What scenarios could be used to assess risk scores centrally, but not decentrally?

[kaythxbye]

From the technical spec:

Although ROBERT is proposed as a ”proximity-tracing” protocol, ROBERT is actually a framework to assess the risk exposure of its users in order to fight pandemics. In our proposal, and as opposed to decentralized schemes, users do not get any information about the status of their contacts. In particular, they do not learn how many of their contacts are infected, nor which of them are. Instead, users get informed about their exposure level only upon the computation of a risk score by the server. The risk score may be based on proximity information, but also on other parameters that epidemiologists will define and adapt according to the evolution of the pandemic.

I would like to know which risk score assessment methodologies would rely on a central operator. Most risk assessments that rely on proximity, locality, or exposure through your job (e.g. in a hospital) can be processed far more efficient on the device itself. So which scenarios did you have in mind for this additional centralized risk assessment?

[ReichertL]

unless they want to do machine learning on the data, there is no real need for the algorithm to be centralized, I think

[beng-git]

My take is that the choice of a central computation, rather than a local computation stems from the trust assumption and not the risk function calculation.