net.wars

Unscreened

My Canadian friend was tolerant enough to restart his Nissan car so I could snare a pic of the startup screen (above) and read it in full. That’s when he followed the instructions to set the car to send only “limited data” to the company. What is that data? The car didn’t say. (Its manual might, but I didn’t test his patience that far.)

In 2023, a Mozilla Foundation study of US cars’ privacy called them the worst category it had ever tested and named Nissan as the worst offender: “The Japanese car manufacturer admits in their privacy policy to collecting a wide range of information, including sexual activity, health diagnosis data, and genetic data – but doesn’t specify how. They say they can share and sell consumers’ ‘preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes’ to data brokers, law enforcement, and other third parties.”

Fortunately, my friend lives in Canada.

Granting that no one wants to read privacy policies, at least apps, and websites display them in their excruciating, fine-print detail. They can afford to because usually you encounter them when you’re not in a hurry. That can’t be said of the start-up screen in a car, when you just want to get moving. Its interference has to be short.

The new startup screen confirmed that “limited data” was now being sent. I wasn’t quick enough to read the rest, but it probably warned that some features might not now work – because that’s what they *always* say, and is what the settings warned (without specifics) when he changed them.

I assume this setup complies with Canada’s privacy laws. But the friction of consulting a manual or website to find out what data is being sent deters customers from exercising their rights. Like website dark patterns, it’s gamed to serve the company’s interests. It feels like grudging compliance with the law, especially because customers are automatically opted in.

How companies obtain consent is a developing problem. At Privacy International, Gus Hosein considers the future of AI assistants. Naturally, he focuses on the privacy implications: the access they’ll need, the data they’ll be able to extract, the new kinds of datasets they’ll create. And he predicts that automation will tempt developers to bypass the friction of consent and permission. In 2013, we considered this with respect to emotionally manipulative pet robots.

I had to pause when Hosein got to “screenless devices” to follow some links. At Digital Trends, Luke Edwards summarizes a report at The Information that OpenAI may acquire io Products. This start-up, led by renowned Apple hardware designer Jony Ive and OpenAI CEO Sam Altman, intends to create AI voice-enabled assistants that may (or may not) take the form of a screenless “phone” or household device.

Meanwhile, The Vergecast (MP3) reports that Samsung is releasing Ballie, a domestic robot infused with Google Cloud’s generative AI that can “engage in natural, conversational interactions to help users manage home environments”. Samsung suggests you can have it greet people at the door. So much nicer than being greeted by your host.

These remind of the Humane AI pin, whose ten-month product life ended in February with HP’s purchase of the company’s assets for $116 million. Or the similar Bee, whose “summaries” of meetings and conversations Victoria Song at The Verge called “fan fiction”. Yes: as factual as any other generative AI chatbot. More notably, the Bee couldn’t record silent but meaningful events, leading Song to wonder, “In a hypothetical future where everyone has a Bee, do unspoken memories simply not exist?”

In November 2018, a Reuters Institute report on the future of news found that on a desktop computer the web can offer 20 news links at a time; a smartphone has room for seven, and smart speakers just one. Four years later, smart speakers were struggling as a category because manufacturers can’t make money out of them. But apparently Silicon Valley still thinks the shrunken communications channel of voice beats typing and reading and are plowing on. It gives them greater control.

The thin, linear stream of information is why Hosein foresees the temptation to avoid the friction of consent. But the fine-grained user control he wants will, I think, mandate offloading reviewing collected data and granting or revoking permissions onto a device with a screen. Like smart watches, these screenless devices will have to be part of a system. What Hosein wants and Cory Doctorow has advocated for web browsers is that these technological objects should be loyal agents. That is, they must favor *our* interests over those of their manufacturer, or we won’t trust them.

More complicated is the situation with respect to incops – incidentally co-present [people] – whose data is also captured without their consent: me in my friend’s car, everyone Song encountered. Mozilla reported that Subaru claims that by getting in the car passengers become “users” who consent to data collection (as if); several other manufacturers say that the driver is responsible for notifying passengers. Song found it easier to mute the Bee in her office and while commuting than to ask colleagues and passersby for permission to record. Then she found it didn’t always disconnect when she told it to…

So now imagine that car saturated with an agentic AI assistant that decides where you want to go and drives you there.

“You don’t want to do that, Dave.”

Illustrations: The start-up screen in my Canadian friend’s car.

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.

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 with a Canadian Coast Guard boat in the foreground.

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.