Inevitable enshittification

Ed Zitron goes on a well written rant

The people running the majority of internet services have used a combination of monopolies and a cartel-like commitment to growth-at-all-costs thinking to make war with the user, turning the customer into something between a lab rat and an unpaid intern, with the goal to juice as much value from the interaction as possible. To be clear, tech has always had an avaricious streak, and it would be naive to suggest otherwise, but this moment feels different. I’m stunned by the extremes tech companies are going to extract value from customers, but also by the insidious way they’ve gradually degraded their products. 

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we are in the midst of the largest-scale ecological disaster of our time, because almost every single interaction with technology, which is required to live in modern society, has become actively adversarial to the user. These issues hit everything we do, all the time, a constant onslaught of interference, and I believe it’s so much bigger than just social media and algorithms — though they’re a big part of it, of course. 

In plain terms, everybody is being fucked with constantly in tiny little ways by most apps and services, and I believe that billions of people being fucked with at once in all of these ways has profound psychological and social consequences that we’re not meaningfully discussing. 

The average person’s experience with technology is one so aggressive and violative that I believe it leaves billions of people with a consistent low-grade trauma. We seem, as a society, capable of understanding that social media can hurt us, unsettle us, or make us feel crazed and angry, but I think it’s time to accept that the rest of the tech ecosystem undermines our wellbeing in an equally-insidious way. And most people don’t know it’s happening, because everybody has accepted deeply shitty conditions for the last ten years.

Trump might really be a fascist

Listen to what he says

I am not asking if the Republican Party is fascist (I think, broadly speaking, it isn’t) and certainly not if you are fascist (I certainly hope not). But I want to employ the concept of fascism as an ideology with more precision than its normal use (‘thing I don’t like’) and in that context ask if Donald Trump fits the definition of a fascist based on his own statements and if so, what does that mean. And I want to do it in a long-form context where we can get beyond slogans or tweet-length arguments and into some detail.

AI bullshit

Large Language Models are bullshitters

in the technical sense of the word 

bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. 

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false statements by ChatGPT and other large language models are described as “hallucinations”, which give policymakers and the public the idea that these systems are misrepresenting the world, and describing what they “see”. We argue that this is an inapt metaphor which will misinform the public, policymakers, and other interested parties.

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their primary goal, insofar as they have one, is to produce human-like text. They do so by estimating the likelihood that a particular word will appear next, given the text that has come before.

The machine does this by constructing a massive statistical model, one which is based on large amounts of text, mostly taken from the internet. This is done with relatively little input from human researchers or the designers of the system; rather, the model is designed by constructing a large number of nodes, which act as probability functions for a word to appear in a text given its context and the text that has come before it. Rather than putting in these probability functions by hand, researchers feed the system large amounts of text and train it by having it make next-word predictions about this training data. They then give it positive or negative feedback depending on whether it predicts correctly. Given enough text, the machine can construct a statistical model giving the likelihood of the next word in a block of text all by itself.

This model associates with each word a vector which locates it in a high-dimensional abstract space, near other words that occur in similar contexts and far from those which don’t. When producing text, it looks at the previous string of words and constructs a different vector, locating the word’s surroundings – its context – near those that occur in the context of similar words. We can think of these heuristically as representing the meaning of the word and the content of its context. But because these spaces are constructed using machine learning by repeated statistical analysis of large amounts of text, we can’t know what sorts of similarity are represented by the dimensions of this high-dimensional vector space. Hence we do not know how similar they are to what we think of as meaning or context. The model then takes these two vectors and produces a set of likelihoods for the next word; it selects and places one of the more likely ones—though not always the most likely. Allowing the model to choose randomly amongst the more likely words produces more creative and human-like text; the parameter which controls this is called the ‘temperature’ of the model and increasing the model’s temperature makes it both seem more creative and more likely to produce falsehoods. The system then repeats the process until it has a recognizable, complete-looking response to whatever prompt it has been given.

Learning economics

Old orthodox economics has proven to fail to describe the real world.

Core-econ is teaching theory that fits empirical data 

The Economy 2.0 is a complete introduction to economics and the economy. It's student-centred and motivated by real-world problems and real-world data. 

Climate news is bleak

So, 

how doomed are we?

The global increase in temperature is the simplest and most predictable dimension of climate change. It is also the one that scares me the most, partly because the direction of change is so certain and partly because heat is such a persistent and widespread hazard. For the large proportion of the world where it’s already hot during some or all of the year, just a couple of degrees of warming will cause great societal harm. In places with cooler climates, such as much of Europe, severe heatwaves can sometimes be even more deadly, because people there are less accustomed to heat1.

Geoengineering to mitigate climate change

Models suggest that it’s feasible to inject SO2 at 20km high

And reduce warming sufficiently to let us decarbonize at the current rate 

Why is there no trust?

Kyla Scanlon  has a great essay.

We live with the expectation that words mean very little, because we have seen it all before, heard it all before.

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“The fastest growing sector of the culture economy is distraction… But it’s not art or entertainment, just ceaseless activity” as Ted Goia described it.