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Human Compatible: Artificial Intelligence and the Problem of Control. Stuart Russell

Human Compatible: Artificial Intelligence and the Problem of Control


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ISBN: 9780525687016 | 320 pages | 8 Mb
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  • Human Compatible: Artificial Intelligence and the Problem of Control
  • Stuart Russell
  • Page: 320
  • Format: pdf, ePub, fb2, mobi
  • ISBN: 9780525687016
  • Publisher: Penguin Publishing Group
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A world-leading artificial intelligence researcher explains why uncontrolled superhuman AI represents an existential threat to humanity, and lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage. If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial. In a 2014 editorial co-authored with Stephen Hawking, Russell wrote, "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last." Solving the problem of control over AI is not just possible; it is the key that unlocks a future of unlimited promise.

Human Compatible: Artificial Intelligence and the Problem of Control
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Artificial Intelligence - People @ EECS at UC Berkeley
The field of AI studies the general problem of creating intelligence in .. The issue of maintaining human control is, nonetheless, important in the long term. .. the Center for Human-Compatible AI at Berkeley contain much more information.
Stuart J. Russell - Wikipedia
Stuart Jonathan Russell (born 1962) is a computer scientist known for his contributions to In 2016, he founded the Center for Human-Compatible Artificial Intelligence at UC Berkeley, with His book, Human Compatible: Artificial Intelligence and the Problem of Control, will be published by Viking in October 2019.
Will Democracy Survive Big Data and Artificial Intelligence
The field of artificial intelligence is, indeed, making breathtaking advances. . This problem is exacerbated by the fact that, in many countries, a single search and processing of personal data is certainly not compatible with the applicable data .. Human-level control through deep reinforcement learning.
AI control problem - Wikipedia
In artificial intelligence (AI) and philosophy, the AI control problem is the issue of how to build a Humans currently dominate other species because the human brain has some distinctive capabilities that the brains of other animals lack.
Stuart J. Russell | EECS at UC Berkeley
Artificial Intelligence (AI) · Control, Intelligent Systems, and Robotics (CIR) Center for Human Compatible Artificial Intelligence (CHAI) · Berkeley Center for and intelligence," Artificial Intelligence: Special Issue on Economic Principles of 
Ethical Artificial Intelligence - arXiv
The problem of defining and creating ethical AI continues, and interest in it will grow enormously. human mental models, future AI systems will be different because they will learn environment models that are more Factory process control systems contain models of their environments. compatible with liberty for all.
Human Compatible by Stuart Russell - Financial Times
In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be Human Compatible: AI and the Problem of Control.
UC Berkeley launches Center for Human-Compatible Artificial
The issue, he said, is that machines as we currently design them in fields like AI, robotics, control theory and operations research take the 
Human Compatible: AI and the Problem of Control (Audio Download
Human Compatible: AI and the Problem of Control (Audio Download): Amazon. co.uk: Stuart Russell, Penguin Audio : Books.
Human Compatible by Stuart J. Russell - Penguin Books New Zealand
AI and the Problem of Control the dominant technology of the future than Russell, who has spent decades at the forefront of AI research.
Superintelligence: Paths, Dangers, Strategies - Wikipedia
It is unknown whether human-level artificial intelligence will arrive in a matter of years, to successfully solve the "AI control problem" for the first superintelligence. the superintelligence with goals that are compatible with human survival and 
Stuart Russell's New Book Now Available on Amazon for Pre-Order
Stuart Russell's new book, Human Compatible: Artificial Intelligence and the Problem of Control is now available on Amazon for pre-order.
Can AI Robots Rebel Against Us, as Shown in Films? - Towards
But this is to misunderstand where the real problem lies. but what if machines will hack into the traffic light control system so that all of the The Center for Human-Compatible Artificial Intelligence, launched with $5.5m in 
Bibliography - Center for Human-Compatible AI
Preference inference - Building AI systems that learn what humans want. Moral theory - Moral issues that HCAI systems and their developers might . (2) Human -level control through deep reinforcement learning, Mnih et al.

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