The Importance of Open Recommender Systems
Just like the food pyramid has served as a heuristic to help people plan what they eat, we could suggest an information diet (or several) for people as a default and then let them modify it as they wish.
An example (not necessarily a good diet):
- (~50%) Content from Hacker News and your reddit feed (the HN/Reddit algorithm decides)
- (~20%) The posts of your closest friends
- (~10%) The posts of your 2nd degree closest friends (friends of friends)
- (~10%) Content from r/all on Reddit (minimal filters)
- (~5%) Low-scoring content (could be controversial, low quality or recently posted)
- (~5%) Let the Facebook algorithm decide
Why don't we create a personalized recommendation system for each person - based on one's own values? It could be great:
- opportunity cost could be taken into account in a strong sense and life would be better
- signal-to-noise is taxing problem on most platforms - fluff could be ranked down
- we could be freed from the shackles of attention economy's driven algorithms (to an extent)
I am tempted to apply some LLM to determine a ranking and importance like with news minimalist (it works really well), but there would definitely have to be hard rules, for example:
- anything from Karpathy should get a high priority
- any blog post from Bartosz should be at the top and once the heuristics are in place, the tie breaking can be done with some LLM perhaps.
- ...
A neat UI where people could add their sources and scoring rules would be fantastic.