net.wars

Predatory inclusion

The recent past is a foreign country; they view the world differently there.

At last week’s We Robot conference on technology, policy, and law, the indefatigably detail-oriented Sue Glueck was the first to call out a reference to the propagation of transparency and accountability by the “US and its allies” as newly out of date. From where we were sitting in Windsor, Ontario, its conjoined fraternal twin, Detroit, Michigan, was clearly visible just across the river. But: recent events.

As Ottawa law professor Teresa Scassa put it, “Before our very ugly breakup with the United States…” Citing, she Anu Bradford, she went on, “Canada was trying to straddle these two [US and EU] digital empires.” Canada’s human rights and privacy traditions seem closer to those of the EU, even though shared geography means the US and Canada are superficially more similar.

We’ve all long accepted that the “technology is neutral” claim of the 1990s is nonsense – see, just this week, Luke O’Brien’s study at Mother Jones of the far-right origins of the web-scraping facial recognition company Clearview AI. The paper Glueck called out, co-authored in 2024 by Woody Hartzog, wants US lawmakers to take a tougher approach to regulating AI and ban entirely some systems that are fundamentally unfair. Facial recognition, for example, is known to be inaccurate and biased, but improving its accuracy raises new dangers of targeting and weaponization, a reality Cynthia Khoo called “predatory inclusion”. If he were writing this paper now, Hartzog said, he would acknowledge that it’s become clear that some governments, not just Silicon Valley, see AI as a tool to destroy institutions. I don’t *think* he was looking at the American flags across the water.

Later, Khoo pointed out her paper on current negotiations between the US and Canada to develop a bilateral law enforcement data-sharing agreement under the US CLOUD Act. The result could allow US police to surveil Canadians at home, undermining the country’s constitutional human rights and privacy laws.

In her paper, Clare Huntington proposed deriving approaches to human relationships with robots from family law. It can, she argued, provide analogies to harms such as emotional abuse, isolation, addiction, invasion of privacy, and algorithmic discrimination. In response, Kate Darling, who has long studied human responses to robots, raised an additional factor exacerbating the power imbalance in such cases: companies, “because people think they’re talking to a chatbot when they’re really talking to a company.” That extreme power imbalance is what matters when trying to mitigate risk (see also Sarah Wynn-Williams’ recent book and Congressional testimony on Facebook’s use of data to target vulnerable teens).

In many cases, however, we are not agents deciding to have relationships with robots but what AJung Moon called “incops”, or “incidentally co-present”. In the case of the Estonian Starship delivery robots you can find in cities from San Francisco to Milton Keynes, that broad category includes human drivers, pedestrians, and cyclists who share their spaces. In a study, Adeline Schneider found that white men tended to be more concerned about damage to the robot, where others worried more about communication, the data they captured, safety, and security. Delivery robots are, however, typically designed with only direct users in mind, not others who may have to interact with it.

These are all social problems, not technological ones, as conference chair Kristen Thomasen observed. Carys Craig later modified it: technology “has compounded the problems”.

This is the perennial We Robot question: what makes robots special? What qualities require new laws? Just as we asked about the Internet in 1995, when are robots just new tools for old rope, and when do they bring entirely new problems? In addition, who is responsible in such cases? This was asked in a discussion of Beatrice Panattoni‘s paper on Italian proposals to impose harsher penalties for crime committed with AI or facilitated by robots. The pre-conference workshop raised the same question. We already know the answer: everyone will try to blame someone or everyone else. But in formulating a legal repsonse, will we tinker around the edges or fundamentally question the criminal justice system? Andrew Selbst helpfully summed up: “A law focusing on specific harms impedes a structural view.”

At We Robot 2012, it was novel to push lawyers and engineers to think jointly about policy and robots. Now, as more disciplines join the conversation, familiar Internet problems surface in new forms. Human-robot interaction is a four-dimensional version of human-computer interaction; I got flashbacks to old hacking debates when Elizabeth Joh wondered in response to Panattoni’s paper if transforming a robot into a criminal should be punished; and a discussion of the use of images of medicalized children for decades in fundraising invoked publicity rights and tricky issues of consent.

Also consent-related, lawyers are starting to use generative AI to draft contracts, a step that Katie Szilagyi and Marina Pavlović suggested further diminishes the bargaining power already lost to “clickwrap”. Automation may remove our remaining ability to object from more specialized circumstances than the terms and conditions imposed on us by sites and services. Consent traditionally depends on a now-absent “meeting of minds”.

The arc of We Robot began with enthusiasm for robots, which waned as big data and generative AI became players. Now, robots/AI are appearing as something being done to us.

Illustrations: Detroit, seen across the river from Windsor, Ontario.

Wendy M. Grossman is the 2013 winner of the Enigma Award. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.

Catoptromancy

It’s a commonly held belief that technology moves fast, and law slowly. This week’s We Robot workshop day gave the opposite impression: these lawyers are moving ahead, while the technology underlying robots is moving slower than we think.

A mainstay of this conference over the years has been Bill Smart‘s and Cindy Grimm‘s demonstrations of the limitations of the technologies that make up robots. This year, that gambit was taken up by Jason Millar and AJung Moon. Their demonstration “robot” comprised six people – one brain, four sensors, and one color sensor. Ordering it to find the purple shirt quickly showed that robot programming isn’t getting any easier. The human “sensors” can receive useful information only as far as their outstretched fingertips, and even then the signal they receive is minimal.

