Abstract
Currently, the process of digital transformation is actively going on in the economy, science, education, and society as a whole. This process has a number of restrictions and risks we consider. The mathematical theory of complexity reveals a large class of the restrictions. The exact solution of a number of simple-looking problems with a small amount of input data requires resources many times greater than the capabilities of all available computers. On the "border" between natural and artificial intelligence lies the "cognitive barrier". This, as a rule, makes it impossible to use the results of a number of artificial intelligence systems to adjust our strategies. We and computers "think" differently. They have to be considered as "black boxes". It is very likely that the tester of artificial intelligence systems will become one of the mass professions in the close future. We give examples to show that the "translation" from "continuous" to "discrete" language can lead to qualitatively different behavior of mathematical models. In a number of problems associated with a computational experiment this can be quite significant. Great risks arise when passing to the "fast world", approaching the "Lem's barrier". It happens when artificial intelligence systems are assigned strategically important tasks that they must solve at a speed inaccessible to humans. The analysis shows that managing the risks of digital transformation and its limitations requires the attention of the scientific and expert community, as well as active participants in this process.
Highlights
Разумеется, это не повод для того, чтобы отказываться от систем с глубоким обучением, вырабатывающим решающие правила на основе самоорганизации
Барьер Лема не должен переходиться – об этом уже сейчас следует вести переговоры до того, как оружие такого класса будет создано
Summary
Однако история науки и техники показывает, что при появлении базисных инноваций, меняющих сферу производства и общество, их возможности, как правило, переоцениваются, ограничения не учитываются, а риски, связанные с их использованием, игнорируются. Пусть для решения задачи в качестве исходных данных необходим массив из N чисел, а произвести следует Q действий. Что в общем случае точное решение этой задачи требует полного перебора Q = N!. Более того – сам выход за эти ограничения стал использоваться для ряда технологий (криптография с открытым ключом, системы блокчейн и др.).
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