Gleeful white hyphic cables are shrivelled and fixated from moon silver to darkness through over-demanded extensions of bandwidth issued by the users who in turn describe this fixation and hardening which takes place over time as a set of symptoms.
Someone leaked internal Apple email exchanges about Right to Repair to Ifixit; they reveal “internal debate, rife with uncertainty” - employees who have deep misgivings about dooming their work-product to become e-waste.
Of particular interest is the internal debate after Apple (surprisingly) published two excellent service manuals, which an Ifixit writer queried them on, asking if it was intentional.
An Apple spox wrote to the internal PR team: “Iit’s pretty clear things are happening in a vacuum and there is not an overall strategy…
“Plus, with one hand we are making these changes and the other is actively fighting Right to Repair legislation moving in 20 states without real coordination for how updated policies could be used to leverage our position.”
It looks like the service manual release was motivated by a desire to attain EPEAT green certification. As Ifixit points out, “these manuals have been online for a year. Has any harm come from it? Have lawsuits sprung out of the woodwork? We certainly haven’t heard of any.”
Apple is publishing “environmental progress reports” that stress the company’s commitment to repair and say “reuse is our first choice” - entirely new messages from the company.
As Ifixit points out: “Apple has an opportunity to push—nay, lead—the entire industry in a better direction. Durable, repairable, long-lasting products could be the norm.”
Intelligence Community Releases Artificial Intelligence Principles and Framework
Narrowing the gap between data collection and decision making is a top priority for the Intelligence Community, but the pace at which data is generated is increasing exponentially—and the IC workforce available to analyze the data is not. Artificial intelligence provides powerful tools to execute this mission, but also brings new challenges.That makes it even more important that the IC to implement AI in a manner that is both ethical and consistent with our values.
Which is to say that AI is about much more than technology. The IC must ensure that technological changes do not change our commitment to protecting privacy and civil liberties in the course of our work.That’s why our data scientists, privacy and civil liberties officers and other key stakeholders worked together to develop the Principles of AI Ethics for the Intelligence Community as well as a framework to ensure that these principles are incorporated into our design and use of this technology.
This framework is a living document, and we’re eager for your feedback on how we can continue to expand and refine it to keep pace with this rapidly evolving technology.
In a major new paper, just released as a preprint, the eminent UK computer scientist and digital rights campaigner Ian Brown makes the case for “Interoperability as a tool for competition regulation.”
The paper pulls together many of the recent interventions on the subject into a single, readable, brief summary that makes for an excellent overview - I’m not saying you shouldn’t read the CMA’s magesterial 450 page report, but realistically…
Brown starts by describing interop - an often slippery topic - in concrete terms, giving familiar examples from existing tech (eg SMS) and then describing how interop could open Big Tech’s silos up.
He summarizes leading economists’ views on the effects of interop on competition, presenting both pro- and con- arguments (the pro arguments are MUCH better, but then reality has a well-known leftist bias).
He then presents a taxonomy of types of platforms:
Gatekeepers: “control access between businesses and potential customers”
Conglomerates: “companies with a broad range of sometimes weakly-related businesses”
Ecosystems: “collections of services connected via privileged channels not fully available to competitors”
This is a jumping-off point for concepts from competition scholarship: “complementary innovation,” “homogenization,” “static vs dynamic effects” - the ways that companies interpenetrate each others’ products/services for good and ill.
Having covered the economic dimension, Brown turns to the social consequences of interop: as covid showed us, platform dominance has a profound effect on our social lives, with choices made by tech giants redounding to every facet of our digitally mediated, locked down lives.
Competition economists since Thatcher and Reagan have largely dismissed these consequences, focusing solely on short-term price increases as the only reliable barometer of whether monopolistic conduct is good or bad.
But tech concentration has profound impacts on our civil society - the BBC can’t get Amazon or Google to put its coronavirus coverage on their smart speakers, so “tech companies with their executives in the US have a monopoly in British people’s kitchens and living rooms.”
Other media orgs also complain that tech acts as a rent-seeker and gate-keeper, holding their audiences hostage (though those who succeed rarely complain on behalf of smaller, new entrants who can’t afford to pay tech’s tolls and thus do not compete with Big Content).