“Many of my students program their robots into a ditch and can’t understand why,” Moon said. It’s the required specificity. For one thing, a color sensor doesn’t see color; it sends a stream of numeric values. It’s all 1s and 0s and tiny engineering decisions whose existence is never registered at the policy level but make all the difference. One of her students, for example, struggled with a robot that kept missing the croissant it was supposed to pick up by 30 centimeters. The explanation turned out to be that the sensor was so slow that the robot was moving a half-second too early, based on historical information. They had to insert a pause before the robot could get it right.

So much of the way we talk about robots and AI misrepresents those inner workings. A robot can’t “smell honey”; it merely has a sensor that’s sensitive to some chemicals and not others. It can’t “see purple” if its sensors are the usual red, green, blue. Even green may not be identifiable to an RGB sensor if the lighting is such that reflections make a shiny green surface look white. Faster and more diverse sensors won’t change the underlying physics. How many lawmakers understand this?

Related: what does it mean to be a robot? Most people attach greater intelligence to things that can move autonomously. But a modern washing machine is smarter than a Roomba, while an iPhone is smarter than either but can’t affect the physical world, as Smart observed at the very first We Robot, in 2012.

This year we are in Canada – to be precise, in Windsor, Ontario, looking across the river to Detroit, Michigan. Canadian law, like the country itself, is a mosaic: common law (inherited from Britain), civil law (inherited from France), and myriad systems of indigenous peoples’ law. Much of the time, said Suzie Dunn, new technology doesn’t require new law so much as reinterpretation and, especially, enforcement of existing law.

“Often you can find criminal law that already applies to digital spaces, but you need to educate the legal system how to apply it,” she said. Analogous: in the late 1990s, editors of the technology section at the Daily Telegraph had a deal-breaking question: “Would this still be a story if it were about the telephone instead of the Internet?”

We can ask that same question about proposed new law. Dunn and Katie Szilagyi asked what robots and AI change that requires a change of approach. They set us to consider scenarios to study this question: an autonomous vehicle kills a cyclist; an autonomous visa system denies entry to a refugee who was identified in her own country as committing a crime when facial recognition software identifies her in images of an illegal LGBTQ protest. In the first case, it’s obvious that all parties will try to blame someone – or everyone – else, probably, as Madeleine Clare Elish suggested in 2016, on the human driver, who becomes the “moral crumple zone”. The second is the kind of case the EU’s AI Act sought to handle by giving individuals the right to meaningful information about the automated decision made about them.

Nadja Pelkey, a curator at Art Windsor-Essex, provided a discussion of AI in a seemingly incompatible context. Citing Georges Bataille, who in 1929 saw museums as mirrors, she invoked the word “catoptromancy”, the use of mirrors in mystical divination. Social and political structures are among the forces that can distort the reflection. So are the many proliferating AI tools such as “personalized experiences” and other types of automation, which she called “adolescent technologies without legal or ethical frameworks in place”.

Where she sees opportunities for AI is in what she called the “invisible archives”. These include much administrative information, material that isn’t digitized, ephemera such as exhibition posters, and publications. She favors small tools and small private models used ethically so they preserve the rights of artists and cultural contexts, and especially consent. In a schematic she outlined a system that can’t be scraped, that allows data to be withdrawn as well as added, and that enables curiosity and exploration. It’s hard to imagine anything less like the “AI” being promulgated by giant companies. *That* type of AI was excoriated in a final panel on technofascism and extractive capitalism.

It’s only later I remember that Pelkey also said that catoptromancy mirrors were first made of polished obsidian.

In other words, black mirrors.

Illustrations: Divination mirror made of polished obsidian by artisans of the Aztec Empire of Mesoamerica between the 15th and 16th centuries (via Wikimedia

A short history of We Robot 2012-

On the eve of We Robot 2025, here are links to my summaries of previous years. 2014 is missing; I didn’t make it that year for family reasons. There was no conference in 2024 in order to move the event back to its original April schedule (covid caused its move to September in 2020). These are my personal impressions; nothing I say here should be taken as representing the conference, its founders, its speakers, or their institutions.

We Robot was co-founded by Michael Froomkin, Ryan Calo, and Ian Kerr to bring together lawyers and engineers to think early about the coming conflicts in robots, law, and policy.

2024 No conference.

2023 The end of cool. After struggling to design a drone delivery service that had any benefits over today’s cycling couriers, we find ourselves less impressed by robot that can do somersaults but not do anything useful.

2022 Insert a human. “Robots” are now “sociotechnical systems”.

Workshop day Coding ethics. The conference struggles to design an ethical robot.

2021 Plausible diversions. How will robots rehape human space?

Workshop day Is the juice worth the squeeze?. We think about how to regulate delivery robots, which will likely have no user-serviceable parts. Title from Woody Hartzog.

2020 (virtual) The zero on the phone. AI exploitation becomes much more visible.

2019 Math, monsters, and metaphors. The trolley problem is dissected; the true danger is less robots than the “pile of math that does some stuff”.

Workshop day The Algernon problem. New participants remind that robots/AI are carrying out the commands of distant owners.

