Love this. What's your process for collecting this info? - was it all manual research and user submissions?
8 karma · joined March 21, 2022
I know you're probably being exaggerative in this statement but to add some clarity: COVID proved that most people's jobs are pointless (more or less), however, there's maybe like 10-15% of the workforce that if they didn't work, everything would come crumbling down and society would fall apart. Examples we saw during COVID: Medical staff (nurses, doctors, EMTs), truck drivers, train operators, agricultural workers, electricians & energy workers at power plants, waste management workers, construction workers, various retail employees (grocery store, pharmacies).
As to your point, humans with copious free time leads to civil unrest - so the fact that 80+% of people's jobs aren't critical to the functioning of the country is quite concerning - especially now with the recent advances in AI. Another concerning thing is that countries with high unemployment rates (20%+) typically have revolutions or similar. We've also never seen what 80% unemployment (or even 50%) looks like in a country not during a time of war or during a natural disaster. During those times extreme unemployment rates are seen as temporary by the population, whereas, with unemployment caused by AI - it won't be viewed as temporary so I think it'll spark a revolution pretty quickly because people won't see a light at the end of the tunnel and immediately call for change.
I never made the argument that it's the imputed ideal. Rather, my point is that in the context of a social platform, having an option for an algorithmic feed leads to other people with opposing views to discover the content and have dialogue about it/contest that viewpoint. Otherwise, it's a closed loop system that contains only like-minded viewpoints that can lead to an echo chamber. How do we prevent echo chambers from forming? Well, the most straightforward option is to introduce opposing viewpoints. How do we introduce opposing viewpoints? Well the people with opposing viewpoints need to be able to discover the content - so it needs to be shown to them somehow. The best way to do that (right now at least) is through an algorithmic recommendation engine.
> Is there any evidence that this is true or should be an expectation? Is that really why billions of dollars are spent on this space?
That's why I said "ideally". There's huge differences in algorithms for all the major social platforms. Algorithms can easily be used to make echo chambers worse, but algorithms can also be used to reduce echo chambers on a platform. To your point, that's why billions of dollars are spent on this because it's a complicated problem. One thing is a fact though, dissenting opinions create engagement and keeps people on the platform. If you responded to my comment and said "I agree with you", I wouldn't be commenting here right now and back on Hackernews. Most social platforms take advantage of this feature of our human psyche to get people to stay on the platform to then show them more ads and drive more ad revenue. That's why engagement is such a critical factor in social media algorithms and also has the unintended consequence of promoting controversial content - because it receives the most engagement. Which goes back to the need of having an algorithm that can balance reducing echo chambers by showing the content to others with dissenting opinions without unintentionally promoting only the most controversial content because it has the highest engagement. There's really no easy answer to this and again, that's why they spend billions like you said.
According to this research study, these are the two main ingredients: 1) Homophily in the interaction networks 2) Bias in the information diffusion toward like-minded peers https://www.pnas.org/doi/10.1073/pnas.2023301118
Substack Notes is their way to venture into the social platform realm, which differs from the personal email inbox model, which isn't a social platform. With that in mind, for ingredient #1: people can only see notes from people they follow. People will overwhelmingly only follow people that align with their ideas/political leanings/beliefs. This creates the homophily in interaction networks. For #2, users can easily share biased information to their like-minded peers without pushback/opposing views since their social network is comprised of people with the same viewpoints.
To be clear, algorithms can definitely create echo chambers as well but ideally an algorithm based feed will promote discourse and dialogue about ideas.
An anecdote: I follow quite a few people on TikTok that post about housing policy in NYC. TikTok's algorithm exposes these videos to people with varying viewpoints, which creates a ton of dialogue on proposed solutions and pushback on ideas that could potentially harm certain demographics/historical areas, etc. This pushback is very important but is only possible when there is a chance for those with opposing views to discover it, which means there needs to be an algorithmic recommendation feature.
If TikTok had no FYP and instead people could only watch videos from people they follow, this would create a closed loop system and those opposing views for housing policy would not be nearly as prevalent.
As an aside, Notion would completely disrupt the flashcard app space (Quizlet, etc) if it had a feature to create flashcards from a Notion database with spaced repetition. I really don't think it would be that difficult for them to implement that feature. Hopefully they will soon.
I just created my first song using automatic real-time pure intonation and uploaded it yesterday[0]. I used a plugin called Scale Breaker[1] that connects to MPE instruments in Ableton (used Wavetable for all the synths in the song since it's MPE enabled) and set the tuning to automatic Just Intonation (12T) with 5-limit symmetric aug 5th tuning. I edited all the bass notes to trigger the correct tuning for each chord so each note is automatically microtuned to be perfectly resonant.
I make House music and noticed that not many people have been experimenting using real-time just intonation in the genre so I gave it a go to see what it sounds like - it was pretty fun to make. I believe perfectly resonant music is going to be really big in the next few years now that these automatic tuning plugins are available.
Question: does your plugin work through modulating the notes using MPE? My understanding is that this method allows for more versatility.
[0]: https://open.spotify.com/track/73r7izAfNtiG20vzoN8mCz?si=104... [1]: https://isotonikstudios.com/product/scale-breaker/
How did you go about finding the ~3000 forums? That's my main hurdle with the idea.