Tootfinder

'The digital commons should not be treated as an object ripe for extraction, but as an expression of “commoning” [Dulong de Rosnay and Stalder 2020]; i.e., as a manifestation of the practice of making, maintaining, and protecting shared and open resources.'
From 'Generative AI and the Future of the Digital Commons' https://www.…

Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps
The rapid advancement of Generative AI (GenAI) relies heavily on the digital commons, a vast collection of free and open online content that is created, shared, and maintained by communities. However, this relationship is becoming increasingly strained due to financial burdens, decreased contributions, and misalignment between AI models and community norms. As we move deeper into the GenAI era, it is essential to examine the interdependent relationship between GenAI, the long-term sustainabilit…

Unser Schwesterkonsortium #NFDI4Objects hat frisch das #WhitePaper „Dokumentationsstandards und der Besitznachweis in Sammlungen – ein vergleichender Überblick“ veröffentlicht und zur Kommentierung freigegeben.
#NFDI4Culture

https://www.cbc.ca/news/politics/house-of-commons-data-breach-1.7608061
House of Commons hit by cyberattack from 'threat actor': internal email

House of Commons hit by cyberattack from 'threat actor': internal email | CBC News
The House of Commons and Canada’s cybersecurity agency are investigating a significant data breach caused by an unknown “threat actor” targeting employee information.

Not good
MPs back assisted dying bill in historic Commons vote - BBC News
https://www.bbc.co.uk/news/articles/cgeqj1egxvyo

MPs back assisted dying bill by majority of 23
The bill would allow terminally ill adults in England and Wales to end their own lives.

The best time to plant a tree was 20 years ago. The worst time was 10 years ago

Starmer's Labour outdid the fucking Tories for supplying war criminals.
#IsraelIsATerroristState #BoycottIsrael #IsraeliWarCrimes

Well, that sucks.
Oh well, he still has to face a leadership convention. His chances are better having won the by-election, but there's still a chance he loses.
https://mastodon.hongkongers.net/@glcalgary_mirror/115064682942073821

Global News Calgary (@glcalgary_mirror@mastodon.hongkongers.net)
Attached: 1 image Poilievre wins Alberta byelection, securing return to House of Commons Battle River—Crowfoot was left vacant when Conservative Damien Kurek stepped down to make way for his party's leader, Pierre Poilievre, to run for a seat. #politics #election #Alberta #BattleRiverCrowfoot #Canada #canadaelection https://globalnews.ca/news/11339007/battle-river-crowfood-byelection-voting-day-pierre-poilievre/

Wo #Berlin-#Gesundbrunnen dieser Tage etwas schlechte Presse hat, hier eine nette regionalhistorische Trouvaille: Es gab offenbar an der Ecke Prinzenallee/Soldiner Straße selbst nach dem Krieg noch einen Rummel.

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Edit: fixed some typos.
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and thus more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of management caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

I see my MP (Danny Chambers - LD) voted in favour of the assisted dying bill:
https://votes.parliament.uk/votes/commons/division/2071
It's a difficult decision with good points on both sides but I'm glad he voted for it.

Heute vor 41 Jahren: Am 20. Juni 1984 zündeten die USA im Rahmen von #Fusileer die #Atombombe "Duoro". Fusileer war eine Serie von Tests zwischen 83/84 bei der insgesamt 17 unterirdische #Kernwaffentests

Campaigners vow to keep up fight against Assisted Dying Bill as it clears House of Commons.
‘People will lose their lives who do not need to’ | Morning Star
https://morningstaronline.co.uk/article/people-will-lose-their-lives-who-do-not-nee…

Another great photo!
Members of the Spanish anarcho-syndicalist trade union #CNT marching in Madrid in 2010.
Source: https://commons.wikimedia.org/wiki/Fil…

An excellent read on how Google is killing the Open Web through attacks on XML and other technical standards.
https://wok.oblomov.eu/tecnologia/google-killing-open-web/

Kein Verbot vorgesehen: Creative Commons arbeitet an Lizenzen fürs KI-Training
Creative Commons will dafür sorgen, dass Verantwortliche für Datensätze signalisieren können, was sie dafür erwarten, wenn damit ein KI-Modell trainiert wird.

Kennt ihr diese Skulptur?