2018 Deception. The conference tries to tease out what makes robots different and revisits Madeleine Clare Elish’s moral crumple zones after the first pedestrian death by self-driving car.

Workshop day Late, noisy, and wrong. Engineers Bill Smart and Cindy Grimm explain why sensors never capture what you think they’re capturing and how AI systems use their data.

2017 Have robot, will legislate. Discussion of risks this year focused on the intermediate sitaution, when automation and human norms clash.

2016 Humans all the way down. Madeline Clare Elish introduces “moral crumple zones”.

Workshop day: The lab and the world. Bill Smart uses conference attendees in formation to show why building a robot is difficult.

2015 Multiplicity. A robot pet dog begs its owner for an upgraded service subscription.

2014 Missed conference

2013 Cautiously apocalyptic. Diversity of approaches to regulation will be needed to handle the diversity of robots.

2012 A really fancy hammer with a gun. Unsentimental engineer Bill Smart provided the title.

Cognitive dissonance

The annual State of the Net, in Washington, DC, always attracts politically diverse viewpoints. This year was especially divided.

Three elements stood out: the divergence between the only remaining member of the Privacy and Civil Liberties Oversight Board (PCLOB) and a recently-fired colleague; a contentious panel on content moderation; and the yay, American innovation! approach to regulation.

As noted previously, on January 29 the days-old Trump administration fired PCLOB members Travis LeBlanc, Ed Felten, and chair Sharon Bradford Franklin; the remaining seat was already empty.

Not to worry, remaining member Beth Williams, said. “We are open for business. Our work conducting important independent oversight of the intelligence community has not ended just because we’re currently sub-quorum.” Flying solo she can greenlight publication, direct work, and review new procedures and policies; she can’t start new projects. A review is ongoing of the EU-US Privacy Framework under Executive Order 14086 (2022). Williams seemed more interested in restricting government censorship and abuse of financial data in the name of combating domestic terrorism.

Soon afterwards, LeBlanc, whose firing has him considering “legal options”, told Brian Fung that the outcome of next year’s reauthorization of Section 702, which covers foreign surveillance programs, keeps him awake at night. Earlier, Williams noted that she and Richard E. DeZinno, who left in 2023, wrote a “minority report” recommending “major” structural change within the FBI to prevent weaponization of S702.

LeBlanc is also concerned that agencies at the border are coordinating with the FBI to surveil US persons as well as migrants. More broadly, he said, gutting the PCLOB costs it independence, expertise, trustworthiness, and credibility and limits public options for redress. He thinks the EU-US data privacy framework could indeed be at risk.

A friend called the panel on content moderation “surreal” in its divisions. Yael Eisenstat and Joel Thayer tried valiantly to disentangle questions of accountability and transparency from free speech. To little avail: Jacob Mchangama and Ari Cohn kept tangling them back up again.

This largely reflects Congressional debates. As in the UK, there is bipartisan concern about child safety – see also the proposed Kids Online Safety Act – but Republicans also separately push hard on “free speech”, claiming that conservative voices are being disproportionately silenced. Meanwhile, organizations that study online speech patterns and could perhaps establish whether that’s true are being attacked and silenced.

Eisenstat tried to draw boundaries between speech and companies’ actions. She can still find on Facebook the sme Telegram ads containing illegal child sexual abuse material that she found when Telegram CEO Pavel Durov was arrested. Despite violating the terms and conditions, they bring Meta profits. “How is that a free speech debate as opposed to a company responsibility debate?”

Thayer seconded her: “What speech interests do these companies have other than to collect data and keep you on their platforms?”

By contrast, Mchangama complained that overblocking – that is, restricting legal speech – is seen across EU countries. “The better solution is to empower users.” Cohn also disliked the UK and European push to hold platforms responsible for fulfilling their own terms and conditions. “When you get to whether platforms are living up to their content moderation standards, that puts the government and courts in the position of having to second-guess platforms’ editorial decisions.”

But Cohn was talking legal content; Eisenstat was talking illegal activity: “We’re talking about distribution mechanisms.” In the end, she said, “We are a democracy, and part of that is having the right to understand how companies affect our health and lives.” Instead, these debates persist because we lack factual knowledge of what goes on inside. If we can’t figure out accountability for these platforms, “This will be the only industry above the law while becoming the richest companies in the world.”

Twenty-five years after data protection became a fundamental right in Europe, the DC crowd still seem to see it as a regulation in search of a deal. Representative Kat Cammack (R-FL), who described herself as the “designated IT person” on the energy and commerce committee, was particularly excited that policy surrounding emerging technologies could be industry-driven, because “Congress is *old*!” and DC is designed to move slowly. “There will always be concerns about data and privacy, but we can navigate that. We can’t deter innovation and expect to flourish.”

Others also expressed enthusiasm for “the great opportunities in front of our country”, compared the EU’s Digital Markets Act to a toll plaza congesting I-95. Samir Jain, on the AI governance panel, suggested the EU may be “reconsidering its approach”. US senator Marsha Blackburn (R-TN) highlighted China’s threat to US cybersecurity without noting the US’s own goal, CALEA.

On that same AI panel, Olivia Zhu, the Assistant Director for AI Policy for the White House Office of Science and Technology Policy, seemed more realistic: “Companies operate globally, and have to do so under the EU AI Act. The reality is they are racing to comply with [it]. Disengaging from that risks a cacophony of regulations worldwide.”

