| Signal | dez.01 |
| Signal | dez.01 |
🇪🇺📢 As #ChatControl will hopefully end, a new study proves mass scanning tech is flawed & easily evaded. 🔬
To truly protect kids now, we must shift from broken algorithms to targeted police work 🕵️♂️ and strict #SecurityByDesign 🛡️.
Read: https://www.patrick-breyer.de/en/end-of-chat-control-paving-the-way-for-genuine-child-protection/

The controversial mass surveillance of private messages in Europe could soon come to an end. Negotiations between the European Parliament and EU member states regarding the extension of the so-called "Chat Control" concluded yesterday without an agreement. This means that starting April 4, US tech g
Every AI company knows they're building the wrong thing.
And they can't stop.
Because the competitive structure specifically punishes anyone who slows down long enough to build the right thing.
The race is real. The destination is fake.
https://www.joanwestenberg.com/everyone-in-ai-is-building-the-wrong-thing-for-the-same-reason/

Every AI founder I talk to is on an accelerating treadmill, burdened by a nagging suspicion that the entire industry is moving too fast in a direction that doesn't quite make sense, with no idea about how to get off. There is an overwhelming feeling that if everyone stopped and
Whatever the output gains promised by LLMs, their initial productivity surge is erased over time, and replaced by heavier workloads—and that leads to workers experiencing “cognitive fatigue, burnout, and weakened decision-making.”
All this from research out of the notoriously pro-worker rag [checks notes] Harvard Business Review: https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it

One of the promises of AI is that it can reduce workloads so employees can focus more on higher-value and more engaging tasks. But according to new research, AI tools don’t reduce work, they consistently intensify it: In the study, employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so. That may sound like a win, but it’s not quite so simple. These changes can be unsustainable, leading to workload creep, cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems. To correct for this, companies need to adopt an “AI practice,” or a set of norms and standards around AI use that can include intentional pauses, sequencing work, and adding more human grounding.