#algorithmic decision making

[atmosphericradar]

"The point of all of this [private equity] maneuvering is decreasingly about turning a profit and increasingly about transitioning to a rent-based economy that hedges inflation."

"The reason that so many cloud-based companies are dumping so much money and resources into pushing [AI chatbots] on everyone is to capture the part of our routine that comparison-shops, or researches, or asks for advice, or arrives at a logical conclusion about something.

If you become friends with ChatGPT or Gemini or Rufus or Siri, and you consult with their vast informational resources on a more personal and casual level, you're not only supplying with the purest form of sentiment analysis, but you're helping them build a system that will further control not only your decisions on what to buy or subscribe to, but what hobby you'll take up next summer."

"...and it's worth pointing out that the primary owner of [the US government's debt] isn't China or Japan or even our own Federal Reserve, it's US investors. As this cycle continues to snowball, money will be less and less valuable, not only because of inflation, but in principal. When the government is so closely entangled with the people who have benefitted the most from this mass extraction of wealth from the capitalist economy, it stops making sense to think of wealth as money."

"To graduate - or transcend - from those unfathomable limits of what money's wealth can get you, you need to control the power of information so that you can manipulate the world that you live in. And I beleive that is exactly what's happening, and unfortunately I think it's going to get worse before it gets better."

~ quotes from You Are Witnessing the Death of American Capitalism, by Benn Jordan

[atmosphericradar]

AI Leader Proposes a New Kind of Turing Test for Chatbots

A new book floats a provocative idea for testing whether machines are capable of human-like intelligence. But first…

This is a very revealing moment for how the modern AI community is thinking:

The question now is whether passing the Turing test even matters anymore. “It’s totally unclear whether this is a meaningful milestone or not,” said Mustafa Suleyman, a founder of DeepMind, now a division of Google, and the founder of Inflection.Ai, a startup making personal AI assistants. “It doesn’t tell us anything about what the system can do or understand, anything about whether it has established complex inner monologues or can engage in planning over abstract time horizons, which is key to human intelligence.”

This is both fair criticism of the Turing Test, and nothing new. Turing himself didn't think his experiment was a good judge of intelligence, either. Where is Suleyman going with this?

Suleyman argues that there’s a misplaced focus in the tech industry on the distant possibility of achieving Artificial General Intelligence, or AGI: algorithms with cognitive abilities that match or exceed humans’. Instead, he said the more achievable and meaningful short-term goal is what he calls Artificial Capable Intelligence, or ACI: programs that can set goals and achieve complex tasks with minimal human intervention.

To measure whether a machine has [become an] ACI, he describes a “modern Turing test” — a new north star for researchers — in which you give an AI $100,000 and see if it can turn the seed investment into $1 million. To do so, the bot must research an e-commerce business opportunity, generate blueprints for a product, find a manufacturer on a site like Alibaba and then sell the item (complete with a written listing description) on Amazon or Walmart.com.

This major C-suiter in the field of AI just said that the best test of a being's intelligence is exploiting business opportunities.

Obviously the final goal for all of the present-day investment into AI is to generate a financial return. It's no surprise that businesses would salivate over AI that can independently come up with, market, and sell new products all on their own.

But think about what that intelligence test says about the mindset of the big-wigs in AI right now! If the true test of human-like intelligence is being able to turn a 10x profit, what does that say about humans who don't (or can't) make tons of money? If your parents came to you one day and said: "we honestly think you're sub-human because you don't make enough money for how much money went into raising you", that would be prestige-drama-villain behavior.

Rich people think that they are smarter and better than everyone else. It's no surprise that, on a philosophical level, investment-capitalist tech bros will idolize (and seek to re-create) technological investment-capitalism.

I have my own thought experiment: I wonder how many of these Fintech C-suiters has rich parents that gave them huge loans or high-paying jobs right out of school, and I wonder how that affected them later in life...