Shortly before, Johnny Ryan, a Senior Fellow at the Irish Council for Civil Liberties posted: “EU Commission has dumped the AI Liability Directive. Presumably for “innovation”. But China, which has the toughest AI law in the world, is out innovating everyone.”

Illustrations: Kat Cammack (R-FL) at State of the Net 2025.

The Gulf of Google

In 1945, the then mayor of New York City, Fiorello La Guardia signed a bill renaming Sixth Avenue. Eighty years later, even with street signs that include the new name, the vast majority of New Yorkers still say things like, “I’ll meet you at the southwest corner of 51st and Sixth”. You can lead a horse to Avenue of the Americas, but you can’t make him say it.

US president Donald Trump’s order renaming the Gulf of Mexico offers a rarely discussed way to splinter the Internet (at the application layer, anyway; geography matters!), and on Tuesday Google announced it would change the name for US users of its Maps app. As many have noted, this contravenes Google’s 2008 policy on naming bodies of water in Google Earth: “primary local usage”. A day later, reports came that Google has placed the US on its short list of sensitive countries – that is, ones whose rulers dispute the names and ownership of various territories: China, Russia, Israel, Saudi Arabia, Iraq.

Sharpieing a new name on a map is less brutal than invading, but it’s a game anyone can play. Seen on Mastodon: the bay, now labeled “Gulf of Fragile Masculinity”.

***

Ed Zitron has been expecting the generative AI bubble to collapse disastrously. Last week provided an “Is this it?” moment when the Chinese company DeepSeek released reasoning models that outperform the best of the west at a fraction of the cost and computing power. US stock market investors: “Let’s panic!”

The code, though not the training data, is open source, as is the relevant research. In Zitron’s analysis, the biggest loser here is OpenAI, though it didn’t seem like that to investors in other companies, especially Nvidia, whose share price dropped 17% on Tuesday alone. In an entertaining sideshow, OpenAI complains that DeepSeek stole its code – ironic given the history.

On Monday, Jon Stewart quipped that Chinese AI had taken American AI’s job. From there the countdown started until someone invoked national security.

Nvidia’s chips have been the picks and shovels of generative AI, just as they were for cryptocurrency mining. In the latter case, Nvidia’s fortunes waned when cryptocurrency prices crashed, ethercoin, among others, switched to proof of stake, and miners shifted to more efficient, lower-cost application-specific integrated circuits. All of these lowered computational needs. So it’s easy to believe the pattern is repeating with generative AI.

There are several ironies here. The first is that the potential for small language models to outshine large ones has been known since at least 2020, when Timnit Gebru, Emily Bender, Margaret Mitchell, and Angelina McMillan-Major published their stochastic parrots paper. Google soon fired Gebru, who told Bloomberg this week that AI development is being driven by FOMO rather than interesting questions. Second, as an AI researcher friend points out, Hugging Face, which is trying to replicate DeepSeek’s model from scratch, said the same thing two years ago. Imagine if someone had listened.

***

A work commitment forced me to slog through Ross Douthat’s lengthy interview with Marc Andreessen at the New York Times. Tl;dr: Andreessen says Silicon Valley turned right because Democrats broke The Deal under which Silicon Valley supported liberal democracy and the Democrats didn’t regulate them. In his whiny victimhood, Andreessen has no recognition that changes in Silicon Valley’s behavior – and the scale at which it operates – are *why* Democrats’ attitudes changed. If Silicon Valley wants its Deal back, it should stop doing things that are obviously exploitive. Random case in point: Hannah Ziegler reports at the Washington Post that a $1,700 bassinet called a “Snoo” suddenly started demanding $20 per month to keep rocking a baby all night. I mean, for that kind of money I pretty much expect the bassinet to make its own breast milk.

***

Almost exactly eight years ago, Donald Trump celebrated his installation in the US presidency by issuing an executive order that risked up-ending the legal basis for data flows between the EU, which has strict data protection laws, and the US, which doesn’t. This week, he did it again.

In 2017, Executive Order 13768 dominated Computers, Privacy, and Data Protection. The deal in place at the time, Privacy Shield, eventually survived until 2020, when it was struck down in lawyer Max Schrems’s second such case. It was replaced by the Transatlantic Data Privacy Framework, which established the five-member Privacy and Civil Liberties Oversight Board to oversee surveillance and, as Politico explains, handle complaints from Europeans about misuse of their data.

This week, Trump rendered the board non-operational by firing its three Democrats, leaving just one Republican-member in place.*

At Techdirt, Mike Masnick warns the framework could collapse, costing Facebook, Instagram, WhatsApp, YouTube, exTwitter, and other US-based services (including Truth Social) their European customers. At his NGO, noyb, Schrems himself takes note: “This deal was always built on sand.”

Schrems adds that another Trump Executive Order gives 45 days to review and possibly scrap predecessor Joe Biden’s national security decisions, including some the framework also relies on. Few things ought to scare US – and, in a slew of new complaints, Chinese – businesses more than knowing Schrems is watching.

Illustrations: The Gulf of Mexico (NASA, via Wikimedia).