Next is privacy and data protection, citing some of the work I’ve done with my EFF colleague Bennett Cyphers:
This is a severely undertheorized area, and there are severe potential pitfalls if we get it wrong. One thing we know, though, is that the status quo is NOT good for privacy, and lack of competition doesn’t incentivize tech monopolists to do better.
Next, Brown turns to content moderation, an area of growing concern that regulators have primarily addressed by creating impossibly expensive mandates to prevent harmful speech, at costs that preclude new market entrants, strengthening Big Tech’s dominance.
Brown cites federated platforms like Mastodon, which allow for partial interconnetion between autonomously maintained servers, where communities can make their own policies and block/filter those with policies they disagree with.
These offer the possibility of having fine-grained locally responsive rules - enforced by the community itself, not by traumatized subcontractors in the Philippines tasked with moderating all of Facebook’s 2.6B users’ contributions.
Brown takes on “digital sovereignty” and the uneasy fact that most of the west’s online media is controlled by a handful of US-based companies with “GDP"s larger than most countries’.
Interop lets domestic competitors arise that can benefit from these US giants’ users, while returning control to local firms and regulators.
Brown ends with an appendix that enumerates types of interop and scenarios for how they could be applied to existing Big Tech firms’ services, bringing the whole thing into focus with concrete examples and proposals.
As the US Congress showed us yesterday, we’re at a turning point with our relationship to Big Tech. Smaller tech companies are experiencing a mass die-off thanks to covid, and Big Tech has huge war-chests it can use to snap them up.
When these US giants buy all their nascent competitors, they will present themselves as rescuers, saviors of businesses drowning in debt. But unless we intervene, they will emerge from the crisis with levels of dominance we can hardly dream of.
“True literacy in systems consists of much more than simple understanding, and might be understood and practised in multiple ways. It goes beyond a system’s functional use to comprehend its context and consequences. It refuses to see the application of any one system as a cure-all, insisting upon the interrelationships of systems and the inherent limitations of any single solution. It is fluent not only in the language of a system, but in its metalanguage — the language it uses to talk about itself and to interact with other systems — and is sensitive to the limitations and the potential uses and abuses of that metalanguage. It is, crucially, capable of both performing and responding to critique.”
— James Bridle, New Dark Age: Technology and the End of the Future
The underlying reason people dismiss climate science, it turns out, has more to do with political identity than logic. In fact, the more intelligent people are, the more polarized they tend to be on climate change. When they’re challenged, Democrats and Republicans alike simply use their smarts to justify their beliefs. Confirmation bias is a powerful thing.
It’s not just that Democrats and Republicans in Congress have different priorities when it comes to the climate crisis — they also use different styles of persuasion. A study published in the journal Environmental Politics earlier this month breaks down the differences along partisan lines. With the help of machine learning, Guber and her colleagues analyzed millions upon millions of words from Congressional floor speeches from 1996 until 2015.
They found that Democrats tend to make arguments about climate change backed up by facts and evidence, while Republicans tend to tell stories, using imagery, emotional appeals, and humor to sway people to their side. According to Guber, Republicans are “communicating in ways that may ultimately be more effective.”
Some research suggests that liberals and conservatives react differently when confronted with new evidence that contradicts their beliefs. A working paper by four Canadian psychologists argues that many liberals are more willing to change their minds (associated with the value liberals tend to place on science and skepticism), while conservatives are more likely to stick to their guns (linked with a respect for tradition and religious beliefs).
Democrats have long been criticized for overlooking emotional appeals, Guber said, but they seem to be moving in a direction that would appeal to a broader swath of the public, framing the climate crisis as a threat to public health and national security, invoking religious stewardship, and explaining that taking on climate change creates jobs.
“The hope is if Democrats can find a way of being emotionally engaging on climate change while avoiding some of the triggers that speak to partisanship, then they’ll do well,” Guber said.
…in these difficult times, these trying, confounding, demanding times, extraordinary, excessive, these dangerous, overwhelming, vertiginous, abject, transcendent, these, immanent, epochal, catastrophic, times, these difficult, in these trying times.
