Article by Diane Coyle: “…But while some policymakers do have deep knowledge about AI, their expertise tends to be narrow, and most other decision-makers simply do not understand the issue well enough to craft sensible policies. Owing to this relatively low knowledge base and the inevitable asymmetry of information between regulators and regulated, policy responses to specific issues are likely to remain inadequate, heavily influenced by lobbying, or highly contested.
So, what is to be done? Perhaps the best option is to pursue more of a principles-based policy. This approach has already gained momentum in the context of issues like misinformation and trolling, where many experts and advocates believe that Big Tech companies should have a general duty of care (meaning a default orientation toward caution and harm reduction).
In some countries, similar principles already apply to news broadcasters, who are obligated to pursue accuracy and maintain impartiality. Although enforcement in these domains can be challenging, the upshot is that we do already have a legal basis for eliciting less socially damaging behavior from technology providers.
When it comes to competition and market dominance, telecoms regulation offers a serviceable model with its principle of interoperability. People with competing service providers can still call each other because telecom companies are all required to adhere to common technical standards and reciprocity agreements. The same is true of ATMs: you may incur a fee, but you can still withdraw cash from a machine at any bank.
In the case of digital platforms, a lack of interoperability has generally been established by design, as a means of locking in users and creating “moats.” This is why policy discussions about improving data access and ensuring access to predictable APIs have failed to make any progress. But there is no technical reason why some interoperability could not be engineered back in. After all, Big Tech companies do not seem to have much trouble integrating the new services that they acquire when they take over competitors.
In the case of LLMs, interoperability probably could not apply at the level of the models themselves, since not even their creators understand their inner workings. However, it can and should apply to interactions between LLMs and other services, such as cloud platforms…(More)”.