*Corrected to reflect that the three departing board members are described as Democrats, not Democrat-appointed. In fact, two of them, Ed Felten and Travis LeBlanc, were appointed by Trump in his original term.

The AI moment

“Why are we still talking about digital transformation?” The speaker was convening a session at last weekend’s UK Govcamp, an event organized by and for civil servants with an interest in digital stuff.

“Because we’ve failed?” someone suggested. These folks are usually *optimists*.

Govcamp is a long-running tradition that began as a guerrilla effort in 2008. At the time, civil servants wanting to harness new technology in the service of government were so thin on the ground they never met until one of them, Jeremy Gould, convened the first Govcamp. These are people who are willing to give up a Saturday in order to do better at their jobs working for us. All hail.

It’s hard to remember now, nearly 15 years on, the excitement in 2010 when David Cameron’s incoming government created the Government Digital Service and embedded it into the Cabinet Office. William Heath immediately ended the Ideal Government blog he’d begun writing in 2004 to press insistently for better use of digital technologies in government. The government had now hired all the people he could have wanted it to, he said, and therefore, “its job is done”.

Some good things followed: tilting government procurement to open the way for smaller British companies, consolidating government publishing, other things less visible but still important. Some data became open. This all has improved processes like applying for concessionary travel passes and other government documents, and made government publishing vastly more usable. The improvement isn’t universal: my application last year to renew my UK driver’s license was sent back because my signature strayed outside the box provided for it.

That’s just one way the business of government doesn’t feel that different. The whole process of developing legislation – green and white papers, public consultations, debates, and amendments – marches on much as it ever has, though with somewhat wider access because the documents are online. Thoughts about how to make it more participatory were the subject of a teacamp in 2013. Eleven years on, civil society is still reading and responding to government consultations in the time-honored way, and policy is still made by the few for the many.

At Govcamp, the conversation spread between the realities of their working lives and the difficulties systems posed for users – that is, the rest of us. “We haven’t removed those little frictions,” one said, evoking the old speed comparisons between Amazon (delivers tomorrow or even today) and the UK government (delivers in weeks, if not months).

“People know what good looks like,” someone else said, in echoing that frustration. That’s 2010-style optimism, from when Amazon product search yielded useful results, search engines weren’t spattered with AI slime and blanketed with ads, today’s algorithms were not yet born, and customer service still had a heartbeat. Here in 2025, we’re all coming up against rampant enshittification, with the result that the next cohort of incoming young civil servants *won’t* know any more what “good” looks like. There will be a whole new layer of necessary education.

Other comments: it’s evolution, not transformation; resistance to change and the requirement to ask permission are embedded throughout the culture; usability is still a problem; trying to change top-down only works in a large organization if it sets up an internal start-up and allows it to cannibalize the existing business; not enough technologists in most departments; the public sector doesn’t have the private sector option of deciding what to ignore; every new government has a new set of priorities. And: the public sector has no competition to push change.

One suggestion was that technological change happens in bursts – punctuated equilibrium. That sort of fits with the history of changing technological trends: computing, the Internet, the web, smartphones, the cloud. Today, that’s “AI”, which prime minister Keir Starmer announced this week he will mainline into the UK’s veins “for everything from spotting potholes to freeing up teachers to teach”.

The person who suggested “punctuated equilibrium” added: “Now is a new moment of change because of AI. It’s a new ‘GDS moment’.” This is plausible in the sense that new paradigms sometimes do bring profound change. Smartphones changed life for homeless people. On the other hand, many don’t do much. Think audio: that was going to be a game-changer, and yet after years of loss-making audio assistants, most of us are still typing.

So is AI one of those opportunities? Many brought up generative AI’s vast consumption of energy and water and rampant inaccuracy. Starmer, like Rishi Sunak before him, seems to think AI can make Britain the envy of other major governments.

Complex systems – such as digital governance – don’t easily change the flow of information or, therefore, the flow of power. It can take longer than most civil servants’ careers. Organizations like Mydex, which seeks to up-end today’s systems to put users in control, have been at work for years now. The upcoming digital identity framework has Mydex chair Alan Mitchell optimistic that the government’s digital identity framework is a breakthrough. We’ll see.

One attendee captured this: “It doesn’t feel like the question has changed from more efficient bureaucracy to things that change lives.” Said another in response, “The technology is the easy bit.”

Illustrations: Sir Humphrey Appleby (Nigel Hawthorne), Bernard Woolley (Derek Fowldes), and Jim Hacker (Paul Eddington) arguing over cultural change in Yes, Minister.

The lost Internet

As we open 2025 it would be traditional for an Old Internet Curmudgeon to rhapsodize about the good, old days of the 1990s, when the web was open, snark flourished at sites like suck.com, no one owned social media (that is, Usenet and Internet Relay Chat), and even the spam was relatively harmless.

But that’s not the period I miss right now. By “lost” I mean the late 2000s, when we shifted from an Internet of largely unreliable opinions to an Internet full of fact-based sites you could trust. This was the period during which Wikipedia (created 2001) grew up, and Open Street Map (founded 2004) was born, joining earlier sites like the Internet Archive (founded 1996) and Snopes (1994). In that time, Google produced useful results, blogs flourished, and before it killed them if you asked on Twitter for advice on where to find a post box near a point in Liverpool you’d get correct answers straight to your mobile phone.

