Fediverse

I would use it in a heartbeat, that would be fantastic.

I don't know if you read the entire transcript, but I bolded what I think you might want to see:

There’s a real tail wagging the dog element of this where you can want to have a different media diet. I have set up RSS readers many times in the past two years. I used to read all of my news in RSS. I used to sit in school, my laptop open, and not pay attention, and go through my RSS reader, and I remember saying to some of my friends, “I finished the internet today,” because I’d read everything in the RSS reader, and there was a great diversity in content. No one thinks that way anymore. You open an RSS reader, you plug your favorite websites into it — candidly, even ours — and you get a bunch of stuff, and some of that stuff is obviously made for SEO, and some of that stuff is obviously made for other platforms.

And very rarely do you see, “Oh, there’s an audience here that wants to read every article on this website, and that is a package,” but it’s coming back. People want to do that, right? You can see… You have felt that way. I have felt that way. We write articles about RSS readers, and people read them. There’s demand for it. Do you think that demand is ever going to get filled?

I hope so. I tend to think, “Wasn’t the great promise of Silicon Valley and all these tech startups [that] we are going to give users things that they want?” There’s this thirst for a new form of delivery of content, better curation, more holistic ideas of what we should consume, and I hope that products arise to give us that. I think people are restlessly questing for it right now in RSS, in newsletters, in a parasocial podcast video, whatever ecosystem. But I don’t know. I like internet technology, I like when startups do new stuff. I hope that they take on this challenge and figure it out.

Okay, thanks for the suggestion but I'm kind of clueless when using github for things. It looks like it does what I want, but how would I implement this?

I think we're in it, the fediverse ran by instances that are more interested in fostering community than making a buck. There is a need and want for new ways to access the internet, the fediverse is one way that it's being provided. I'm not sure we're ever going to attract the internet tourists, but that's probably a good thing. This is where you go to get away from that.

Again, more complicated.

It doesn't have to be.

Are the algorithms mathematically sound, or just AI/machine learning magic fairy dust?

MAB algorithms lie in middle. They are a mathematically sound way to explore the unknown and make reasonable decisions given whatever context is available.

There have been a few hospital trials with success, but progress is slow and funding is low. There are a few really interesting papers if you are interested to read more.

Do the algorithms have implicit biases against poor people, or those with darker skin or who live in certain postcodes?

In a sense, it's not different than laws that discriminate against people of color or other marginalized communities. The fact that a bunch of super privileged lawmakers create laws that disproportionately harm us, does not mean that the concept of law is flawed.

You got to ask yourself why the algorithm was given that information in the first place, and more importantly who gave it?

What we call algorithm, is actually two things. A set of instructions (the actual algorithm) and a set of parameters. The instructions explain how to use those parameters in order to make a decision. The parameters may or may not be biased, it all depends on the process that is used to generate those parameters.

AI in particular uses a process called training, in which people make decisions, and another algorithm is used to adjust the parameters so those decisions can be genralized and repeated by the AI. When, biased people make biased decisions, they are going to train an AI to make biased decisions.

Unfortunately, that's our reality, biased people make biased decisions, as a result we have biased laws and biased algorithms.

By the way, this is what the author calls algorithm cleanse, and it's bureaucracy supercharged. Why hire someone to reject applicants of color when you can build an algorithm to do that? Making a legal case against that is much harder, and the legal system isn't ready to understand the nuisances of the case.

However, in contrast to the laws, we marginalized people can create our own "algorithms", thay are not biased to our best effort. The fediverse is living proof of this. Why fight the system when we can make our own?