Hackers reportedly compromise Canadian House of Commons through Microsoft vulnerability https://therecord.media/hackers-compromise-canada-house-of-commons

Pro-Hamas Protester Vandalizes State House, MIT and Now They Mention the IEDs on Boston Commons (Beege Welborn/HotAir)
https://hotair.com/tree-hugging-sister/2025/08/12/pro-hamas-protester-vandalizes-state-house-mit-and-now-they-mention-the-ieds-on-boston-commons-n3805754
http://www.memeorandum.com/250812/p135#a250812p135

Managing, Analyzing and Sharing Research Data with Gen3 Data Commons
Craig Barnes, Kyle Burton, Michael S. Fitzsimons, Hara Prasad Juvvala, Brienna Larrick, Christopher Meyer, Pauline Ribeyre, Ao Liu, Clint Malson, Noah Metoki-Shlubsky, Andrii Prokhorenkov, Jawad Qureshi, Radhika Reddy, L. Philip Schumm, Mingfei Shao, Trevar Simmons, Alexander VanTol, Peter Vassilatos, Aarti Venkat, Robert L. Grossman

Managing, Analyzing and Sharing Research Data with Gen3 Data Commons
Gen3 is an open-source data platform for building data commons. A data commons is a cloud-based data platform for managing, analyzing, and sharing data with a research community. Gen3 has been used to build over a dozen data commons that in aggregate contain over 28 PB of data and 64 million FAIR data objects. To set up a Gen3 data commons, you first define a data model. Gen3 then autogenerates 1) a data portal for searching and exploring data in the commons; 2) a data portal for submitting dat…

From Translink
A massive increase in bus service is coming to Metro Vancouver this fall, with TransLink delivering improvements to 53 routes used by more than 100,000 people every weekday.
More service on the five most overcrowded routes
321, 335, 345, 393, and 503
Service increases on 13 of the highest ridership routes
5/6, 9, 16, 19, 20, 49, 99, 100, 130, 321, 335, R1, and R4
For a complete list of service changes, visit translink.ca/servicechanges.

Heute vor 69 Jahren: Am 20. Juli 1956 kam es zum #Atomtest "Tewa". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

There’s a new #OpenStreetMap website feature related to #Wikidata!
When viewing objects in OSM that have a Wikidata tag, you can now click the Wikidata icon to turn the opaque QID values into human-readable info (plus a link to Wikipedia if any).

For #FOSSfriday I would just like to add that, while I am not a programmer, I picked this instance when I first signed up because I felt like it was the most philosophically aligned with the way I see the world.
It always seemed strategically untenable to devolve all of our computing needs to giant private corporations. It also seemed that developing software for the commons was a quiet a…

Two [more] MPs indicate a shift to oppose the assisted dying Bill as it returns to Commons | Morning Star
https://morningstaronline.co.uk/article/two-mps-indicate-shift-oppose-assisted-dying-bill-it-returns-commons…

Creative Commons launches “CC Signals”. Quote:
“TL;DR – What are CC signals?
“CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation.”

CC Signals: A New Social Contract for the Age of AI - Creative Commons
TL;DR – What are CC signals? CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation. 💗Love it! How can I show my support?…

Hey @…, how’s this for a CC signal for AI, you clowns?
🖕
https://creativecommons.org/2025/06/25

Introducing CC Signals: A New Social Contract for the Age of AI - Creative Commons
CC Signals © 2025 by Creative Commons is licensed under CC BY 4.0 Creative Commons (CC) today announces the public kickoff of the CC signals project, a new preference signals framework designed to increase reciprocity and sustain a creative commons in the age of AI. The development of CC signals represents a major step forward…

Какво е Creative Commons? - Петър Тушков
https://petertoushkov.eu/paper-books/kakvo-e-creative-commons

Какво е Creative Commons? - Петър Тушков
Наскоро публикувах моя български превод на „Приключенията на Алиса в Страната на чудесата“ под условията на договора Криейтив Комънс и имам усещането, че може би трябва да поговорим какво означават тези две думи.

Looked at @…'s Signals page (https://creativecommons.org/ai-and-the-commons/cc-signals/) again.
I think this…

CC Signals: A New Social Contract for the Age of AI - Creative Commons
TL;DR – What are CC signals? CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation. 💗Love it! How can I show my support?…

Creative Commons debuts CC Signals, a framework that will allow dataset holders to detail how their content can or cannot be reused for training AI models (Sarah Perez/TechCrunch)
https://techcrunch.com/2025/06/25/creative…

Creative Commons debuts CC signals, a framework for an open AI ecosystem | TechCrunch
CC signals will allow dataset holders to detail how their content can or cannot be reused by machines, as in the case of training AI models.

