Tootfinder

The Duty Comes From the Data: Rethinking Platform Liability in the Age of Algorithmic Harm
https://musictechpolicy.com/2025/07/05

The Duty Comes From the Data: Rethinking Platform Liability in the Age of Algorithmic Harm
Platforms like TikTok and YouTube claim immunity under Section 230, but when they exploit user data to push harmful content, they cross into tort liability. It’s time to hold platforms accountable …

USAID Official and Three Corporate Executives Plead Guilty to Decade-Long Bribery Scheme Involving Over $550 Million in Contracts; Two Companies Admit Criminal Liability ... (US Department of Justice)
https://www.justice.gov/opa/pr/usaid-official-and-three-corporate-executives-plead-guilty-decade-long-bribery-scheme
http://www.memeorandum.com/250613/p132#a250613p132

CA state Senator Scott Wiener releases amendments to SB 53, which has transparency requirements for AI companies but omits SB 1047's provision on liability (Shirin Ghaffary/Bloomberg)
https://www.bloomberg.com/news/articles/20

This https://arxiv.org/abs/2505.00616 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current practices at many AI labs developing these systems lack sufficient transparency around safety measures, testing procedures, and governance structures. This opacity makes it challenging to verify safety claims or establish appropriate liability when harm occurs. Drawing on liability frameworks from nuclear energy, aviati…

One thing I've noticed about the coverage of the LA protests is the differing use of "non-lethal" and "less-lethal" in describing weapons being used by the state against protesters.
And in this case I think the liability-dodging term "less lethal" is actually more useful, and should be incorporated into style-guides.

GOP tax bill includes a $6,000 ‘senior deduction.’ Here’s who qualifies.
Under current law, most taxpayers claim the standard deduction of $15,000 (or $30,000 for couples)
to reduce their tax liability,
though the GOP tax bill would increase those amounts slightly.
Additionally, seniors already qualify for an additional deduction of $2,000 (or $3,600 for couples).

The Senate bill would create a third category that gives seniors an additional $6,000 (or $12,000) off…

GOP tax bill includes a $6,000 ‘senior deduction.’ Here’s who qualifies.
The provision emerged from President Donald Trump’s campaign pledge to end taxes on Social Security. But experts say many are excluded.

#kde kmymoney also started to eat data. If Devs turn something from reliable and safe to unreliable and unsafe, the real question of liability comes into play. How can such a thing end in distribution?
Maybe we need to re-organize open source to have a reliable portfolio of applications, a kind of reliable #kde fr…

FOIA docs: the Trump administration claimed broad authority to nullify laws in letters to tech firms releasing them of legal liability related to the TikTok ban (Charlie Savage/New York Times)
https://www.nyt…

How the Trump Administration Justified Ignoring the TikTok Ban
In purporting to license otherwise illegal conduct by tech firms, President Trump set a precedent expanding executive power, legal experts warned.

"Nigerian communities to take Shell to high court over oil pollution"
#Nigera #Shell #Pollution

Nigerian communities to take Shell to high court over oil pollution https://www.theguardian.com/environment/2025/jun/20/nigerian-communities-shell-high-court-oil-pollution

I just got a request from the US FAA to sign an addendum on a purchase of one of our products.
This seems weird and redundant - kinda like something triggered by the DOG-E gang. But I have not yet found any actual explanation.
"Nothing contained in the Agreement will obligate the United States Government to indemnify any indemnified
person(s) for damages, costs, fees, or any other loss or liability that would create an Anti-Deficiency Act
violation (31 U.S.C. §134…

Persistence Paradox in Dynamic Science
Honglin Bao, Kai Li
https://arxiv.org/abs/2506.22729 https://arxiv.org/pdf/2506.22729

Persistence Paradox in Dynamic Science
Persistence is often regarded as a virtue in science. In this paper, however, we challenge this conventional view by highlighting its contextual nature, particularly how persistence can become a liability during periods of paradigm shift. We focus on the deep learning revolution catalyzed by AlexNet in 2012. Analyzing the 20-year career trajectories of over 5,000 scientists who were active in top machine learning venues during the preceding decade, we examine how their research focus and output…

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.

Cowboys' RB room: Thunder and lightning is the way to go https://insidethestar.com/cowboys-rb-room-thunder-and-lightning-is-the-way-to-go

Flexible Moral Hazard Problems with Adverse Selection
Siwen Liu
https://arxiv.org/abs/2506.23954 https://arxiv.org/pdf/2506.23954

Flexible Moral Hazard Problems with Adverse Selection
We study a moral hazard problem with adverse selection: a risk-neutral agent can directly control the output distribution and possess private information about the production environment. The principal designs a menu of contracts satisfying limited liability. Deviating from classical models, not only can the principal motivate the agent to exert certain levels of aggregate efforts by designing the "power" of the contracts, but she can also regulate the support of the chosen output distributions…

This https://arxiv.org/abs/2410.13878 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Corporate Non-Disclosure Disputes: equilibrium settlement where increasing legal liability encourages voluntary disclosures
How should a court resolve a shareholder-management dispute after an unexpected price drop, when it is suspected that at an earlier time management chose not to update (disclose to) the market about a material event that was privately observed? An earlier fundamental result in this area (Dye, 2017) has shown that if the court chooses to make public that it will increase awards of damages to try and deter non-disclosure, then this may have the perverse effect that management may rationally choos…

This https://arxiv.org/abs/2502.19213 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Framework for asset-liability management with fixed-term securities
We consider an optimal investment-consumption problem for a utility-maximizing investor who has access to assets with different liquidity and whose consumption rate as well as terminal wealth are subject to lower-bound constraints. Assuming utility functions that satisfy standard conditions, we develop a methodology for deriving the optimal strategies in semi-closed form. Our methodology is based on the generalized martingale approach and the decomposition of the problem into subproblems. We il…

Hey, #Utahns #utpol #utleg #SaltLake