[manmishra]

📢 WAR BY ALGORITHM! 🤖 AI is now controlling drones & cyber attacks 💣 Lethal autonomous weapons are real 🛰️ Robots & machines making battlefield decisions ⚔️ Human soldiers are being replaced 📡 War is becoming data-driven & unpredictable 🔍 Are we still in control—or is AI? 👉 Read how AI is rewriting the rules of combat #AIWarfare #MilitaryAI #FutureOfWar #AutonomousWeapons

War by Algorithm: 7 Alarming Ways AI Is Rewriting the Rules of Combat

[cheshirecat-rabbit]

An automated policing program got this man shot twice

The Chicago PD made a “heat list” to predict people involved with violent crimes — and instead, it caused them.

The algorithm indicated Robert McDaniel was more likely than 99.9 percent of Chicago’s population to either be shot or to have a shooting connected to him. That made him dangerous, and top brass at the Chicago PD knew it. So McDaniel had better be on his best behavior.

The idea that a series of calculations could predict that he would soon shoot someone, or be shot, seemed outlandish. At the time, McDaniel didn’t know how to take the news.

But the visit set a series of gears in motion. This Kafka-esque policing nightmare — a circumstance in which police identified a man to be surveilled based on a purely theoretical danger — would seem to cause the thing it predicted, in a deranged feat of self-fulfilling prophecy.

McDaniel had no violent history — no reason, as far as he was concerned, that any police officer should randomly show up to his house and declare him a threat.

If individuals are arrested under suspicion of potentially committing a crime, there is no “innocent until proven guilty”; there’s a supposition of guilt. Plus, there’s just so much uncertainty in the technology: What if the data is wrong?

Unbeknownst to McDaniel, he was a sort of guinea pig, one of the first individuals to be put on Chicago’s “heat list.”

Police started hanging around the bodega where he worked, looking for opportunities to go after him, often questioning his managers about his activities and whereabouts.

McDaniel found himself in a kind of worst-case scenario: police were distrustful of him because of the heat list, while his neighbors and friends were distrustful of him because they assumed he was cooperating with law enforcement — no amount of assurances would convince them he wasn’t.

McDaniel became isolated. Friends stopped talking to him.

“I’m just trying to get my name off this heat list shit, I don’t even know how I got on there.” 

Reporters and community organizations criticized the lack of transparency about which factors placed an individual on the list. Researchers questioned its efficacy. And civil rights groups wondered how damaging someone’s inclusion on the list might be to their record.

LAPD brass ended its person-based predictive policing program in April 2020. Though the CPD still uses place-based predictive policing algorithms, Chicago’s heat list program ended in 2019. 

The heat list may have been designed to reduce violence, but for McDaniel, he says it brought violence directly to him. It got him all the negative ramifications of being an informant — a snitch — with none of the benefits.

He can’t trust anyone. Nowhere’s safe. Everyone’s a potential threat.

“I got this target on my back,” he says.

And there’s no way to remove it.

[cheshirecat-rabbit]

How the LAPD and Palantir Use Data to Justify Racist Policing

In a new book, a sociologist who spent months embedded with the LAPD details how data-driven policing techwashes bias.

The LAPD ended its contract with PredPol last April, citing financial constraints brought on by the pandemic. Operation LASER ended in 2019. But a range of other companies, including heavyweights like Amazon and Microsoft, have moved into the space nationally, and a guidebook published by the LAPD last year makes clear that big data will continue to prominently figure in policing in Los Angeles. Palantir, meanwhile, has lately expanded its access to data by moving into coronavirus tracking and vaccine safety analysis. Last year, the company brokered lucrative contracts with the National Institutes of Health and the Food and Drug Administration. It went public in September. Since then, its stock prices have more than tripled.

[caressyouintodarkness]

One possibility for addressing the politics of machines is to work through a philosophy of another kind, starting not only from the unthought of thinking, but also from the inhumanness of instrumentality, an awareness of alienness within reasoning that could be the starting point for envisioning a techno-philosophy, the reprogramming of thinking through and with machines. If the antagonism between automation and philosophy is predicated on the instrumental use of thinking, techno-philosophy should instead suggest not an opposition, but a parallel articulation of philosophies of machines contributing to the reinvention of worlds, truths, and facts that exist and can change.

Reprogramming Decisionism by Luciana Parisi