Everything is a commons. It's commons management all the way down.

Heute vor 69 Jahren: Am 21. Juni 1956 kam es zum #Atomtest "Inca". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps
Arman Noroozian, Lorena Aldana, Marta Arisi, Hadi Asghari, Renata Avila, Pietro Giovanni Bizzaro, Ramya Chandrasekhar, Cristian Consonni, Deborah De Angelis, Francesca De Chiara, Maria del Rio-Chanona, Melanie Dulong de Rosnay, Maria Eriksson, Frederic Font, Emilia Gomez, Val\'erian Guillier, Lisa Gutermuth, David Hartmann, Lucie-Aim\'ee Kaffee, Paul Keller, Felix Stalder, Joao Vinagre, …

Generative AI and the Future of the Digital Commons: Five Open Questions and Knowledge Gaps
The rapid advancement of Generative AI (GenAI) relies heavily on the digital commons, a vast collection of free and open online content that is created, shared, and maintained by communities. However, this relationship is becoming increasingly strained due to financial burdens, decreased contributions, and misalignment between AI models and community norms. As we move deeper into the GenAI era, it is essential to examine the interdependent relationship between GenAI, the long-term sustainabilit…

Creative Commons debuts CC Signals, a framework that will allow dataset holders to detail how their content can or cannot be reused for training AI models (Sarah Perez/TechCrunch)
https://techcrunch.com/2025/06/25/creative…

Creative Commons debuts CC signals, a framework for an open AI ecosystem | TechCrunch
CC signals will allow dataset holders to detail how their content can or cannot be reused by machines, as in the case of training AI models.

Check out today's Metacurity for the most crucial infosec developments you should know, including
--Russian hackers suspected of sabotaging a dam in Norway,
--Canadian House of Commons is probing a 'significant' data breach,
--North Korean hackers unmasked by leak to ZachXBT,
--Court rules that FCC data breach rules are legal,
--US AG sues Zelle for allegedly enabling scammer fraud,
--UK gov't spent $3.2m to keep Afghan breach secret
--…

Russian hackers suspected of sabotaging dam in Western Norway
Canadian House of Commons is probing a 'significant' data breach, North Korean hackers unmasked by leak to ZachXBT, Court rules that FCC data breach rules are legal, US AG sues Zelle for allegedly enabling scammer fraud, UK gov't spent $3.2m to keep Afghan breach secret, much more

Welp, looks like I'll need to file a bill to require that if the state is going to assert copyright over its historical markers, it's gotta be under a copyleft license: https://commons.wikimedia.org/wiki/Commons:Deletion_requests/Files_in_Category:Historical_markers_in_New_Hampshire
(that is, assuming something can't be worked out independently without one...)

Heute vor 53 Jahren: Am 20.07.1972 zündeten die USA im Rahmen von Operation Toggle die Atombombe "Diamond Sculls". Toggle war eine Serie von #Kernwaffentests bei der 72/73 insgesamt 35 Bomben größtenteils im Testgebiet in #Nevada und Rio Blanco unterirdisch gezündet wurden.

Is now a bad time to point out Canada already has a king, I've met him, he's a nice fellow as is his brother I dined with. Thing is, like most kings, he has absolutely no power whatsoever, the Commons write his speeches. It's a very good system, a living fairy tale.
In the seventies I lobbied to have PET declared king for the same reason, to get him out of politics.

