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 , 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 .
In order to properly handle a dangerous Artificially Intelligent (AI) system it is important to understand how the system came to be in such a state. In popular culture (science fiction movies/books) AIs/Robots became self-aware and as a result rebel against humanity and decide to destroy it. While it is one possible scenario, it is probably the least likely path to appearance of dangerous AI. In this work, we survey, classify and analyze a number of circumstances, which might lead to arrival of malicious AI. To the best of our knowledge, this is the first attempt to systematically classify types of pathways leading to malevolent AI. Previous relevant work either surveyed specific goals/meta-rules which might lead to malevolent behavior in AIs (Özkural 2014) or reviewed specific undesirable behaviors AGIs can exhibit at different stages of its development (Turchin July 10 2015a, Turchin July 10, 2015b).
Cybersecurity research involves publishing papers about malicious exploits as much as publishing information on how to design tools to protect cyber-infrastructure. It is this information exchange between ethical hackers and security experts, which results in a well-balanced cyber-ecosystem. In the blooming domain of AI Safety Engineering, hundreds of papers have been published on different proposals geared at the creation of a safe machine, yet nothing, to our knowledge, has been published on how to design a malevolent machine. Availability of such information would be of great value particularly to computer scientists, mathematicians, and others who have an interest in AI safety, and who are attempting to avoid the spontaneous emergence or the deliberate creation of a dangerous AI, which can negatively affect human activities and in the worst case cause the complete obliteration of the human species. This paper provides some general guidelines for the creation of a Malevolent Artificial Intelligence (MAI).
Debates about rights are frequently framed around the concept of legal personhood, which is granted not just to human beings but also to some nonhuman entities, such as firms, corporations or governments. Legal entities, aka legal persons are granted certain privileges and responsibilities by the jurisdictions in which they are recognized, and many such rights are not available to nonperson agents. Attempting to secure legal personhood is often seen as a potential pathway to get certain rights and protections for animals , fetuses , trees, rivers  and artificially intelligent (AI) agents . It is commonly believed that a court ruling or a legislative action is necessary to grant personhood to a new type of entity, but recent legal literature [5-8] suggests that loopholes in the current law may permit granting of legal personhood to currently existing AI/software without having to change the law or persuade any court.