The first of these is #NoStalking, and allows a publisher to do all the advertising they want, so long as it’s not based on tracking people. Think of it as the opposite of an ad blocker. (Customer Commons is also involved in the IEEE’s P7012 Standard for Machine Readable Personal Privacy Terms.
4. Payments. For demand and supply to be truly balanced, and for customers to operate at full agency in an open marketplace (which the Internet was designed to support), customers should have their own pricing gun: a way to signal—and actually pay willing sellers—as much as they like, however, they like, for whatever they like, on their own terms. There is already a design for that, called EmanciPay. Its promise for the music industry alone is enormous.
5. Intentcasting. Advertising is all guesswork, which involves massive waste. But what if customers could safely and securely advertise what they want, and only to qualified and ready sellers? This is called intentcasting, and to some degree, it already exists. Toward this, the Intention Byway is a core focus of Customer Commons. (Also see a list of intentcasting providers on the ProjectVRM Development Work list.)
6. Shopping. Why can’t you have your own shopping cart—that you can take from store to store? Because we haven’t invented one yet. But we can. And when we do, all sellers are likely to enjoy more sales than they get with the current system of all-silo’d carts.
7. Internet of Things. We don’t have this yet. Instead, we have the Apple of things, the Amazon of things, the Google of things, the Samsung of things, the Sonos of things, and so on, each silo’d in separate systems we don’t control. Things we own on the Internet should be our things. We should be able to control them, as independent operators, as we do with our computers and mobile devices. (Also, by the way, things don’t need to be intelligent or connected to belong to the Internet for us to control what’s known about them. They can be, or have, picos.)
8. Loyalty. All loyalty programs are gimmicks, and coercive. True loyalty is worth far more to companies than the coerced kind, and only customers are in a position to truly and fully express it. We should have our own loyalty programs, to which companies are members, rather than the reverse.
9. Privacy. We’ve had privacy tech in the physical world since the inventions of clothing, shelter, locks, doors, shades, shutters, and other ways to limit what others can see or hear—and to signal to others what’s okay and what’s not. Instead, all we have are unenforced promises by others not to watch our naked selves, or to report what they see to others. Or worse, coerced urgings to “accept” spying on us and distributing harvested information about us to parties unknown, with no record of what we’ve agreed to.
10. Customer service. There are no standard ways for customers and companies to enjoy relationships, with useful data flowing both ways, and for help to come when it’s needed. Instead, every company does it differently, in its own silo’d system. For more on this, see # 12 below.
11. Regulatory compliance. Especially around privacy. Because really, all the GDPR and the CCPA want is for companies to stop spying on people. Without any privacy tech on the individual’s side, however, responsibility for everyone’s privacy is entirely a corporate burden. This is unfair to people and companies alike, as well as insane—because it can’t work. (Worse, nearly all B2B “compliance” solutions only solve the felt need by companies to obey the letter of a law while ignoring its spirit. But if people have their own ways to signal their privacy requirements and expectations (as they do with clothing and shelter in the natural world), life gets a lot easier for everybody, because there’s something there to respect. We don’t have that yet online, but it shouldn’t be hard. For more on this, see Privacy is Personal and our own Privacy Manifesto.
12. Real relationships: ones in which both parties actually care about and help each other, and good market intelligence flows both ways. Marketing by itself can’t do it. All you get is the sound of one hand slapping. (Or, more typically, pleasuring itself with mountains of data and fanciful maths first described in Darrell Huff’s How to Lie With Statistics, written in 1954). Sales departments can’t do it either, because their job is done once the relationship is established. CRM can’t do it without a VRM hand to shake on the customer’s side. From What Makes a Good Customer: “Consider the fact that a customer’s experience with a product or service is far more rich, persistent and informative than is the company’s experience selling those things, or learning about their use only through customer service calls (or even through pre-installed surveillance systems such as those which for years now have been coming in new cars). The curb weight of customer intelligence (knowledge, know-how, experience) with a company’s products and services far outweighs whatever the company can know or guess at. So, what if that intelligence were to be made available by the customer, independently, and in standard ways that work at scale across many or all of the companies the customer deals with?”
13. Any-to-any/many-to-many business: a market environment where anybody can easily do business with anybody else, mostly free of centralizers or controlling intermediaries (with due respect for inevitable tendencies toward federation). There is some movement in this direction around what’s being called Web3.
14. Life management platforms. KuppingerCole has been writing and thinking about these since not long after they gave ProjectVRM an award for its work, way back in 2007. These have gone by many labels: personal data clouds, vaults, dashboards, cockpits, lockers, and other ways of characterizing personal control of one’s life where it meets and interacts with the digital world. The personal data that matters in these is the kind that matters in one’s life: health (e.g. HIEofOne), finances, property, subscriptions, contacts, calendar, creative works, and so on, including personal archives for all of it. Social data out in the world also matters, but is not the place to start, because that data is less important than the kinds of personal data listed above—most of which has no business being sold or given away for goodies from marketers. (See We can do better than selling our data.)

All of these, however, are ocean-boiling ideas. In other words, not easy, especially without what the military calls “robust funding.” So our strategies are best aimed toward what are called “blue” rather than “red” (blood filled) oceans. One of those is the Byway (or “buyway”) project by Customer Commons, in Bloomington, Indiana. An excerpt:

There are three parts to the Byway project as it now stands (in July 2022): an online community (Small Town/mastodon), a matcher tool (Intently), and a local e-commerce “buyway.” (For more on that one, download the slide deck presented by Doc and Joyce at The Mill in November 2021. Or download this earlier and shorter one.)

We also see the Byway as complementary to, rather than competitive with, developments with similar and overlapping ambitions, such as SSI, DIDcomm, picos, JLINC, Digital Homesteading / Dazzle and many others.

Joyce and I, both founders and board members of Customer Commons, are heading up to DWeb Camp in a few minutes, and plan to make progress there on Byway development. I’ll report here on progress.

[Later…] DWeb Camp was a great success for us. We are now in planning conversations with developers and others. Stay tuned for more on that.