Just exemplifying this:
Different countries use different testing strategies and thus have
different amounts of new infected persons just based on this difference
already (e.g. a country that does never more than 500 tests a day will
not have more than 500 new infections per day)
Different countries score the deaths related to COVID-19 different. Some
countries record all patients dying that have the virus, while others
only count the death if it is caused by the virus. (don't ask me how
this is exactly done).
It is clear from these simple and empirical facts that the data from
different countries cannot easily be compared anymore. So, even taking
"raw" data is not as objective as people tend to believe.
Cheers,
Frank.
On 2020-03-23 14:11, Jiaqi Ge wrote:
> Dear Colleagues,
> Thanks for the fascinating discussion. Just want to add that, if the data on which the model is validated are hugely wrong (e.g. hugely under-estimated in some countries for political reasons), then using a 'highly empirical' model to inform policy will be very dangerous. Nobody would take the results of a toy model literally, but these seemingly empirical model will give us the delusion of accuracy or the 'Pretense-of-Knowledge' (https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.24.4.85), because it is based on some data and produce some numerical predictions.
> Jiaqi Ge
>
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Med vänlig hälsning/Best regards,
Frank Dignum *
Professor Socially Aware AI *
Department of Computer Science *
Umeå University *
Sverige * Knowledge is only one point,
e-mail: [log in to unmask] * the ignorant have multiplied it
telephone: +46-90-7869101 *
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