Hey, that's Valencia!
#Andor
https://commons.wikimedia.org/wiki/Fil

I tried Flickr’s Creative Commons (https://www.flickr.com/creativecommons/) search today and was greeted with a page-blocking sign-up modal.
Eff that.
Stylus CSS:
```
.blur-overlay,
.fluid-modal-view.blur-overlay,
.photo-page-sidebar,
.upgrade-to-pr…

ICYMI yesterday: I've been writing about the diversity of tools for contributing to #OpenStreetMap and how this diversity plays a role in creating and maintaining a healthy commons.
https://tzovar.as/tool-diversity/

Home and dry now - there was a bigger turn out than you'd have thought, but at least we all got home in time to watch Le Mans 😃
A few photos at https://timfoster.smugmug.com/Events/Stormont-Car-Show-2025

Stormont Car Show 2025 - timfoster
All of the photos under timfoster.smugmug.com are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Please contact me if you want to use any of these photos for commercial purposes. You're welcome to print any photos you like for your own use.

Heute vor 52 Jahren: Am 21.06.1973 zündeten die USA im Rahmen von Operation Toggle die Atombombe "Potrillo". Toggle war eine Serie von #Kernwaffentests bei der 72/73 insgesamt 35 Bomben größtenteils im Testgebiet in #Nevada und Rio Blanco unterirdisch gezündet wurden.

Heute vor 38 Jahren: Am 20.06.1987 zündeten die #USA im Rahmen von Operation Musketeer die Atombombe "Mission Ghost". Musketeer war eine Serie von #Kernwaffentests bei der 1986/87 insgesamt 16 Bomben im Testgebiet in

To add a single example here (feel free to chime in with your own):
Problem: editing code is sometimes tedious because external APIs require boilerplate.
Solutions:
- Use LLM-generated code. Downsides: energy use, code theft, potential for legal liability, makes mistakes, etc. Upsides: popular among some peers, seems easy to use.
- Pick a better library (not always possible).
- Build internal functions to centralize boilerplate code, then use those (benefits: you get a better understanding of the external API, and a more-unit-testable internal code surface; probably less amortized effort).
- Develop a non-LLM system that actually reasons about code at something like the formal semantics level and suggests boilerplate fill-ins based on rules, while foregrounding which rules it's applying so you can see the logic behind the suggestions (needs research).
Obviously LLM use in coding goes beyond this single issue, but there are similar analyses for each potential use of LLMs in coding. I'm all cases there are:
1. Existing practical solutions that require more effort (or in many cases just seem to but are less-effort when amortized).
2. Near-term researchable solutions that directly address the problem and which would be much more desirable in the long term.
Thus in addition to disastrous LLM effects on the climate, on data laborers, and on the digital commons, they tend to suck us into cheap-seeming but ultimately costly design practices while also crowding out better long-term solutions. Next time someone suggests how useful LLMs are for some task, try asking yourself (or them) what an ideal solution for that task would look like, and whether LLM use moves us closer to or father from a world in which that solution exists.

Der #Leapmotor T03 scheint die Leute hier anzusprechen. In #Jena sehe ich in letzter Zeit sehr viele davon.
#eauto

Eugene de Blaas, In the Water. (Wikimedia Commons)

Heute vor 46 Jahren: Am 20.06.1979 zündeten die #USA im Rahmen von Operation Quicksilver die 10. Atombombe "Chess". Quicksilver war eine Serie von #Kernwaffentests bei der 1978/79 insgesamt 16 Bomben im Testgebiet in

What do people think of this as a suitable t-shirt/hoodie design in response to the proscription of #PalestineAction ?
#GazaGenocide

#AI is a great example of the Tragedy of the Commons. We all know it’s trashing the planet but we carry on using it because ‘everyone else is’.
#Environment

Creative Commons jumps the shark.
*smdh*
#AI #CreativeCommons https://mastodon.social/@creativeco…

When autism is genuine and @… becomes a hobby, you end up creating this new flag for https://nsf-iaa.org. Lmao.

Nice! I just learned that my forthcoming article (with Marijana Hamersak) will be #OpenAccess due to some agreement of @… with SAGE.
Coming soon in Memory Studies
#ElShatt

Die Veranstaltung ist eine gute Gelegenheit, das gesammelte Wissen auf #Wikidata und Wikimedia #Commons für alle und dauerhaft zu dokumentieren:

Sprouting technology otherwise, hospicing negative commons -- Rethinking technology in the transition to sustainability-oriented futures
Martin Deron
https://arxiv.org/abs/2508.05860

Sprouting technology otherwise, hospicing negative commons -- Rethinking technology in the transition to sustainability-oriented futures
