We could restore debates by an analog to a fight to the death. The defeated in the debate would have to kill his presence in social media and then build a new presence with a new identity. Lacking such finality in a debate allows a person to return to the established fortress of his channel with its established subscriber base, and within weeks resume content as if the debate never occurred.
A data-driven economy is not a free economy. While there remains promise that algorithms acting on vast amounts of rapidly arriving data can produce a better economy, I am suspicious that such an economy will eventually languish because it robs the human actors of their ability to negotiate. The vitality of a free economy derives from individual freedom to negotiate terms of engagement. Eventually, A data-driven economy may prove to be superior but it will succeed only by suppressing natural human negotiation. Human actors negotiating in a data-driven economy must negotiate with machines. Applying approaches that work for other humans to machines instead is criminalized as cybercrime. Human negotiation involves coming to terms with weaknesses as well as strengths. Exploiting weaknesses of machines is a crime.
When we identify a population with a label of low incomes we imply that their lives would be better if they had higher incomes. This meaning is similar to the above syllogistic fallacy of the illicit major. While there is no doubt that many poor people would desire higher incomes, there are many who choose lower incomes because of some other benefit they get from the jobs. The jobs may be less demanding, or may involve the kind of work they find more enjoyable.
Data should meet tests against fallacies that apply to data like errors in grammar, logic, or reasoning are fallacies in arguments. The above example of a medical health record of a birth with same-sex parents and the mother identifying as a male is analogous to a grammatical error even though the data itself meets the business rules for the form. We should be able to object to this data as valid to use for some purposes such as determining eligibility medical necessity for health services just like we would reject a grammatically incorrect sentence in an formal argument.
Democracy also can not afford to be distracted by spark data (stray voltage) for the same reason. The urgent issues need solutions that require hard and painful choices. Unfortunately, the modern practice of democracy demands obedience to daily public opinion polls that are easily manipulated by stray voltage or spark data. Instead of governing by the people, modern democracy wastes time on arguments over sparks.
There may be many other ways to identify fallacies in handling data that may have an analogous effect on dedomenocracy automated rule-making as classical rhetorical fallacies have on persuasive arguments. In order to defend against malicious or unfair manipulation of a dedomenocracy, we need to develop ways to identify data fallacies that we can use to govern the quality of data for automated rule making.
I think this is what distinguishes modern non-fiction from non-fiction in earlier ages. In earlier ages (Melville’s time), the non-fiction took pains to exclude any fanciful information at all. Non-fiction was devoted the presentation of actual evidence that supports a particular conclusion or theory. Fiction (such as Moby Dick) was a separate work that incorporated those facts into an illustrative example. Today’s non-fiction typically incorporates both fanciful illustrations and actual facts. The danger is that some readers may confuse the illustration as another fact.