Unpredictability of AI

With increase in capabilities of artificial intelligence, over the last decade, a significant number of researchers have realized importance in creating not only capable intelligent systems, but also making them safe and secure [1-6]. Unfortunately, the field of AI Safety is very young, and researchers are still working to identify its main challenges and limitations. Impossibility results are well known in many fields of inquiry [7-13], and some have now been identified in AI Safety [14-16]. In this paper, we concentrate on a poorly understood concept of unpredictability of intelligent systems [17], which limits our ability to understand impact of intelligent systems we are developing and is a challenge for software verification and intelligent system control, as well as AI Safety in general. In theoretical computer science and in software development in general, many well-known impossibility results are well established, some of them are strongly related to the subject of this paper, for example: Rice's Theorem states that no computationally effective method can decide if a program will exhibit a particular nontrivial behavior, such as producing a specific output [18].