Safety And Security Of Artificial Intelligence Systems

The history of robotics and artificial intelligence in many ways is also the history of humanity’s attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.

The history of robotics and artificial intelligence in many ways is also the history of humanity’s attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.

In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

This book constitutes the refereed proceedings of five workshops co-located with SAFECOMP 2018, the 37th International Conference on Computer Safety, Reliability, and Security, held in Västerås, Sweden, in September 2018. The 28 revised full papers and 21 short papers presented together with 5 introductory papers to each workshop were carefully reviewed and selected from 73 submissions. This year's workshops are: ASSURE 2018 – Assurance Cases for Software-Intensive Systems; DECSoS 2018 – ERCIM/EWICS/ARTEMIS Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems; SASSUR 2018 – Next Generation of System Assurance Approaches for Safety-Critical Systems; STRIVE 2018 – Safety, securiTy, and pRivacy In automotiVe systEms; and WAISE 2018 – Artificial Intelligence Safety Engineering. The chapter '“Boxing Clever”: Practical Techniques for Gaining Insights into Training Data and Monitoring Distribution Shift' is available open access under an Open Government License via link.springer.com.

As intelligent autonomous agents and multiagent system applications become more pervasive, it becomes increasingly important to understand the risks associated with using these systems. Incorrect or inappropriate agent behavior can have harmful - fects, including financial cost, loss of data, and injury to humans or systems. For - ample, NASA has proposed missions where multiagent systems, working in space or on other planets, will need to do their own reasoning about safety issues that concern not only themselves but also that of their mission. Likewise, industry is interested in agent systems that can search for new supply opportunities and engage in (semi-) automated negotiations over new supply contracts. These systems should be able to securely negotiate such arrangements and decide which credentials can be requested and which credentials may be disclosed. Such systems may encounter environments that are only partially understood and where they must learn for themselves which aspects of their environment are safe and which are dangerous. Thus, security and safety are two central issues when developing and deploying such systems. We refer to a multiagent system’s security as the ability of the system to deal with threats that are intentionally caused by other intelligent agents and/or s- tems, and the system’s safety as its ability to deal with any other threats to its goals.

AI Security is a book on the technical and societal impacts of advanced artificial intelligence. Written by a strong AI researcher, it uniquely addresses the safety and security questions by utilizing fundamentals from cybersecurity and computer science. The result is a rigorous and candid response to the major questions surrounding the future impacts of artificial intelligence on humanity.

What Is Artificial Intelligence Safety Artificial intelligence (AI) safety is an interdisciplinary field that focuses on the prevention of accidents, abuse, and other potentially negative outcomes that could be caused by artificial intelligence (AI) systems. It comprises machine ethics and AI alignment, both of which attempt to make AI systems moral and beneficial, while AI safety encompasses technical concerns such monitoring systems for hazards and making them extremely reliable. Both of these aspects aim to make AI systems more trustworthy and beneficial. In addition to AI research, it entails the development of standards and guidelines that prioritize safety. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: AI safety Chapter 2: Machine learning Chapter 3: Artificial general intelligence Chapter 4: Applications of artificial intelligence Chapter 5: Adversarial machine learning Chapter 6: Existential risk from artificial general intelligence Chapter 7: AI alignment Chapter 8: Explainable artificial intelligence Chapter 9: Neuro-symbolic AI Chapter 10: Hallucination (artificial intelligence) (II) Answering the public top questions about artificial intelligence safety. (III) Real world examples for the usage of artificial intelligence safety in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of artificial intelligence safety' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial intelligence safety.