Due to its significant and growing environmental harms, both directly through its materiality and indirectly through its pervasive integration into unsustainable economic systems, ICT will need to be radically redirected to align with sustainability-oriented futures. While the role of ICT in such futures will likely diverge significantly from current dynamics, it will probably not be entirely disconnected from the present. Instead, such transition involves complex dynamics of continuity, adapta…

У меня на экране блокировки стоит "Изображение дня" из Wikimedia Commons. Обычно это какой-нибудь пейзаж, природа, картина, здание и всё в этом духе, но сегодня это ОБАМА.
Я долго не могла проржаться.

From CreativeCommons with their "signals" to the OSI with their "open source AI" fiasco it seems that the stewards of the legal structures protecting the digital commons are not on the side of people actually wanting to contribute to the commons for humanity. (Maybe they never were.)
If those organizations don't reorient themselves to align with people's needs maybe we need to fork.

Following our mapping party for OpenStreetMap's birthday, I've been thinking more about the diversity of OSM tools and how they help create and maintain a commons.
#OpenStreetMap

As it happens she was upset before PMQs started, it's reported as being something personal, pointless speculation isn't very useful.
https://mastodonapp.uk/@bbcnewsfeed/114784881998604378

Ich wurde gebeten, meine Infografik "Kultur einer Mensch-Maschine-Kollaboration gemeinsam einüben" unter einer creativecommons-Lizenz zur allgemeinen Verfügung zu stellen.
Sie ist jetzt lizensiert als CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/…

At its core, #CCSignals is an attempt by Creative Commons, a Silicon Valley-based organisation, to legitimise the AI grifts of its donors – Google, Microsoft, and Meta (Zuckerberg).
Creative Commons was always a thinly-veiled attempt at enabling Big Tech data farmers to get more data (that’s why the whole “open data” realm is so well funded/popular – open as in “open for business” not fre…

Heute vor 68 Jahren: Am 19. Juli 1957 fand der #Atomtest "John" (9/29) im Rahmen der Operation #Plumbbob in Nevada statt. Sie beinhaltete die höchsten Turmtests in den #USA, umfasste Luftabwehr …

Heute vor 51 Jahren: Am 19. Juni 1974 führten die #USA in #Nevada den #Atomtest "Ming Blade", Teil der "Operation Arbor", durch. Bei dieser Operation wurden 1973/74 20 Atomtests unterird…

Should we teach vibe coding? Here's why not.
Should AI coding be taught in undergrad CS education?
1/2
I teach undergraduate computer science labs, including for intro and more-advanced core courses. I don't publish (non-negligible) scholarly work in the area, but I've got years of craft expertise in course design, and I do follow the academic literature to some degree. In other words, In not the world's leading expert, but I have spent a lot of time thinking about course design, and consider myself competent at it, with plenty of direct experience in what knowledge & skills I can expect from students as they move through the curriculum.
I'm also strongly against most uses of what's called "AI" these days (specifically, generative deep neutral networks as supplied by our current cadre of techbro). There are a surprising number of completely orthogonal reasons to oppose the use of these systems, and a very limited number of reasonable exceptions (overcoming accessibility barriers is an example). On the grounds of environmental and digital-commons-pollution costs alone, using specifically the largest/newest models is unethical in most cases.
But as any good teacher should, I constantly question these evaluations, because I worry about the impact on my students should I eschew teaching relevant tech for bad reasons (and even for his reasons). I also want to make my reasoning clear to students, who should absolutely question me on this. That inspired me to ask a simple question: ignoring for one moment the ethical objections (which we shouldn't, of course; they're very stark), at what level in the CS major could I expect to teach a course about programming with AI assistance, and expect students to succeed at a more technically demanding final project than a course at the same level where students were banned from using AI? In other words, at what level would I expect students to actually benefit from AI coding "assistance?"
To be clear, I'm assuming that students aren't using AI in other aspects of coursework: the topic of using AI to "help you study" is a separate one (TL;DR it's gross value is not negative, but it's mostly not worth the harm to your metacognitive abilities, which AI-induced changes to the digital commons are making more important than ever).
So what's my answer to this question?
