Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures
In this work, we present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. We suggest that both the frequency and the seriousness of future AI failures will steadily increase. AI Safety can be improved based on ideas developed by cybersecurity experts. For narrow AIs safety failures are at the same, moderate, level of criticality as in cybersecurity, however for general AI, failures have a fundamentally different impact. A single failure of a superintelligent system may cause a catastrophic event without a chance for recovery. The goal of cybersecurity is to reduce the number of successful attacks on the system; the goal of AI Safety is to make sure zero attacks succeed in bypassing the safety mechanisms. Unfortunately, such a level of performance is unachievable. Every security system will eventually fail; there is no such thing as a 100% secure system.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Advancing the cybersecurity of the healthcare system with self-optimising and self-adaptative artificial intelligence (part 2)
This article advances the knowledge on teaching and training new artificial intelligence algorithms, for securing, preparing, and adapting the healthcare system to cope with future pandemics. The core objective is to dev…
Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions
Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, deterministic, and low-latency decision making under uncertainty. Although the clas…
Quantum Machine LearningDecision MakingOn Safety Assessment of Artificial Intelligence
In this paper we discuss how systems with Artificial Intelligence (AI) can undergo safety assessment. This is relevant, if AI is used in safety related applications. Taking a deeper look into AI models, we show, that man…
Explainable Artificial Intelligence and Cybersecurity: A Systematic Literature Review
Cybersecurity vendors consistently apply AI (Artificial Intelligence) to their solutions and many cybersecurity domains can benefit from AI technology. However, black-box AI techniques present some difficulties in compre…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Systematic Literature ReviewA Cybersecurity Risk Analysis Framework for Systems with Artificial Intelligence Components
The introduction of the European Union Artificial Intelligence Act, the NIST Artificial Intelligence Risk Management Framework, and related norms demands a better understanding and implementation of novel risk analysis a…
Management