1/15 I visited a physical bookstore after a long time yesterday, and had this revelation about knowledge distribution.
2/15: Knowledge on the internet is like a free market. Platforms serve you what they think you want (e.g. Netflix, Youtube, Instagram).
3/15: Knowledge before was a highly regulated market - you needed authority figures (publishers) to vouch for the quality of your work before it could be available on shelves. Still a market though, because more popular books would get more shelf space.
4/15: A complete free market has the obvious advantage that there's less gaps in the market - content is fresher, and appeals to very niche demographics...
But at the obvious cost of quality. Content that is vile, inappropriate, hateful, etc do exist.
5/15: Trying to establish partial regulation online is tricky because (1) regulation in many ways is not automatic enough to scale (besides porn filters, etc) (2) users have transparency so they complain when they disagree with regulation (YT takedowns, etc)
6/15: But even today, people are more likely to trust a book than something they read online. With deregulation, you lose that trust (fake news).
7/15: Doing regulation at scale is a tricky problem from a Machine Learning perspective. A high precision (high trust) solution impedes on free speech (low recall), creating a quality vs free speech tradeoff.
8/15: Another key aspect is about what content gets exposure (ranking) over just what content is allowed (regulation). Products often optimize on engagement vs expert regulation. An algorithm might put a listicle on the front page but an editor wouldn't.
9/15: A news editor cares about his expertise and his responsibility to the reader, regardless of what the user wants. He supplies what the user *needs*, not what they *want*.
10/15: However, in capitalism, that's fighting a losing battle. Capitalism rewards wants, not needs. More views is (usually) more money, not societal impact. How do we contend with that?
11/15: I think there are ways to tackle this problem with technology. Can we train on data only from an exclusive subset of the population whose opinions we trust?
Can we move to a subscription model to not have to rely on viewership numbers?
12/15: Non-tech heavy solutions that work already exist: Reddit and Wikipedia both have trusted "moderators" who regulate content quality cheaply and scalably very well. Maybe we can empower those moderators to be the editor and decide which posts/pages they recommend.
13/15: Another unintuitive idea: cap the amount of content like a newspaper. If users know they only get access to a select few high quality things, maybe they'll value quality over quantity, and retention will be higher (?)
14/15: The physical bookstore visit reminded me that there's so much fascinating content I'd never look up organically. But because of the way bookstores are organized, I got to delve into old South Indian folklore to graphic novels about capitalism.
15/15: That made me think - very rarely do I discover such niche timeless high quality content online, and maybe there are opportunities to change that!
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I want to dispel certain accusations made about my EB-1 blog on X.
I wrote that to help people. To not gate-keep knowledge. It's not great to be punished for that. The primary reason I write online is to help.
I'll break down the claims and why they're patently false:
1/8
On low quality science journals.
1 I did not use them, you can check Scholar.
2 These were recommended in the onboarding email of one of the biggest immi law firms that I used at first who have done 1000s of EB-1s.
I don't recommend it, but people have the right to know.
2/8
On publishing trade articles pt1
My language in the blog insinuated that Trade Press Services writes papers for you.
They DON'T.
They interview you, draft an article that you edit, and find trade publications who run it. Been around 30+yrs, with corp clients too.
I've spent the past 13yrs in the US afraid of being fired, anxious about travel paperwork, and not knowing if I'd spend New Years with family. Takes 100+yrs for India-borns unless you do an EB-1A.
Things immigrants go through:
1/8
You can't study what you want.
A close friend, a star mechanical engineer, learnt by soph year that most of the jobs he wanted didn't hire intls — Lockheed, Boeing, SpaceX. At his lowest point, he almost switched to CS. He ended up powering through a top PhD to get a job.
2/8
You can't always work in a field you didn't study.
A friend who was a chemical engineer ended up getting up a job as a consultant in NYC. When she applied for an H-1B, she was told her job doesn't require her major and had to leave.
3/8
When I write about leaving India, many say I'm biased. Let's look at data.
Every year, ~2.5M Indians move abroad.
Indians are the largest overseas diaspora with 30M+ people. In comparison, ~30M in India make 10LPA ($12k/yr). People who leave far outnumber those who return!
1/7
The topic of moving to and from India is so prone to narrative building on both sides..
Indians overseas feel patriotic and say "I want to move back" without doing so. Indians in India for 30yrs have said "India's future is now, why leave?" and cherrypick flaws abroad.
2/7
I've moved back and forth to India a few times and many in my circle debate this. There are plenty of good reasons to do both, but let's not lie about the data.
The numbers are scant on reverse migration, but most estimates show <10%. For every 10 that leave, 1 comes back.
3/7