If I'm being incredibly optimistic, senior year. Slightly less optimistic, second year of a masters program. Realistic? Maybe never.
The interesting bit for you-the-reader is: why is this my answer? (Especially given that students would probably self-report significant gains at lower levels.) To start with, [this paper where experienced developers thought that AI assistance sped up their work on real tasks when in fact it slowed it down] (https://arxiv.org/abs/2507.09089) is informative. There are a lot of differences in task between experienced devs solving real bugs and students working on a class project, but it's important to understand that we shouldn't have a baseline expectation that AI coding "assistants" will speed things up in the best of circumstances, and we shouldn't trust self-reports of productivity (or the AI hype machine in general).
Now we might imagine that coding assistants will be better at helping with a student project than at helping with fixing bugs in open-source software, since it's a much easier task. For many programming assignments that have a fixed answer, we know that many AI assistants can just spit out a solution based on prompting them with the problem description (there's another elephant in the room here to do with learning outcomes regardless of project success, but we'll ignore this over too, my focus here is on project complexity reach, not learning outcomes). My question is about more open-ended projects, not assignments with an expected answer. Here's a second study (by one of my colleagues) about novices using AI assistance for programming tasks. It showcases how difficult it is to use AI tools well, and some of these stumbling blocks that novices in particular face.
But what about intermediate students? Might there be some level where the AI is helpful because the task is still relatively simple and the students are good enough to handle it? The problem with this is that as task complexity increases, so does the likelihood of the AI generating (or copying) code that uses more complex constructs which a student doesn't understand. Let's say I have second year students writing interactive websites with JavaScript. Without a lot of care that those students don't know how to deploy, the AI is likely to suggest code that depends on several different frameworks, from React to JQuery, without actually setting up or including those frameworks, and of course three students would be way out of their depth trying to do that. This is a general problem: each programming class carefully limits the specific code frameworks and constructs it expects students to know based on the material it covers. There is no feasible way to limit an AI assistant to a fixed set of constructs or frameworks, using current designs. There are alternate designs where this would be possible (like AI search through adaptation from a controlled library of snippets) but those would be entirely different tools.
So what happens on a sizeable class project where the AI has dropped in buggy code, especially if it uses code constructs the students don't understand? Best case, they understand that they don't understand and re-prompt, or ask for help from an instructor or TA quickly who helps them get rid of the stuff they don't understand and re-prompt or manually add stuff they do. Average case: they waste several hours and/or sweep the bugs partly under the rug, resulting in a project with significant defects. Students in their second and even third years of a CS major still have a lot to learn about debugging, and usually have significant gaps in their knowledge of even their most comfortable programming language. I do think regardless of AI we as teachers need to get better at teaching debugging skills, but the knowledge gaps are inevitable because there's just too much to know. In Python, for example, the LLM is going to spit out yields, async functions, try/finally, maybe even something like a while/else, or with recent training data, the walrus operator. I can't expect even a fraction of 3rd year students who have worked with Python since their first year to know about all these things, and based on how students approach projects where they have studied all the relevant constructs but have forgotten some, I'm not optimistic seeing these things will magically become learning opportunities. Student projects are better off working with a limited subset of full programming languages that the students have actually learned, and using AI coding assistants as currently designed makes this impossible. Beyond that, even when the "assistant" just introduces bugs using syntax the students understand, even through their 4th year many students struggle to understand the operation of moderately complex code they've written themselves, let alone written by someone else. Having access to an AI that will confidently offer incorrect explanations for bugs will make this worse.
