freshtake
Joined 2 years ago
Joined 2 years ago
The best example of this is heroin, which has both a severe physical and mental addiction component, and it's the mental addiction that makes relapse so common.
Mental addictions rewire the brain's chemistry, causing the user to seek and only find joy in the substance. This is a better comparison for social media (albeit not as destructive and instantaneously harmful as narcotics)
I agree that a big part of this is educating children about these hazards, but that also doesn't mean we should allow these companies to data science the shit out of our attention and will power. Many adults have concerning relationships with social media too -- exposure, pressure, and manipulation are key ingredients that are difficult for anyone to deal with.
Personal responsibility IS important, but we also don't allow cigarette companies to advertise on billboards with cute characters (remember Joe Camel?)
YouTube allows you to "show fewer shorts" but what if you don't want them popping up at all?
AI Slop is the best thing to happen to these platforms - because it will lower trust and engagement as people (hopefully) become tired of inauthenticity. Rage bait is potent when the event in the video _actually_ happened, but when you realize it was AI generated, the manipulation feels even more obvious (though it was always there).
These platforms should also allow users to understand how the algorithm has categorized them, and be able to configure it. YouTube, Instagram, et al. would be safer places for viewers if they allowed users to tell them what they want to be exposed to, and what they don't. Big tech is dodgy about this currently, because the more control the user has the lower the engagement (good for the user, bad for profit).
This is the most important part of the article. Key takeaway.
Some questions:
[Tech]
1. How deep does the modification go? If I request a tweek to the YouTube homepage, do I need to re-specify or reload the tweek to have it persist across the entire site (deeply nested pages, iframes, etc.)
2. What is your test and eval setup? How confident are you that the model is performing the requested change without being overly aggressive and eliminating important content?
3. What is your upkeep strategy? How will you ensure that your system continues to WAI after site owners update their content in potentially adversarial ways? In my experience LLMs do a fairly poor job at website understanding when the original author is intentionally trying to mess with the model, or has overly complex CSS and JS.
4. Can I prompt changes that I want to see globally applied across all sites (or a category of sites)? For example, I may want a persistent toolbar for quick actions across all pages -- essentially becoming a generic extension builder.
[Privacy]
5. Where and how are results being cached? For example, if I apply tweeks to a banking website, what content is being scraped and sent to an LLM? When I reload a site, is content being pulled purely from a local cache on my machine?
[Business]
6. Is this (or will it be) open source? IMO a large component of empowering the user against enshittification is open source. As compute commoditizes it will likely be open source that is the best hope for protection against the overlords.
7. What is your revenue model? If your product essentially wrestles control from site owners and reduces their optionality for revenue, your arbitrage is likely to be equal or less than the sum of site owners' loss (a potentially massive amount to be sure). It's unclear to me how you'd capture this value though, if open source.
8. Interested in the cost and latency. If this essentially requires an LLM call for every website I visit, this will start to add up. Also curious if this means that my cost will scale with the efficiency of the sites I visit (i.e. do my costs scale with the size of the site's content).
Very cool.
Cheers
Can we also get the ability to filter by seller entity country of origin?
Amazon also needs to offer far better tools for buyers to effectively find and attach to brands.
I think the main thing the readme is missing is the core benefits. Reducing LOC and dependencies is cool, but it would be great to understand if this provides some additional benefits like lower latency or memory requirements.