paper-with-me

Papers

Superintelligence Safety: A Requirements Engineering Perspective

2019-09-26 · Hermann Kaindl, Jonas Ferdigg

Under the headline "AI safety", a wide-reaching issue is being discussed, whether in the future some "superhuman artificial intelligence" / "superintelligence" could could pose a threat to humanity. In addition, the late Steven Hawking warned that the rise of robots may be disastrous for mankind. A major concern is that even benevolent superhuman artificial intelligence (AI) may become seriously harmful if its given goals are not exactly aligned with ours, or if we cannot specify precisely its objective function. Metaphorically, this is compared to king Midas in Greek mythology, who expressed the wish that everything he touched should turn to gold, but obviously this wish was not specified precisely enough. In our view, this sounds like requirements problems and the challenge of their precise formulation. (To our best knowledge, this has not been pointed out yet.) As usual in requirements engineering (RE), ambiguity or incompleteness may cause problems. In addition, the overall issue calls for a major RE endeavor, figuring out the wishes and the needs with regard to a superintelligence, which will in our opinion most likely be a very complex software-intensive system based on AI. This may even entail theoretically defining an extended requirements problem.

📄 PDF Abstract BibTeX arXiv:1909.12152

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

The Subject of Emergent Misalignment in Superintelligence: An Anthropological, Cognitive Neuropsychological, Machine-Learning, and Ontological Perspective

2025-12-19 · Muhammad Osama Imran, Roshni Lulla, Rodney Sappington arxiv

We examine the conceptual and ethical gaps in current representations of Superintelligence misalignment. We find throughout Superintelligence discourse an absent human subject, and an under-developed theorization of an "…

Foundational Analysis of Safety Engineering Requirements (SAFER)

2026-01-09 · Noga Chemo, Yaniv Mordecai, Yoram Reich arxiv

We introduce a framework for Foundational Analysis of Safety Engineering Requirements (SAFER), a model-driven methodology supported by Generative AI to improve the generation and analysis of safety requirements for compl…

The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment

2024-12-21 · HyunJin Kim, Xiaoyuan Yi, Jing Yao, Jianxun Lian 외

The emergence of large language models (LLMs) has sparked the possibility of about Artificial Superintelligence (ASI), a hypothetical AI system surpassing human intelligence. However, existing alignment paradigms struggl…

Survey

Safeguarding Learning-based Control for Smart Energy Systems with Sampling Specifications

2023-08-11 · Chih-Hong Cheng, Venkatesh Prasad Venkataramanan, Pragya Kirti Gupta, Yun-Fei Hsu 외

We study challenges using reinforcement learning in controlling energy systems, where apart from performance requirements, one has additional safety requirements such as avoiding blackouts. We detail how these safety req…

reinforcement-learningReinforcement LearningSafe Reinforcement Learning

Aligning Artificial Superintelligence via a Multi-Box Protocol

2025-11-26 · Avraham Yair Negozio arxiv

We propose a novel protocol for aligning artificial superintelligence (ASI) based on mutual verification among multiple isolated systems that self-modify to achieve alignment. The protocol operates by containing multiple…