"1 in 20 Post-80s die" is a rumor, and the culprit may be AI.

February 18, 2011 - According to the "Shanghai Network Disinformation" public number today, the recent news about the "Shanghai Network Disinformation" is a new one.One out of every 20 post-80s people dies." has been circulating on the Internet, and this information isrumorThe culprit could be AI.

"1 in 20 Post-80s die" is a rumor, and the culprit may be AI.

The report mentions that most of the articles in question claimed that their data came from the"Authoritative data" from the Seventh CensusHowever, the information contained therein is full of holes, to which Li Ting, a professor at Renmin University of China, has also refuted in an article.

She suggested that there are theoretically two options for calculating mortality through censuses, one of which is to directly utilize the age-specific population counts published in each census. For example, the proportion of post-1980s survivors aged 30-39 could be obtained from the 1990 Census total population aged 0-9 / 2020 Census total population aged 30-39. However, the conversion of survival rates to mortality rates requires a complex process and additional information.

Another option is to extrapolate the level of mortality based on death data collected in the census. Each census registration asks householders about the deaths of family members in the previous year, which is used to count the number of deaths in the previous year, and then the population mortality rate is calculated by extrapolating the average population size of the census.

Calculated from publicly available statistics, both methods, although flawed, demonstrate thatThe survival of the post-80s is better than that of the post-70s, and the mortality rate is much lower than 5.2%..

So where did this bogus data come from, according to Prof. Litin who traced theThe original source was probably a conversation with an AI.. The attached chart is below:

"1 in 20 Post-80s die" is a rumor, and the culprit may be AI.

Despite the AI conversation labeling the data as having limitations, indirect extrapolations and estimations, the fake news story was splashed across the internet with lurid headlines.

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