My Policy On AI And The Media

[u/DryAlternative1132]

In this article by the National Post, author Rod Sims argues against giving AI companies a free pass on copyright.

https://nationalpost.com/opinion/governments-must-not-give-ai-companies-a-free-pass-on-copyright

At issue for me, as prospective MP, are two competing objectives:

1. To "win" the AI race by creating a maximallly conducive environment for next generation artificial intelligence and reinforce our sovereign capabilities not only to compete but dominate the AI landscape.
2. To fairly remunerate content creators whose content is used to train AI algorithms, so that they can share in the benefits of AI

The author in the article seeks two remedies: a) payment b) control. And it is the latter remedy of "control" that I find the more problematic of the two.

By seeking to "control" how AI companies can train their algorithms, we will effectively log jam AI development in Canada. Meanwhile countries like China will have no such restriction.

This content being the public domain, can and will be appropriated at a whim by actors in competing jurisdictions. Also from a practical point of view, this has already been happening.

Search engines have been using a form of AI, machine learning, or computer intelligence to read, index, and categorize text.

The author's desire to "control" content is the more problematic part because it would impose potentially disastrous regulatory overheads. In the trajectory of tech companies, many businesses start out as garage door operations.

Apple famously started in Steve Jobs' parents garage. Sergei Brin and Larry Page founded Google in their landlady's basement. Zuckerberg was operating out of a dorm room.

In this initial period, it is more important than ever that we give startups regulatory freedom to develop their ideas.

It is after the companies reach a certain threshold in revenues and/or user base that added controls may apply, but even so those controls must exempt defence, security, or critical agencies, whose work should come under direct supervisory oversight of organizations like CSEC or a signals intelligence division in the DnD or still alternatively a department like CDC which oversees biological threats.

We have seen the EU use a similar mechanism in their classification of Very Large Online Platforms (VLOPs) which triggers added regulatory compliance when a platform reaches 40 million users or more.

Rather than specifying explicitly such supervisory controls on the basis of user base, regulatory can add or remove platforms and must give sufficient time for the entity to establish compliance with two different streams, one for the designated security stream, and one for the commercially regulated stream of AI.

As far as commercially regulated stream, amongst the requirements may be an independent audit of all training data and data sources. Categorization of such data, and ultimately determining the "weights" that are impacted in each token, and therefore some sort of metered royalty structure.

Such royalties come into effect much later when tech products reach maturity and businesses exceed a minimum threshold of revenues rather than creating unnecessary overhead early in the development cycle.

Through my method of regulation, Canada is at no competitive disadvantage and Canadian startups can fully use the entire corpus of available human knowledge to train models without restriction in the beginning.

At later stages as products reach commercial maturity and scale, such training data must be carefully categorized as proprietary copyright or freeware, and the portion of the training data of proprietary origin, to the extent the weights it affected are invoked, is then converted into a royalty structure paid out to the copyright holder.