Designed to last more than 200 years, the Oosterscheldekering (Eastern Scheldt storm surge barrier) is the largest in a series of 13 dams designed to protect the Netherlands from North Sea flooding. It spans about 9 km between the islands of Schouwen-Duiveland and Noord-Beveland, containing large sluicegate-type doors that can be closed under adverse weather conditions.
“I no longer claim to know anything
But I still have persistent suspicions.
My greatest suspicion holds that
All my suspicions may prove wrong.
Intelligence recognizes
That nothing now seems impossible.
Have a good hearty laugh
And do not dare to mourn me.”
“Scientists come in two varieties, hedgehogs and foxes. I borrow this terminology from Isaiah Berlin (1953), who borrowed it from the ancient Greek poet Archilochus. Archilochus told us that foxes know many tricks, hedgehogs only one. Foxes are broad, hedgehogs are deep. Foxes are interested in everything and move easily from one problem to another. Hedgehogs are only interested in a few problems that they consider fundamental, and stick with the same problems for years or decades. Most of the great discoveries are made by hedgehogs, most of the little discoveries by foxes. Science needs both hedgehogs and foxes for its healthy growth, hedgehogs to dig deep into the nature of things, foxes to explore the complicated details of our marvelous universe. Albert Einstein and Edwin Hubble were hedgehogs. Charley Townes, who invented the laser, and Enrico Fermi, who built the first nuclear reactor in Chicago, were foxes. It often happens that foxes are as creative as hedgehogs. The laser was a big discovery made by a fox. The general public is misled by the media into believing that great scientists are all hedgehogs. Some periods in the history of science are good times for hedgehogs, other periods are good times for foxes. The beginning of the twentieth century was good for hedgehogs. The hedgehogs—Einstein and his followers in Europe, Hubble and his followers in America—dug deep and found new foundations for physics and astronomy. When Fermi and Townes came onto the scene in the middle of the century, the foundations were firm and the universe was wide open for foxes to explore. Most of the progress in physics and astronomy since the 1920s was made by foxes.”
— Freeman J. Dyson, A Many-Colored Glass: Reflections on the Place of Life in the Universe
I’m working on a systems project rn and when I want to freak out the people I’m sprinting with I show them my 666 tattoo and gets them pretty upset. pic.twitter.com/EFJqrgKXRw
“The deployment of unidentified federal officers is particularly dangerous in a situation like that in Portland and elsewhere in America, because it could easily lead to right-wing militias’ impersonating legal authorities and kidnapping citizens. As former CIA counterintelligence analyst Aki Peritz notes, “All it takes is one of these similar-kitted out militiamen groups to start grabbing folks off the street as well, but then having their way with them, for there to be huge, possibly violent pushback for these tactics. This hurts the police, and the citizenry.” Peritz argues, “We’re quickly entering secret police territory now. DHS is becoming Trump’s Mukhābarāt” (mukhābarāt being the Arabic word for intelligence agency, used colloquially to refer, for example, to the Egyptian or Iraqi or Libyan secret police).”
100 gecs is kero kero bonito for girls who’s aphex twin is sophie they’re basically the hatsune miku of the girls who post chloë sevigny the same way ecco2k is the yves tumor for girls who’s arca is ayesha erotica it’s not very hard to understand tbh
““Every particle in the universe,” continued Dirk, warming to his subject and beginning to stare a bit, “affects every other particle, however faintly or obliquely. Everything interconnects with everything. The beating of a butterfly’s wings in China can affect the course of an Atlantic hurricane. If I could interrogate this table leg in a way that made sense to me, or to the table leg, then it could provide me with the answer to any question about the universe. I could ask anybody I liked, chosen entirely by chance, any random question I cared to think of, and their answer, or lack of it, would in some way bear upon the problem to which I am seeking a solution. It is only a question of knowing how to interpret it. Even you, whom I have met entirely by chance, probably know things that are vital to my investigation, if only I knew what to ask you, which I don’t, and if only I could be bothered to, which I can’t.””
