The Edge home page featured an online editorial that downplayed AI art because it just combines images that already exist. If you look closely enough, human artwork is also combinations of things that already existed.

One example is Blackballed Totem Drawing: Roger 'The Rajah' Brown. James Pate drew this charcoal drawing in 2016. It was the Individual Artist Winner of the Governor's Award for the Arts. At the microscopic scale, this artwork is microscopic black particles embedded in a large sheet of paper. I doubt he made the paper he drew on, and the black particles were part of Pate's drawing utensils.

Zooming out, one can see depictions of Roger Brown shooting a basketball, like one would see on TV. This collage-style artwork, as the description beside says, depicts Roger Brown's story.

These are the pieces that came together to form an award-winning piece of art. Even though most human art is combinations of things that already exist, I still value it. I am also amazed at AI's image creation capabilities.

I like the mantra, "If we choose to give more effort today, then we are sure to go beyond our past mistakes." This mantra is on my desktop screen.

Hedonic Treadmill and the Economy

The hedonic treadmill is when permanent changes to living conditions lead to only temporary increases in happiness. This keeps us always wanting improvements to our lives. We often spend money on the newest Iphones and focus our attention on improving our external circumstances. We ignore the quote:

"What lies before us and what lies behind us are tiny matters compared to what lies within us" 

Some people eat chips to quell their boredom. The hedonic treadmill ensures that, despite improvements in income, people are not satisfied. I was surprised by how much the hedonic treadmill dovetails with profit maximization. If they maximized profit, I suspect companies would pay Big Pharma billions not to release drugs that improve the hedonic set point. The antidepressant drugs Big Pharma releases act as mood flatteners, according to https://www.hedweb.com/. 

I have an idea for a possible utility function combination method. It basically normalizes based on how much utility is at stake in a random dictatorship. The combined utility function has these nice properties:

Pareto-optimality wrt all input utilities on all lotteries

Adding Pareto-dominated options (threats) does not change players' utilities

Invariance to utility scaling

Invariance to cloning every utility function

Threat resistance

The combination method goes like this:

X=list of utility functions to combine

dist(U)=worlds where random utility function is argmaxed with ties broken to argmax U

Step 1: For each U in X, U=U-expect(argmax U)

Step 2: For each U in X,

U=-U/U(null universe) if (expected value of U on dist(U))==0

U=-U/(expected value of U on dist(U)) otherwise

Step 3: U(final)=sum(U in X)

I designed this to be a CEV of voting utility maximizers, but the combination has multiple discontinuities. It does not need transferrable utility like the ROSE values, but it does not have nearly have as many nice properties as the ROSE values.

For the examples in this article, for each option only take the monetary value that goes last. log(amount after year)~0.79*log(amount now)+0.79 is the indifference curve. If U(now)=log(amount now), U(year)=(log(amount after year)-0.79)/0.79.

There is a hypothetical example of simulating a ridiculous number of humans typing text and seeing what fraction of those people that type out the current text type out each next token. In the limit, this approaches the best possible text predictor. This would simulate a lot of consciousness.

What if most people would develop superhuman intelligences in their brains without school but, because they have to write essays in school, these superhuman intelligences become aligned with writing essays fast? And no doomsday scenario has happened because they mostly cancel out each others' attempted manipulations and they couldn't program nanobots with their complicated utility functions. ChatGPT writes faster than us and has 20B parameters where humans have 100T parameters, but our neural activations are more noisy than floating-point arithmetic.