16 found
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Roman Yampolskiy [13]Roman V. Yampolskiy [3]
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Roman Yampolskiy
University of Louisville
  1. Long-Term Trajectories of Human Civilization.Seth D. Baum, Stuart Armstrong, Timoteus Ekenstedt, Olle Häggström, Robin Hanson, Karin Kuhlemann, Matthijs M. Maas, James D. Miller, Markus Salmela, Anders Sandberg, Kaj Sotala, Phil Torres, Alexey Turchin & Roman V. Yampolskiy - 2019 - Foresight 21 (1):53-83.
    Purpose This paper aims to formalize long-term trajectories of human civilization as a scientific and ethical field of study. The long-term trajectory of human civilization can be defined as the path that human civilization takes during the entire future time period in which human civilization could continue to exist. -/- Design/methodology/approach This paper focuses on four types of trajectories: status quo trajectories, in which human civilization persists in a state broadly similar to its current state into the distant future; catastrophe (...)
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  2. Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles.Steven Umbrello & Roman Yampolskiy - 2022 - International Journal of Social Robotics 14 (2):313-322.
    One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model for (...)
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  3. On Controllability of Artificial Intelligence.Roman Yampolskiy -
    Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization. In order to reap the benefits and avoid pitfalls of such powerful technology it is important to be able to control it. However, possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established. In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI can’t be fully controlled. Consequences of (...)
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  4. Responses to Catastrophic AGI Risk: A Survey.Kaj Sotala & Roman V. Yampolskiy - 2015 - Physica Scripta 90.
    Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to (...)
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  5. Simulation Typology and Termination Risks.Alexey Turchin & Roman Yampolskiy - manuscript
    The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which humanity is most likely located based on pure theoretical reasoning. We suggest a new patch to the classical simulation argument, showing that we are likely simulated not by our own descendants, but by alien civilizations. Based on this, we provide (...)
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  6.  81
    Unpredictability of AI.Roman Yampolskiy - manuscript
    The young field of AI Safety is still in the process of identifying its challenges and limitations. In this paper, we formally describe one such impossibility result, namely Unpredictability of AI. We prove that it is impossible to precisely and consistently predict what specific actions a smarter-than-human intelligent system will take to achieve its objectives, even if we know terminal goals of the system. In conclusion, impact of Unpredictability on AI Safety is discussed.
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  7.  58
    Unownability of AI: Why Legal Ownership of Artificial Intelligence is Hard.Roman Yampolskiy - manuscript
    To hold developers responsible, it is important to establish the concept of AI ownership. In this paper we review different obstacles to ownership claims over advanced intelligent systems, including unexplainability, unpredictability, uncontrollability, self-modification, AI-rights, ease of theft when it comes to AI models and code obfuscation. We conclude that it is difficult if not impossible to establish ownership claims over AI models beyond a reasonable doubt.
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  8. Unexplainability and Incomprehensibility of Artificial Intelligence.Roman Yampolskiy - manuscript
    Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to understand how an intelligent system functions for safety and security reasons. In this paper, we describe two complementary impossibility results (Unexplainability and Incomprehensibility), essentially showing that advanced AIs would not be able to accurately explain some of their decisions and for the decisions they could explain people would (...)
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  9. Types of Boltzmann Brains.Alexey Turchin & Roman Yampolskiy - manuscript
    Abstract. Boltzmann brains (BBs) are minds which randomly appear as a result of thermodynamic or quantum fluctuations. In this article, the question of if we are BBs, and the observational consequences if so, is explored. To address this problem, a typology of BBs is created, and the evidence is compared with the Simulation Argument. Based on this comparison, we conclude that while the existence of a “normal” BB is either unlikely or irrelevant, BBs with some ordering may have observable consequences. (...)
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  10. AI Risk Denialism.Roman V. Yampolskiy - manuscript
    In this work, we survey skepticism regarding AI risk and show parallels with other types of scientific skepticism. We start by classifying different types of AI Risk skepticism and analyze their root causes. We conclude by suggesting some intervention approaches, which may be successful in reducing AI risk skepticism, at least amongst artificial intelligence researchers.
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  11. Glitch in the Matrix: Urban Legend or Evidence of the Simulation?Alexey Turchin & Roman Yampolskiy - manuscript
    Abstract: In the last decade, an urban legend about “glitches in the matrix” has become popular. As it is typical for urban legends, there is no evidence for most such stories, and the phenomenon could be explained as resulting from hoaxes, creepypasta, coincidence, and different forms of cognitive bias. In addition, the folk understanding of probability does not bear much resemblance to actual probability distributions, resulting in the illusion of improbable events, like the “birthday paradox”. Moreover, many such stories, even (...)
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  12. Human ≠ AGI.Roman Yampolskiy - manuscript
    Terms Artificial General Intelligence (AGI) and Human-Level Artificial Intelligence (HLAI) have been used interchangeably to refer to the Holy Grail of Artificial Intelligence (AI) research, creation of a machine capable of achieving goals in a wide range of environments. However, widespread implicit assumption of equivalence between capabilities of AGI and HLAI appears to be unjustified, as humans are not general intelligences. In this paper, we will prove this distinction.
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  13. When Should Co-Authorship Be Given to AI?G. P. Transformer Jr, End X. Note, M. S. Spellchecker & Roman Yampolskiy -
    If an AI makes a significant contribution to a research paper, should it be listed as a co-author? The current guidelines in the field have been created to reduce duplication of credit between two different authors in scientific articles. A new computer program could be identified and credited for its impact in an AI research paper that discusses an early artificial intelligence system which is currently under development at Lawrence Berkeley National. One way to imagine the future of artificial intelligence (...)
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  14. “Cheating Death in Damascus” Solution to the Fermi Paradox.Alexey Turchin & Roman Yampolskiy - manuscript
    One of the possible solutions of the Fermi paradox is that all civilizations go extinct because they hit some Late Great Filter. Such a universal Late Great Filter must be an unpredictable event that all civilizations unexpectedly encounter, even if they try to escape extinction. This is similar to the “Death in Damascus” paradox from decision theory. However, this unpredictable Late Great Filter could be escaped by choosing a random strategy for humanity’s future development. However, if all civilizations act randomly, (...)
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  15.  60
    Designometry – Formalization of Artifacts and Methods.Soenke Ziesche & Roman Yampolskiy - manuscript
    Two interconnected surveys are presented, one of artifacts and one of designometry. Artifacts are objects, which have an originator and do not exist in nature. Designometry is a new field of study, which aims to identify the originators of artifacts. The space of artifacts is described and also domains, which pursue designometry, yet currently doing so without collaboration or common methodologies. On this basis, synergies as well as a generic axiom and heuristics for the quest of the creators of artifacts (...)
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  16. Sztuczna Inteligencja: Bezpieczeństwo I Zabezpieczenia.Roman Yampolskiy (ed.) - 2020 - Warszawa: Wydawnictwo Naukowe PWN.
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