— Douglas Adams, The Long Dark Tea-Time of the Soul
I drew the above diagram in my notebook last November, a double allusion. The first is the epigram, “Work as if you live in the early days of a better nation,” which is generally attributed to the Scottish writer and artist, Alasdair Gray. On digging a little deeper into its provenance, I was startled to learn that the line is borrowed from a poet—and not just any poet, but the much-beloved poet laureate of my Canadian childhood, Dennis Lee, author of Alligator Pie and Garbage Delight. The quotation is from Lee’s poem “Civil Elegies”, and the second pleasant surprise was the wording in the original, which I much prefer [the emphasis here is mine]: “…the early days of a better civilization.”
The second allusion is to William Gibson’s concept of ’the jackpot’, introduced in his 2014 novel The Peripheral and which continues as the backdrop in his 2020 novel, Agency. It’s a multi-causal, distributed, decentralized apocalypse, comprising climate change, pollution, the emergence of drug-resistance diseases and, of course, pandemics. It’s not clear we’re in its early days—in Gibson’s conception, we are a century into a multi-century event. It’s just that it’s taken us this long to realize it.
So. Greetings from the jackpot, and the early days of a better civilization.
What 2020 has taught us is that a realistic zombie movie would show most people carrying on as normal, ignoring the shamblers in their offices and homes, while a large minority accuse the zombies of being crisis actors and a leftwing conspiracy to polute their bodily fluids.
So many questions! Great (re)generative discussions were had. Thanks again to all the participants for your inputs. Looking forward to further developing this format and these ideas, and seeing what gets made of all this by the researchers involved from @CreaturesEuhttps://t.co/fZuiJgC2FU
I have a essay in the current issue of #Reliquiae - Journal of Landscape, Nature & Mythology published by the wonderful @Corbel_Stone | ‘Scholar’s Rocks - The Inter-Animating Spirit of Mind & Matter’ - a lithic meditation into miniaturism, apohenia, hylozoism & geoaesthetics pic.twitter.com/QVElcE4s66
2019 set a record for the amount of e-waste ever generated worldwide: 53.6 million metric tons of discarded phones, computers, appliances, and other gadgets. That’s more than the combined weight of all the adults in Europe.
There’s a story I tell in my book because it’s a great illustration of how AI gets the wrong idea about what problem we’re asking it to solve:
Researchers at the University of Tuebingen trained a neural net to recognize images, and then had it point out which parts of the images were the most important for its decision. When they asked it to highlight the most important pixels for the category “tench” (a kind of fish), this is what it highlighted:
Human fingers against a green background!
Why was it looking for human fingers when it was supposed to be looking for a fish? It turns out that most of the tench pictures the neural net had seen were of people holding the fish as a trophy. It doesn’t have any context for what a tench actually is, so it assumes the fingers are part of the fish.
The image-generating neural net in ArtBreeder (called BigGAN) was also trained on the same dataset, called ImageNet, and when you ask it to generate tenches, this is what it does:
The humans are much more distinct than the fish, and I’m fascinated by the highly exaggerated human fingers.
There are other categories in ImageNet that have similar problems. Here’s “microphone”.
It’s figured out about dramatic stage lighting and human forms, but many of its images don’t contain anything that remotely resembles a microphone. In so many of its training pictures the microphone is a tiny part of the image, easy to overlook. There are similar problems with small instruments like “flute” and “oboe”.
In other cases, there might be evidence of pictures being mislabeled. In these generated images of “football helmet”, some of them are clearly of people NOT wearing helmets, and a few even look suspiciously like baseball helmets.
ImageNet is a really messy dataset. It has a category for agama, but none for giraffe. Rather than horse as a category, it has sorrel (a specific color of horse). “Bicycle built for two” is a category, but not skateboard.
A huge reason for ImageNet’s messiness is that it was automatically scraped from images on the internet. The images were supposed to have been filtered by the crowdsourced workers who labeled them, but plenty of weirdness slipped through. And horribleness - many images and labels that definitely shouldn’t have appeared in a general-purpose research dataset, and images that looked like they had gotten there without the consent of the people pictured. After several years of widespread use by the AI community, the ImageNet team has reportedly been removing some of that content. Other problematic datasets - like those scraped from online images without permission, or from surveillance footage - have been removed recently. (Others, like Clearview AI’s, are still in use.)