Today, so far: I can’t get a weather app to stop showing the location I was at last week and show the location I’m at this week. Basically, the app is punishing me for not turning on location tracking. The TV remote at my friend’s house doesn’t fully work and she doesn’t know why or how to fix it; she works around it with a second remote whose failings are complementary. No calendar app works as well as the software I had 1995-2001 (it synced! without using a cloud server and third-party account!). At the supermarket, the computer checkout system locked up. It all adds up to a constant white noise of frustration.

We still have Wikipedia, Open Street Map, Snopes, and the Internet Archive. But this morning a Mastodon user posted that their ten-year-old says you can’t trust Google any more: “It just returns ‘a bunch of madeup stuff’.” When ten-year-olds know your knowledge product sucks…

If generative AI were a psychic we’d call what it does cold reading.

At his blog, Ed Zitron has published a magnificent, if lengthy, rant on the state ot technology. “The rot economy”, he calls it, and says we’re all victims of constant low-level trauma. Most of his complaints will be familiar: the technologies we use are constantly shifting and mostly for the worse. My favorite line: “We’re not expected to work out ‘the new way to use a toilet’ every few months because somebody decided we were finishing too quickly.”

Pause to remember nostalgically 2018, when a friend observed that technology wasn’t exciting any more and 2019, when many more people thought the Internet was no longer “fun”. Those were happy days. Now we are being overwhelmed with stuff we actively don’t want in our lives. Even hacked Christmas lights sound miserable for the neighbors.

***

I have spent some of these holidays editing a critique of Ofcom’s regulatory plans under the Online Safety Act (we all have our own ideas about holidays), and one thing seems clear: the splintering Internet is only going to get worse.

Yesterday, firing up Chrome because something didn’t work in Firefox, I saw a fleeting popup to the effect that because I may not be over 18 there are search results Google won’t show me. I don’t think age verification is in force in the Commonwealth of Pennsylvania – US states keep passing bills, but hit legal challenges.

Age verification has been “imminent” in the UK for so long – it was originally included in the Digital Economy Act 2017 – that it seems hard to believe it may actually become a reality. But: sites within the Act’s scope will have to complete an “illegal content risk assessment” by March 16. So the fleeting popup felt like a visitation from the Ghost of Christmas Future.

One reason age verification was dropped back then – aside from the distractions of Brexit – was that the mechanisms for implementing it were all badly flawed – privacy-invasive, ineffective, or both. I’m not sure they’ve improved much. In 2022, France’s data protection watchdog checked them out: “CNIL finds that such current systems are circumventable and intrusive, and calls for the implementation of more privacy-friendly models.”

I doubt Ofcom can square this circle, but the costs of trying will include security, privacy, freedom of expression, and constant technological friction. Bah, humbug.

***

Still, one thing is promising: the rise of small, independent media outlets wbo are doing high-quality work. Joining established efforts like nine-year-old The Ferret, ten-year-old Bristol Cable, and five-year-old Rest of World are year-and-a-half-old 404 Media and newcomer London Centric. 404Media, formed by four journalists formerly at Vice’s Motherboard, has been consistently making a splash since its founding; this week Jason Koebler reminds that Elon Musk’s proactive willingness to unlock the blown-up cybertruck in Las Vegas and provide comprehensive data on where it’s been, including video from charging stations, without warrant or court order, could apply to any Tesla customer at any time. Meanwhile, in its first three months London Centric’s founding journalist, Jim Waterson, has published pieces on the ongoing internal mess at Transport for London resulting from the August cyberattack and bicycle theft in the capital. Finally, if you’re looking for high-quality American political news, veteran journalist Dan Gillmore curates it for you every day in his Cornerstone of Democracy newsletter.

The corporate business model of journalism is inarguably in trouble, but journalism continues.

Happy new year.

Illustrations: The Marx Brothers in their 1929 film, The Cocoanuts, newly released into the public domain.

Playing monopoly

If you were going to carve up today’s technology giants to create a more competitive landscape, how would you do it? This time the game’s for real. In August, US District Judge Amit Mehta ruled that, “Google is a monopolist and has acted as one to maintain its monopoly.” A few weeks ago, the Department of Justice filed preliminary proposals (PDF) for remedies. These may change before the parties reassemble in court next April.

Antitrust law traditionally aimed to ensure competition in order to create both a healthy business ecosystem and better serve consumers. “Free” – that is, pay-with-data – online services have been resistant to antitrust analysis through decades of focusing on lowered prices to judge success.

It’s always tempting to think of breaking monopolists up into business units. For example, a key moment in Meta’s march to huge was its purchase of WhatsApp (2014) and Instagram (2012), turning baby competitors into giant subsidiaries. In the EU, that permission was based on a promise, which Meta later broke, not to merge the three companies’ databases. Separating them back out again to create three giant privacy-invading behemoths in place of one is more like the sorceror’s apprentice than a win.

In the late 1990s case against Microsoft, which ended in settlement, many speculated about breaking it up into Baby Bills. The key question: create clones or divide up the Windows and office software?

In 2013, at ComputerWorld Gregg Keizer asked experts to imagine the post-Microsoft-breakup world. Maybe the office software company ported its products onto the iPad. Maybe the clones eventually diverged and one would have dominated search. Keizer’s experts generally agree, though, that the antitrust suit itself had its effects, slowing the company’s forward progress by making it fear provoking further suits, like IBM before it.

