Regulation
==regulation seen as dampening builders’ likelihood of releasing open models==
Regulation is a barrier against open model development, at times lobbied for by closed model builders to keep their edge. This is mostly because specific regulations like SB-1047 puts the burden of damages caused by users of open models to open model builders, which disincentivizes them to release them in a fashion that will not enable them to roll the model back in the future, or in other words, incentivizes centralized development. For reasons like this, people see regulation as a overly restrictive force.
- Closed model builders using regulation as a strategy to stifle open model development is the most dominant. (regulation_as_strategy, 18)
- Second is that developers of open models should not be responsible for damages caused by users (bad actors) of such models. (developer_user_misuse, 13)
- Regulation is overly restrictive is fourth, in that regulation of any kind against AI development is likely to disproportionately affect smaller players, most likely more open ones, in the field. (regulation_overly_restrictive, 9)
Regulation is often geographically bound, where AI regulation put forth in one country usually means that an open model provider will not release its models in that country. However, in the case of open model distributors like Hugging Face, the story can get a more complicated, as it is a global platform. Furthermore, it technically isn’t possible to fully regulate models being downloaded through other means like torrents, as it is with access to restricted sites using VPNs.
topic sentence has nothing to do with open source model
instead of explaining subthemes, each subtheme should be explained. as it stands now it is looking like paragraph is too short to capture the subsubthemes below
- Then, there is that regulation is location agnostic, as in one regulation in one country will not stifle development in another. (regulation_location_agnostic, 11)
- Another equally sized box is how some regulations can negatively affect model marketplaces like Hugging Face, which is a counterbalance against the sentiment that regulation is location agnostic. (regulation_affect_marketplaces, 5)
- Then there is openness as an advantage against regulation, as they get distributed in untrackable ways once released, and therefore become much harder to control from one centralized distributor. (open_regulation_advantage, 5)
- After that is how countries with heavy AI regulation is setting back their own companies in the AI race, giving clues to why the US and China is winning currently. is this just open models or closed models or both? (heavy_regulation_setback, 4)
However, at an individual level, unless the open model provider decides not to distribute to individuals at all, they are less likely to be negatively affected by regulation, as they often have much smaller risk of harm in the eyes of regulators compared to companies scaling them up.
nuances are being unpacked in each paragraph, so make that clear in the writing
use more quotes
- Similarly sized, there is interests of open model users being at odds with regulators, which is highly related to close model builders using regulation as a strategy to stifle open model development. (open_regulation_odds, 5)
- Last is that AI regulations are often not a concern for individual users but are for companies using them, as most of the time the regulation is directed towards companies making scaled effects onto the world via AI models. (regulation_not_concern, 3)
There is one subsubtheme showing that regulation is often well intentioned (regulation_well_intentioned, 11), and that slowing down development for risk management is ultimately best for everyone’s safety, even if it may mean slower model performance growth for open model users.