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May 29, 2019 · Unpredictability of AI, one of many impossibility results in AI Safety also known as Unknowability [22] or Cognitive Uncontainability [23], is defined as our inability to precisely and consistently predict what specific actions an intelligent system will take to achieve its objectives, even if we know terminal goals of the system.
Dec 17, 2023 · Latent errors in AI systems, both unpredictable and undetectable, can pose significant risks to societies, especially as these systems become more advanced and complex. The complexity of such ...
Jun 15, 2023 · Richards doesn’t think the AI interpretability problem is all that surprising given the human brains that deep learning systems were modeled after. “When we drop electrodes in human’s brains ...
Feb 23, 2024 · Delving into the deeply enigmatic nature of Artificial Intelligence (AI), AI: Unexplainable, Unpredictable, Uncontrollable explores the various reasons why the field is so challenging. Written by one of the founders of the field of AI safety, this book addresses some of the most fascinating questions facing humanity, including the nature of intelligence, consciousness, values and knowledge.
Notes on macroeconomics and AI. The mental models we have when we try to assess the effects of artificial intelligence on the economy matters. There are several different mental models in circulation, and it is useful to try to sketch them out. First, let’s look at AI-as-additional-humans.
Delving into the deeply enigmatic nature of Artificial Intelligence (AI), AI: Unexplainable, Unpredictable, Uncontrollable explores the various reasons why the field is so challenging. Written by one of the founders of the field of AI safety, this book addresses some of the most fascinating questions facing humanity, including the nature of intelligence, consciousness, values and knowledge. Moving from a broad introduction to the core problems, such as the unpredictability of AI outcomes or the
Jan 3, 2024 · Learning is a more advanced and complex way to make your AI behavior more unpredictable and adaptive. You can use learning algorithms, such as reinforcement learning, neural networks, or genetic ...