In Google’s case, the key turning point was likely the 2007-2008 acquisition of online advertising pioneer DoubleClick. Google was then ten years old and had been a public company for almost four years. At its IPO Wall Street pundits were dismissive, saying it had no customer lock-in and no business model.

Reading Google’s 2008 annual report is an exercise in nostalgia. Amid an explanation of contextual advertising, Google says it has never spent much on marketing because the quality of its products generated word of mouth momentum worldwide. This was all true – then.

At the time, privacy advocates opposed the DoubleClick merger. Both FTC and EU regulators raised concerns, but let it go ahead to become the heart of the advertising business Susan Wojcicki and Sheryl Sandberg built for Google. Despite growing revenues from its cloud services business, most of Google’s revenues still come from advertising.

Since then, Mehta ruled, Google cemented its dominance by paying companies like Apple, Samsung, and Verizon to make its search engine the default on the devices they make and/or sell. Further, Google’s dominance – 90% of search – allows it to charge premium rates for search ads, which in turn enhances its financial advantage. OK, one of those complaining competitors is Microsoft, but others are relative minnows like 15-year-old DuckDuckGo, which competes on privacy, buys TV ads, and hasn’t cracked 1% of the search market. Even Microsoft’s Bing, at number two, has less than 4%. Google can insist that it’s just that good, but complaints that its search results are degrading are everywhere.

Three aspects of the DoJ’s proposals seized the most attention: forcing Google to divest itself of the Chrome browser; second, if that’s not enough, to divest the Android mobile operating system; and third a block on paying other companies to make Google search the default. The latter risks crippling Mozilla and Firefox, and would dent Apple’s revenues, but not really harm Google. Saving $26.3 billion (2021 number) can’t be *all* bad.

At The Verge, Lauren Feiner summarizes the DoJ’s proposals. At the Guardian, Dan Milmo notes that the DoJ also wants Google to be barred from buying or investing in search rivals, query-based AI, or adtech – no more DoubleClicks.

At Google’s blog, chief legal officer Kent Walker calls the proposals “a radical interventionist agenda”. He adds that it would chill Google’s investment in AI like this is a bad thing, when – hello! – a goal is ensuring a competitive market in future technologies. (It could even be a good thing generally.)

Finally, Walker claims divesting Chrome and/or Android would endanger users’ security and privacy and frets that it would expose Americans’ personal search queries to “unknown foreign and domestic companies”. Adapting a line from the 1980 movie Hopscotch, “You mean, Google’s methods of tracking are more humane than the others?” While relaying DuckDuckGo’s senior vice-president’s similar reaction, Ars Technica’s Ashley Belanger dubs the proposals “Google’s nightmare”.

At Techdirt, Mike Masnick favors DuckDuckGo’s idea of forcing Google to provide access to its search results via an API so competitors can build services on top, as his company does with Bing. Masnick wants users to become custodians and exploiters of their own search histories. Finally, at Pluralistic, Cory Doctorow likes spinning out – not selling – Chrome. End adtech surveillance, he writes, don’t democratize it.

It’s too early to know what the DoJ will finally recommend. If nothing is done, however, Google will be too rich to fear future lawsuits.

Illustration: Mickey Mouse as the sorceror’s apprentice in (1940).

Wendy M. Grossman is the 2013 winner of the Enigma Award. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.

Review: Supremacy

Supremacy: AI, ChatGPT, and the Race That Will Change the World
By Parmy Olson
Macmillan Business
ISBN: 978-1035038220

One of the most famous books about the process of writing software is Frederick Brooks’ The Mythical Man Month. The essay that gives the book its title makes the point that you cannot speed up the process by throwing more and more people at it. The more people you have, the more they have to all communicate with each other, and the pathways multiply exponentially. Think of it this way: 500 people can’t read a book faster than five people can.

Brooks’ warning immediately springs to mind when Parmy Olson reports, late in her new book, Supremacy, that Microsoft CEO Sadya Nadella was furious to discover that Microsoft’s 5,000 direct employees working on AI lagged well behind the rapid advances being made by the fewer than 200 working working at OpenAI. Some things just aren’t improved by parallel processing.

The story Olson tells is a sad one: two guys, both eager to develop an artificial general intelligence in order to save, or least help, humanity, who both wind up working for large commercial companies whose primary interests are to 1) make money and 2) outcompete the other guy. For Demis Hassabis, the company was Google, which bought his DeepMind startup in 2014. For Sam Altman, founder of OpenAI, it was Microsoft. Which fits: Hassabis’s approach to “solving AI” was to let them teach themselves by playing games, hoping to drive science discovery; Altman sought to solve real-world problems and bring everyone wealth. Too late for Olson’s book, Hassabis has achieved enough of a piece of his dream to have been one of three awarded the 2024 Nobel Prize in chemistry for using AI to predict how proteins will fold.

For both the reason was the same: the resources they sought to work in AI – data, computing power, and high-priced personnel – are too expensive for either traditional startup venture capital funding or for academia. (Cure Vladen Joler, at this year’s Computers, Privacy, and Data Protection, noting that AI is arriving “pre-monopolized”.) As Olson tells the story, they both tried repeatedly to keep the companies they founded independent. Yet, both have wound up positioned to run the companies whose money they took apparently believing, like many geek founders with more IQ points than sense, that they would not have to give up control.