To be sure a small minority of students will be able to overcome these problems, but that minority is the group that has a good grasp of the fundamentals and has broadened their knowledge through self-study, which earlier AI-reliant classes would make less likely to happen. In any case, I care about the average student, since we already have plenty of stuff about our institutions that makes life easier for a favored few while being worse for the average student (note that our construction of that favored few as the "good" students is a large part of this problem).
To summarize: because AI assistants introduce excess code complexity and difficult-to-debug bugs, they'll slow down rather than speed up project progress for the average student on moderately complex projects. On a fixed deadline, they'll result in worse projects, or necessitate less ambitious project scoping to ensure adequate completion, and I expect this remains broadly true through 4-6 years of study in most programs (don't take this as an endorsement of AI "assistants" for masters students; we've ignored a lot of other problems along the way).
There's a related problem: solving open-ended project assignments well ultimately depends on deeply understanding the problem, and AI "assistants" allow students to put a lot of code in their file without spending much time thinking about the problem or building an understanding of it. This is awful for learning outcomes, but also bad for project success. Getting students to see the value of thinking deeply about a problem is a thorny pedagogical puzzle at the best of times, and allowing the use of AI "assistants" makes the problem much much worse. This is another area I hope to see (or even drive) pedagogical improvement in, for what it's worth.
1/2

A tunnelled road underneath Ontario's Highway 401 would be an expensive and very short term solution to congestion. A high speed train subway would be cheaper, move many more people and cost less.
A better Toronto, for all.
A Real Solution to Highway 401 Congestion — the Express Subway.
A subway to Pickering makes much more sense than a 401 Tunnel.

Heute vor 33 Jahren: Am 19. Juni 1992 zündeten die #USA im Rahmen von Operation Julin die 4. Atombombe "Victoria". Julin war eine Serie von #Kernwaffentests bei der 1991/92 insgesamt 9 Bomben im Testgebiet in

Heute vor 50 Jahren: Am 19. Juni 1975 testen die #USA die Atombombe "Mast". Die Operation Bedrock war eine Serie von 27 US-amerikanischen #Kernwaffentests, die 1974/75 auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde.

Verlage haben ja i.d.R. solche an Desinformation grenzenden Urheberrechtswarnungen. Ich frage mich, ob da die Bildredaktionen ihrerseits entsprechend sorgfältig die Rechte eingeholt haben. Abbildungen aus Wikimedia Commons dürften oft CC BY oder restriktiver lizenziert sein. Dem genügt der Bildnachweis dann nicht.

ICT Within Limits Is Bound To Be Old-Fashioned By Design
Olivier Michel, Emilie Frenkiel
https://arxiv.org/abs/2508.08311 https://arxiv.org/pdf/2508.08311

ICT Within Limits Is Bound To Be Old-Fashioned By Design
Crossing multiple planetary boundaries places us in a zone of uncertainty that is characterized by considerable fluctuations in climatic events. The situation is exacerbated by the relentless use of resources and energy required to develop digital infrastructures that have become pervasive and ubiquitous. We are bound to these infrastructures, dead technologies and negative commons, just as much as they bind us. Although their growth threatens the necessary reduction of our impact, we have a re…

Heute vor 68 Jahren: Am 18. August 1957 fand der #Atomtest "Shasta" (15/29) im Rahmen der Operation #Plumbbob in Nevada statt. Sie beinhaltete die höchsten Turmtests in den #USA, umfasste Luftab…

Heute vor 51 Jahren: Am 18 Juli 1974 testen die #USA simultan die Atombomben "Crestlake-Briar" u. "Crestlake-Tansan". Die Operation Bedrock war eine Serie von 27 US-amerikanischen #Kernwaffentests, die 1974/75 auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde…

Heute vor 27 Jahren: Am 13. Juli 1998 fiel im armenischen #Kernkraftwerk #Mezamor während eines Tests das komplette Notkühlwasserpumpensystem (EFP) aus. Die Funktionsfähigkeit wurde nach über 6 Stunden wiederhergestellt. Keine Strahlung freigesetzt.

Heute vor 40 Jahren: Am 17. August 1985 zündeten die #USA im Rahmen von Operation Grenadier die 15. Atombombe "Chamita". Grenadier war eine Serie von #Kernwaffentests bei der 1984/85 insgesamt 16 Bomben im Testgebiet in

Heute vor 67 Jahren: Am 17.07.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Pisonia". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 57 Jahren: Am 17. Juli 1968 zündeten die #USA im Rahmen von Operation Bowline die Atombombe "Spud". Bowline war eine Serie von #Kernwaffentests bei der 68/69 insgesamt 58 Bomben im Testgebiet in #Nevada

