(Roughly) Daily

Posts Tagged ‘modeling

“Prediction is very difficult, especially if it’s about the future”*…

… but maybe not as hard as it once was. While multi-agent artificial intelligence was first used in the sixties, advances in technology have made it an extremely sophisticated modeling– and prediction– tool. As Derek Beres explains, it can be a powerfully-accurate prediction engine… and it can potentially also be an equally powerful tool for manipulation…

The debate over free will is ancient, yet data don’t lie — and we have been giving tech companies access to our deepest secrets… We like to believe we’re not predictable, but that’s simply not true…

Multi-agent artificial intelligence (MAAI) is predictive modeling at its most advanced. It has been used for years to create digital societies that mimic real ones with stunningly accurate results. In an age of big data, there exists more information about our habits — political, social, fiscal — than ever before. As we feed them information on a daily basis, their ability to predict the future is getting better.

[And] given the current political climate around the planet… MAAI will most certainly be put to insidious means. With in-depth knowledge comes plenty of opportunities for exploitation and manipulation, no deepfake required. The intelligence might be artificial, but the target audience most certainly is not…

Move over deepfakes; multi-agent artificial intelligence is poised to manipulate your mind: “Can AI simulations predict the future?,” from @derekberes at @bigthink.

[Image above: source]

* Niels Bohr


As we analyze augury, we might note that today is National Computer Security Day. It was inaugurated by the Association for Computing Machinery (ACM) in 1988, shortly after an attack on ARPANET (the forerunner of the internet as we know it) that damaged several of the connected machines. Meant to call attention to the need for constant need for attention to security, it’s a great day to change all of one’s passwords.


Written by (Roughly) Daily

November 30, 2022 at 1:00 am

“In the attempt to make scientific discoveries, every problem is an opportunity and the more difficult the problem, the greater will be the importance of its solution”*…

(Roughly) Daily is headed into its traditional Holiday hibernation; regular service will begin again very early in the New Year.

It seems appropriate (especially given the travails of this past year) to end the year on a positive and optimistic note, with a post celebrating an extraordinary accomplishment– Science magazine‘s (thus, the AAAS‘) “Breakthrough of the Year” for 2021…

In his 1972 Nobel Prize acceptance speech, American biochemist Christian Anfinsen laid out a vision: One day it would be possible, he said, to predict the 3D structure of any protein merely from its sequence of amino acid building blocks. With hundreds of thousands of proteins in the human body alone, such an advance would have vast applications, offering insights into basic biology and revealing promising new drug targets. Now, after nearly 50 years, researchers have shown that artificial intelligence (AI)-driven software can churn out accurate protein structures by the thousands—an advance that realizes Anfinsen’s dream and is Science’s 2021 Breakthrough of the Year.

AI-powered predictions show proteins finding their shapes: the full story: “Protein structures for all.”

And read Nature‘s profile of the scientist behind the breakthrough: “John Jumper: Protein predictor.”

* E. O. Wilson


As we celebrate science, we might send well-connected birthday greetings to Robert Elliot Kahn; he was born on this date in 1938. An electrical engineer and computer scientist, he and his co-creator, Vint Cerf, first proposed the Transmission Control Protocol (TCP) and the Internet Protocol (IP), the fundamental communication protocols at the heart of the Internet. Later, he and Vint, along with fellow computer scientists Lawrence Roberts, Paul Baran, and Leonard Kleinrock, built the ARPANET, the first network to successfully link computers around the country.

Kahn has won the Turing Award, the National Medal of Technology, and the Presidential Medal Of Freedom, among many, many other awards and honors.


“It is impossible to work in information technology without also engaging in social engineering”*…


ai religion

… Using a separate model, Future of Religion and Secular Transitions (forest), the team found that people tend to secularize when four factors are present: existential security (you have enough money and food), personal freedom (you’re free to choose whether to believe or not), pluralism (you have a welcoming attitude to diversity), and education (you’ve got some training in the sciences and humanities). If even one of these factors is absent, the whole secularization process slows down. This, they believe, is why the U.S. is secularizing at a slower rate than Western and Northern Europe.

“The U.S. has found ways to limit the effects of education by keeping it local, and in private schools, anything can happen,” said [LeRon] Shults’s collaborator, Wesley Wildman, a professor of philosophy and ethics at Boston University. “Lately, there’s been encouragement from the highest levels of government to take a less than welcoming cultural attitude to pluralism. These are forms of resistance to secularization.”

When you build a model, you can accidentally produce recommendations that you weren’t intending. Years ago, Wildman built a model to figure out what makes some extremist groups survive and thrive while others disintegrate. It turned out one of the most important factors is a highly charismatic leader who personally practices what he preaches. “This immediately implied an assassination criterion,” he said. “It’s basically, leave the groups alone when the leaders are less consistent, [but] kill the leaders of groups that have those specific qualities. It was a shock to discover this dropping out of the model. I feel deeply uncomfortable that one of my models accidentally produced a criterion for killing religious leaders.”

The results of that model have been published, so it may already have informed military action. “Is this type of thing being used to figure out criteria for drone killings? I don’t know, because there’s this giant wall between the secret research in the U.S. and the non-secret side,” Wildman said. “I’ve come to assume that on the secret side they’ve pretty much already thought of everything we’ve thought of, because they’ve got more money and are more focused on those issues. … But it could be that this model actually took them there. That’s a serious ethical conundrum.”

Shults told me, “I lose sleep at night on this. … It is social engineering. It just is—there’s no pretending like it’s not.” But he added that other groups, like Cambridge Analytica, are doing this kind of computational work, too. And various bad actors will do it without transparency or public accountability. “It’s going to be done. So not doing it is not the answer.” Instead, he and Wildman believe the answer is to do the work with transparency and simultaneously speak out about the ethical danger inherent in it.

“That’s why our work here is two-pronged: I’m operating as a modeler and as an ethicist,” Wildman said. “It’s the best I can do.”…

Artificial Intelligence Shows Why Atheism Is Unpopular“– and other tales from the trenches of social modeling– the learnings and the ethical questions they raise.

* Jaron Lanier


As we’re careful what we wish for, we might send elaborately-designed birthday greetings to a practitioner of another, older form of social engineering, Pierre Charles L’Enfant; he was born on this date in 1754.  A military and civil engineer, he became a city planner, most famously crafting the unique “radiant” layout for Washington, D.C.

210px-Pierre_Charles_L'Enfant source


Written by (Roughly) Daily

August 2, 2018 at 1:01 am

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