When I was a PhD student, I attended a talk by the late Robin Milner where he said two things that have stuck with me.
The first, I repeat quite often. He argued that credit for an invention did not belong to the first person to invent something but to the first person to explain it well enough that no one needed to invent it again. His first historical example was Leibniz publishing calculus and then Newton claiming he invented it first: it didn’t matter if he did or not, he failed to explain it to anyone and so the fact that Leibniz needed to independently invent it was Newton’s failure.
The second thing, which is a lot more relevant now than at the time, was that AI should stand for Augmented Intelligence not Artificial Intelligence if you want to build things that are actually useful. Striving to replace human intelligence is not a useful pursuit because there is an abundant supply of humans and you can improve the supply of intelligent humans by removing food poverty, improving access to education, and eliminating other barriers that prevent vast numbers of intelligent humans from being able to devote time to using their intelligence. The valuable tools are ones that do things humans are bad at. Pocket calculators changed the world because being able to add ten-digit numbers together orders of magnitude faster allowed humans to use their intelligence for things that were not the tedious, repetitive, tasks (and get higher accuracy for those tasks). If you want to change the world, build tools that allow humans to do more by offloading things humans are bad at and allowing them to spend more time on things humans are good at.
Anyone spending the brief liminal window between Christmas and Georgian new year in Hamburg, with the hackers, at CCC?
I am! With new research and a new talk ☺️
What happens when we center love in our understanding of privacy? What are the consequences of its disavowal, in favor of a familiar technocratic definition of privacy-as-absence, privacy-as-isolation? What role does our desire for love/fear of rejection have to do with the shape of the tech today?
halfnarp.events.ccc.de
With everything going on right now preserving, contextualizing and promoting history and digital archives is more important than ever. You have to know the past to understand the present.
V USA rozhodla volby ekonomika = inflace
Německo, rozpad vlády a předčasné volby: jako ano, ceny v Německu vzrostly o něco méně než v USA = "a bude to stačit, myslíš?"
ČR: hold my beer aka "neříkám nic"
Thank you Mastodon and the Fediverse for being an example of communicating without billionaires and US venture capitalists calling the shots. We're going to need more of this.
Tohle se dnes hodí. Jane Werichu, to snad buďte rád, že jste se nedočkal dnešní doby 🙁🤦
#dobaKonce #JanWerich #citáty
We live in an amazing time—a Pakistani website specializing in publishing fake news created by AI to earn advertising revenue published an announcement of a non-existent Halloween parade in Dublin. The article was picked up by search algorithms and rose in Google's results. Journalists began spreading the news in their publications without even bothering to verify it. As a result, thousands of people came to the square, ready to participate in a parade that didn't exist. #FakeNews #AI #Media #Dublin #Halloween #Misinformation
![An awareness of the history of p-values might elp deflate their swollen stature and encourage more judicious use. We were surprised to learn, in the course of writing this article, that the p < 0.05 cutoff was established as a competitive response to a disagreement over book royalties between two foundational statisticians. In the early 1920s, Kendall Pearson, whose income depended on the sale of extensive statistical tables, was unwilling to allow Ronald A. Fisher to use them in his new book. To work around this barrier, Fisher created a method of inference based on only two values: p-values of 0.05 and 0.01 (Hurlbert and Lombardi,
2009). Fisher himself later admitted that Pearson's more continuous method of inference was better than his binary approach: "no scientific worker has a fixed level of significance at which from year to year, and in all circumstances, he rejects [null] hypotheses; he rather gives his mind to each particular case in the light of his evidence and ideas (Hurlbert and Lombardi, 2009: 316). A fair interpretation of this history is that we use p-values at east in part because a statistician from the 1920s was afraid that sharing his work would undermine his income](https://s3.eu-central-2.wasabisys.com/mastodonworld/media_attachments/files/113/404/999/832/750/171/original/197090ae839ab845.jpeg "An awareness of the history of p-values might elp deflate their swollen stature and encourage more judicious use. We were surprised to learn, in the course of writing this article, that the p < 0.05 cutoff was established as a competitive response to a disagreement over book royalties between two foundational statisticians. In the early 1920s, Kendall Pearson, whose income depended on the sale of extensive statistical tables, was unwilling to allow Ronald A. Fisher to use them in his new book. To work around this barrier, Fisher created a method of inference based on only two values: p-values of 0.05 and 0.01 (Hurlbert and Lombardi,
2009). Fisher himself later admitted that Pearson's more continuous method of inference was better than his binary approach: \"no scientific worker has a fixed level of significance at which from year to year, and in all circumstances, he rejects [null] hypotheses; he rather gives his mind to each particular case in the light of his evidence and ideas (Hurlbert and Lombardi, 2009: 316). A fair interpretation of this history is that we use p-values at east in part because a statistician from the 1920s was afraid that sharing his work would undermine his income")