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ZorbaTHut  1yr ago (text post)   44922 thread views

Culture War Roundup for the week of September 5, 2022

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First volley in the AI culture war? The EU’s attempt to regulate open-source AI is counterproductive

The regulation of general-purpose AI (GPAI) is currently being debated by the European Union’s legislative bodies as they work on the Artificial Intelligence Act (AIA). One proposed change from the Council of the EU (the Council) would take the unusual, and harmful, step of regulating open-source GPAI. While intended to enable the safer use of these tools, the proposal would create legal liability for open-source GPAI models, undermining their development. This could further concentrate power over the future of AI in large technology companies and prevent research that is critical to the public’s understanding of AI.

The definition of "GPAI" is vague and unclear, but it may possibly differ from the commonly-understood usage of "AGI" and may include systems like GPT-3 and SD.

I will be very curious to see how much mainstream political traction these issues get in the coming years and what the left/right divide on the issue will look like.

The only clause about “open source” I found in EU reports, says that current regulations should apply irrespective of whether software is open source or not. Brookings doesn’t discuss details of regulations at all, but makes a bunch of empirical claims (I chose interesting):

  1. Open source GPAI (osai) promotes competition and erodes monopolies

  2. Regulation of osai would disincentivize its development by introducing liabilities and delays

1 Since osai has public good features, any breakthrough would be instantly adopted by everyone, but only big players have enough resources to continuously integrate and build off others’ breakthroughs. Some startups would be consumed altogether. If anything, releasing and adopting open source seems to profit monopolies more than anyone else. And curiously, Brookings admits this in their other article about benefits of osai:

At first glance, one might be inclined to think that open-source code enables more market competition, yet this is not clearly the case. […] In fact, for Google and Facebook, the open sourcing of their deep learning tools (Tensorflow and PyTorch, respectively), may have the exact opposite effect, further entrenching them in their already fortified positions

2 Most influential open source DL libraries like pytorch, tensorflow came from BigTech. And since almost every big company released its own library, it appears to be a common strategy – in a competition to entrench your own de-facto standard. Same about cloud infrastructure. Whether you like this status quo or not, it is monopolies who provide most services and tools at the moment.

Would regulation change this situation? Big players would certainly endure the bureaucratic costs, but many small but valuable innovators (esp nonprofits) might be effectively barred from releasing open source.

The document (pdf) mentions “AI regulatory sandboxes” as a measure to alleviate the burden of small entrants:

The objectives of the AI regulatory sandboxes should be to foster AI innovation by establishing a controlled experimentation and testing environment in the development and pre-marketing phase with a view to ensuring compliance […] including by removing barriers for small and medium enterprises (SMEs), including and start-ups.

Moreover, in order to ensure proportionality considering the very small size of some operators regarding costs of innovation, it is appropriate to exempt microenterprises from the most costly obligations, such as to establish a quality management system which would reduce the administrative burden and the costs for those enterprises

Would be interesting to see more substantial analysis of the regulations themselves.

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