In comparing and contrasting the two founders, Olson shows where many of today’s problems came from. Allying themselves with Big Tech meant giving up on transparency. The ethicists who are calling out these companies over real and present harms caused by the tools they’ve built, such as bias, discrimination, and exploitation of workers performing tasks like labeling data, have 1% or less of the funding of those pushing safety for superintelligences that may never exist.

Olson does a good job of explaining the technical advances that led to the breakthroughs of recent years, as well as the business and staff realities of their different paths. A key point she pulls out is the extent to which both Google and Microsoft have become the kind of risk-averse, slow-moving, sclerotic company they despised when they were small, nimble newcomers.

Different paths, but ultimately, their story is the same: they fought the money, and the money won.

Blown

“This is a public place. Everyone has the right to be left in peace,” Jane (Vanessa Redgrave) tells Thomas (David Hemmings), whom she’s just spotted photographing her with her lover in the 1966 film Blow-Up, by Michelangelo Antonioni. The movie, set in London, proceeds as a mystery in which Thomas’s only tangible evidence is a grainy, blown-up shot of a blob that may be a murdered body.

Today, Thomas would probably be wielding a latest-model smartphone instead of a single lens reflex film camera. He would not bother to hide behind a tree. And Jane would probably never notice, much less challenge Thomas to explain his clearly-not-illegal, though creepy, behavior. Phones and cameras are everywhere. If you want to meet a lover and be sure no one’s photographing you, you don’t go to a public park, even one as empty as the film finds Maryon Park. Today’s 20-somethings grew up with that reality, and learned early to agree some gatherings are no-photography zones.

Even in the 1960s individuals had cameras, but taking high-quality images at a distance was the province of a small minority of experts; Antonioni’s photographer was a professional with his own darkroom and enlarging equipment. The first CCTV cameras went up in the 1960s; their proliferation became public policy issue in the 1980s, and was propagandized as “for your safety without much thought in the post-9/11 2000s. In the late 2010s, CCTV surveillance became democratized: my neighbor’s Ring camera means no one can leave an anonymous gift on their doorstep – or (without my consent) mine.

I suspect one reason we became largely complacent about ubiquitous cameras is that the images mostly remained unidentifiable, or at least unidentified. Facial recognition – especially the live variant police seem to feel they have the right to set up at will – is changing all that. Which all leads to this week, when Joseph Cox at 404 Media reports ($) (and Ars Technica summarizes) that two Harvard students have mashed up a pair of unremarkable $300 Meta Ray-Bans with the reverse image search service Pimeyes and a large language model to produce I-XRAY, an app that identifies in near-real time most of the people they pass on the street, including their name, home address, and phone number.

The students – AnhPhu Nguyen and Caine Ardayfio – are smart enough to realize the implications, imagining for Cox the scenario of a random male spotting a young woman and following her home. This news is breaking the same week that the San Francisco Standard and others are reporting that two men in San Francisco stood in front of a driverless Waymo taxi to block it from proceeding while demanding that the female passenger inside give them her phone number (we used to give such males the local phone number for time and temperature).

Nguyen and Ardayfio aren’t releasing the code they’ve written, but what two people can do, others with fewer ethics can recreate independently, as 30 years of Black Hat and Def Con have proved. This is a new level of democratizated surveillance. Today, giant databases like Clearview AI are largely only accessible to governments and law enforcement. But the data in them has been scraped from the web, like LLMs’ training data, and merged with commercial sources

This latest prospective threat to privacy has been created by the marriage of three technologies that were developed separately by different actors without regard to one another and, more important, without imagining how one might magnify the privacy risks of the others. A connected car with cameras could also run I-XRAY.

The San Francisco story is a good argument against allowing cars on the roads without steering wheels, pedals, and other controls or *something* to allow a passenger to take charge to protect their own safety. In Manhattan cars waiting at certain traffic lights often used to be approached by people who would wash the windshield and demand payment. Experienced drivers knew to hang back at red lights so they could roll forward past the oncoming would-be washer. How would you do this in a driverless car with no controls?

We’ve long known that people will prank autonomous cars. Coverage focused on the safety of the *cars* and the people and vehicles surrounding them, not the passengers. Calling a remote technical support line for help is never going to get a good enough response.

What ties these two cases together – besides (potentially) providing new ways to harass women – is the collision between new technologies and human nature. Plus, the merger of three decades’ worth of piled-up data and software that can make things happen in the physical world.

Arguably, we should have seen this coming, but the manufacturers of new technology have never been good at predicting what weird things their users will find to do with it. This mattered less when the worst outcome was using spreadsheet software to write letters. Today, that sort of imaginative failure is happening at scale in software that controls physical objects and penetrates the physical world. The risks are vastly greater and far more unsettling. It’s not that we can’t see the forest for the trees; it’s that we can’t see the potential for trees to aggregate into a forest.

Illustrations: Jane (Vanessa Redgrave) and her lover, being photographed by Thomas (David Hemmings) in Michelangelo Antonioni’s 1966 film, Blow-Up.