Heute vor 39 Jahren: Am 17. Juli 1986 zündeten die #USA im Rahmen von Operation Charioteer die 12. Atombombe "Cybar". Charioteer war eine Serie von #Kernwaffentests bei der 1985/86 insgesamt 16 Bomben im Testgebiet in

Heute vor 48 Jahren: Am 16.08.1977 zündeten die #USA im Rahmen von Operation Fulcrum simultan die 18. u. 19. Atombombe "Gruyere" und "Gradino". Fulcrum war eine Serie von #Kernwaffentests bei der 1976/77 insgesamt 24 Bomben im Testgebiet in

Heute vor 54 Jahren: Am 16. Juni 1971 kam es zum #Atomtest "Embudo". Die Operation #Emery war eine US-Serie von 24 Atomtestdetonationen zwischen 1970/71. Sie wurden auf dem Nevada Test Site (NST) unterirdisch durchgeführt und dienten der Waffenentwicklung.

Heute vor 56 Jahren: Am 16. Juli 1969 testen die #USA die Atombombe "Ildrim". Operation Mandrel war eine Serie von 53 US-amerikanischen #Kernwaffentests, die 1969 und 1970 hauptsächlich auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde.

Heute vor 44 Jahren: Am 16. Juli 1981 testen die #USA die #Atombombe "Pineau". Die Operation #Guardian war eine Serie von 14 US-amerikanischen

Heute vor 69 Jahren: Am 16. Juni 1956 kam es zum #Atomtest "Osage". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

Heute vor 43 Jahren: Am 16. Juni 1982 testen die #USA die Atombombe "Kesti". Die Operation #Praetorian war eine Serie von 20 US-amerikanischen #Kernwaffentests, die 1981/82 auf der Neva…

Heute vor 51 Jahren: Am 14 August 1974 testen die #USA die Atombombe "Puye". Die Operation Bedrock war eine Serie von 27 US-amerikanischen #Kernwaffentests, die 1974/75 auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde.

Heute vor 56 Jahren: Am 14. August 1969 testen die #USA zwei Atombomben "Spider-1" und "Spider-2". Operation Mandrel war eine Serie von 53 US-amerikanischen #Kernwaffentests, die 1969/70 hauptsächlich auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde.

Heute vor 40 Jahren: Am 14. August 1985 zündeten die #USA im Rahmen von Operation Grenadier die 14. Atombombe "Cebrero". Grenadier war eine Serie von #Kernwaffentests bei der 1984/85 insgesamt 16 Bomben im Testgebiet in

Heute vor 67 Jahren: Am 14.07.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Scaevola". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 67 Jahren: Am 14.06.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Walnut". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 67 Jahren: Am 14.06.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Aspen". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 69 Jahren: Am 13. Juni 1956 kam es zum #Atomtest "Kickapoo". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

Heute vor 41 Jahren: Am 12. Juli 1984 zündeten die USA im Rahmen von #Fusileer die #Atombombe "Normanna". Fusileer war eine Serie von Tests zwischen 83/84 bei der insgesamt 17 unterirdische #Kernwaffentests

Heute vor 67 Jahren: Am 12.08.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Orange". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 67 Jahren: Am 12.07.1958 kam es bei Enewetak zum Atomtest Operation Hardtack I, "Poplar". Dieser Test war Teil einer Serie von 35 #Atomtests, die die USA im Sommer 1958 auf den #Marshallinseln im Pazifik durchführten.

Heute vor 47 Jahren: Am 12.07.1978 zündeten die #USA im Rahmen von Operation Cresset die 17. Atombombe "Lowball". Cresset war eine Serie von #Kernwaffentests bei der 1977/78 insgesamt 23 Bomben im Testgebiet in

Heute vor 42 Jahren: Am 11.08.1983 zündeten die #USA im Rahmen von Operation Phalanx die 12. Atombombe "Sabado". Phalanx war eine Serie von #Kernwaffentests bei der 1982/83 insgesamt 19 Bomben größtenteils im Testgebiet in

Heute vor 63 Jahren: Am 11. Juli 1962 fand der #Atomtest "Pamlico" als Teil der US-Operation Dominic statt. Insgesamt wurden 31 Tests, viele davon mit B-52 Bombern, im #Pazifik mit 38,1 Mt Sprengkraft durchgeführt, darunter neue Waffen und die Überprüfung bestehender Modelle.

Heute vor 69 Jahren: Am 11. Juni 1956 kam es zum #Atomtest "Blackfoot". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

Heute vor 69 Jahren: Am 11. Juni 1956 kam es zum #Atomtest "Flathead". Die Operation #Redwing war eine US-Serie von 17 Atomtestdetonationen von Mai bis Juli 1956. Sie wurden von der Joint Task Force 7 (JTF7) auf den Atollen

Heute vor 46 Jahren: Am 11.06.1979 zündeten die #USA im Rahmen von Operation Quicksilver die 9. Atombombe "Pepato". Quicksilver war eine Serie von #Kernwaffentests bei der 1978/79 insgesamt 16 Bomben im Testgebiet in

Heute vor 50 Jahren: Am 11. Juni 1975 testen die #USA die Atombombe "Alviso". Die Operation Bedrock war eine Serie von 27 US-amerikanischen #Kernwaffentests, die 1974/75 auf der Nevada Test Site in Nevada unterirdisch durchgeführt wurde.