This week Vinay Prabhu and Abeba Birhane pointed out major problems with another dataset, 80 Million Tiny Images, which scraped images and automatically assigned tags to them with the help of another neural net trained on internet text. The internet text, you may be shocked to hear, had some pretty offensive stuff in it. MIT CSAIL removed that dataset permanently rather than manually filter all 80 million images.
This is not just a problem with bad data, but with a system where major research groups can release datasets with such huge issues with offensive language and lack of consent. As tech ethicist Shannon Vallor put it, ”For any institution that does machine learning today, ‘we didn’t know’ isn’t an excuse, it’s a confession”. Like the algorithm that upscaled Obama into a white man, ImageNet is the product of a machine learning community where there’s a huge lack of diversity. (Did you notice that most of the generated humans in this blog post are white? If you didn’t notice, that might be because so much of Western culture treats white as default).
It takes a lot of work to create a better dataset - and to be more aware of which datasets should never be created. But it’s work worth doing.
Bonus material this week: a few of my favorite BigGAN image categories. Enter your email here for a gallery!
“I must program as inefficiently as possible. I must program as inefficiently as possible.” Today I’m chanting Joe Armstrong’s famous mantra for writing code to solve a problem that you don’t understand yet. The instinct to optimize is extremely counter-productive at these times.
“The word‘good’ has many meanings. For example, if a man were to shoot his grandmother at a range of five hundred yards, I should call him a good shot, but not necessarily a good man.”
From September on I’ll be starting a residency over @LYL_Radio Did my first show last thursday, so here’s a taster.. full tracklisting on the page.. perfect way to start off the week, enjoy!
“The single quantity ‘time’ melts into a spiderweb of times. We do not describe how the world evolves in time: we describe how things evolve in local time, and how local times evolve relative to each other. The world is not like a platoon advancing at the pace of a single commander. It’s a network of events affecting each other.”
I was looking at a complex schedule with multiple time zones and suddenly remembered Swatch Internet Time. And, what do you know, it’s still around… https://t.co/kFXUeBIrIb
At Walkaway’s climax, prisoners who’ve taken over their prison face off against an army of militarized police who lay siege to the occupied prison complex.
Just as the prisoners’ defenses are about to fail, their network of supporters watching from a livestream all over the world leap into the fray, doxing the cops on the line and waking their relatives and talking them into broadcasting pleas on the prison’s PA system.
As the cops hear their loved ones’ pleas, their morale breaks. One at a time, then in bunches, they set down their weapons, shuck body armor, and walk away down the highway. As they trickle away, their commanders are enraged, then terrified, sensing the turn. They retreat.
Yesterday, visual journalist Tyler LaRiviere posted a stunning series of images and clips from a protest in Chicago where protesters faced a standoff with the CPD at a barricade near Mayor Lori Lightfoot’s home.
“To clarify these aren’t random officers they are getting information on but the officers blocking off the intersection on Kimball and Wrightwood. Two of the officers who had their infomation publicized left the line and walked away.”
The final update from Al Baydha Project Co-founder Neal Spackman, 9 years in. How desertification resulted from the loss of an indigenous land management system, and how the land has changed since all inputs to the project were ceased in 2016. Neal moved on from Al Baydha in 2018 and can now be contacted at regenerativeresources.co
Al Baydah is a project we’ve been following for a long time here it Solarpunks. This final update from one of the projects co-founders is equally as incredible as it is inspirational.
Solarpunk does not rely on huge technological leaps into the future, nor does it take wistful glances at the past. Instead it looks laterally at what’s already in the world and projects it forward. Projects like Al Baydha and others provide a rich soil of ideas and action from which our struggles to an on-route to a better world can grow.
I’ve attend a few online lectures and courses hosted by Al Baydah’s cofounder. The results of this project are just … incredible.
“A footprint is something we should want to leave on the earth” - Ben Falk
We’ve been working on an intense critical sensemaking activity, charting threads of nested trends and signals across technology, civic infrastructure and governance to explore multiple futures. Hope to share the findings + report soon. pic.twitter.com/qwClLbj7A9
