RE: https://toot.cat/@plexus/116283016837715719
It should also be noted that beyond the ethical, political and environmental issues with this is that it doesn't work:
1. There is on average no mid to long term productivity gain with actual real-world software development that isn't just a "wow see what it can do" demo. (Multiple studies have shown that now.)
2. It won't help with 90% of the work when professionally making software, which, believe it or not, isn't coding. 90% of the work is designing and planning the software (these are things that happen both upfront and during development).
Maybe you have seen the recent Microsoft thing rolling back features in Windows they added?
E.g. Copilot in Notepad. What they did is essentially outsourcing project management to developers who then outsourced it to LLMs. But an LLMs can't plan and design software, and arguably barely can even generate code that works (as in reliable and performant). So now they have a buggy mess with features no one wants and they're rolling it back.
There's no silver bullets in software development.
Good #process_improvement practices include:
standardized improvement process (pdsa, or whatever)
Going to the gemba – improvement is done where the work is done. You must go to the where the action is. Sitting in meeting rooms, or offices, reading reports and making decisions is not the way to improve effectively.
evidence based decision making
...
I never realized making everyone spend time in the most crowded, most slowly moving lines would end up "prioritizing the general traveling population" - I thought that would just slow down throughput for everyone, creating longer, slower lines. I'm amazed at #Noem's brilliant management insights. /s
Homeland Security suspends TSA PreCheck, Global Entry airport security prog…
I never realized making everyone spend time in the most crowded, most slowly moving lines would end up "prioritizing the general traveling population" - I thought that would just slow down throughput for everyone, creating longer, slower lines. I'm amazed at #Noem's brilliant management insights. /s
Homeland Security suspends TSA PreCheck, Global Entry airport security prog…
RE: https://mastodon.social/@workchronicles/116260028658995411
If this is the decision making process on your project, it means your project is fucked.
Yes, I have suffered through those projects. They mean project leadership is incompetent. I…
Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
Xu Wan, Chao Yang, Cheng Yang, Jie Song, Mingyang Sun
https://arxiv.org/abs/2602.20729 https://arxiv.org/pdf/2602.20729 https://arxiv.org/html/2602.20729
arXiv:2602.20729v1 Announce Type: new
Abstract: Safe Reinforcement Learning (RL) is crucial for achieving high performance while ensuring safety in real-world applications. However, the complex interplay of multiple uncertainty sources in real environments poses significant challenges for interpretable risk assessment and robust decision-making. To address these challenges, we propose Fuz-RL, a fuzzy measure-guided robust framework for safe RL. Specifically, our framework develops a novel fuzzy Bellman operator for estimating robust value functions using Choquet integrals. Theoretically, we prove that solving the Fuz-RL problem (in Constrained Markov Decision Process (CMDP) form) is equivalent to solving distributionally robust safe RL problems (in robust CMDP form), effectively avoiding min-max optimization. Empirical analyses on safe-control-gym and safety-gymnasium scenarios demonstrate that Fuz-RL effectively integrates with existing safe RL baselines in a model-free manner, significantly improving both safety and control performance under various types of uncertainties in observation, action, and dynamics.
toXiv_bot_toot
Coevolutionary dynamics of cooperation, risk, and cost in collective risk games
Lichen Wang, Shijia Hua, Yuyuan Liu, Liang Zhang, Linjie Liu, Attila Szolnoki
https://arxiv.org/abs/2603.20706 https://arxiv.org/pdf/2603.20706 https://arxiv.org/html/2603.20706
arXiv:2603.20706v1 Announce Type: new
Abstract: Addressing both natural and societal challenges requires collective cooperation. Studies on collective-risk social dilemmas have shown that individual decisions are influenced by the perceived risk of collective failure. However, existing feedback evolving game models often focus on a single feedback mechanism, such as the coupling between cooperation and risk or between cooperation and cost. In many real-world scenarios, however, the level of cooperation, the cost of cooperating, and the collective risk are dynamically interlinked. Here, we present an evolutionary game model that considers the interplay of these three variables. Our analysis shows that the worst-case scenario, characterized by full defection, maximum risk, and the highest cost of cooperation, remains a stable evolutionary attractor. Nevertheless, cooperation can emerge and persist because the system also supports stable equilibria with non-zero cooperation. The system exhibits multistability, meaning that different initial conditions lead to either sustained cooperation or a tragedy of the commons. These findings highlight that initial levels of cooperation, cost, and risk collectively determine whether a population can avert a tragic outcome.
toXiv_bot_toot
In the winter of 1898, a mechanical engineer named Frederick Winslow Taylor arrived at the Bethlehem Steel Company in Pittsburgh with a stopwatch and a conviction.
Taylor had been thinking for years about why industrial work was so inefficient, and he believed he had found the answer:
the problem, he thought, was that the people who did the work were also the people who decided how to do it.
Workers brought their own habits, their own rhythms, their own judgment. All of th…
The TC39 Temporal proposal is coming along. It’s meant to replace JavaScript’s date API:
https://www.igalia.com/2026/03/13/Temporal-Reaches-Stage-4.html
Jason Williams’ talk about this at State of the Browser is now online:
Past administrations had been war-gaming an Iran invasion for decades
– but with Trump in the White House, observers said that the rigidly closed circle of advisers around him,
the collapse of an interagency process in the government
and his erratic decision-making process made this unlike any other US military campaign in recent memory.
Donald Trump’s back-of-the-envelope plan for regime change in Tehran ran into the reality of the largest US intervention in the Midd…