In times of machine intelligence evidence and truth take on new meaning as an orientation in a constructed reality. Large language moduls as used in machine learning are designed for simulation and deception. An electronic network that is suitable for imitating human language logic provides most of the properties to perfect lies. Lies are very much based on rationality and logic. Dichotomous thinking creates the polarity between the extremes of truth and untruth. While truth is immutably derived from the application of established laws and regulations evidence arises from the distinction between the probabilities of right and wrong or adequate and inadequate. Social conventions regulate many interhuman relationships in which we have to be able to rely on each other. In terms of social development, we have learned to live with compromises related to honesty. Direct lying remains socially unacceptable but concealment, deception and misleading are common means of competition. Although, peaceful and tolerant coexistence in the community is based on trust, lies are prevalent in the human society. Dealing openly with the topic allows to recognize how large and comprehensive the influence of lying within a community is. Rather than feeling a false sense of certainty it is better to use common sense and to estimate the probability of potential uncertainty. It remains to be hoped that the new machine intelligence can also be used to check data quality and provide precise information about data truthworthiness.
Wolfgang Lederer (Sat,) studied this question.
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