Mar 16, 2017 12:32 AM
(This post was last modified: Mar 16, 2017 02:01 AM by C C.)
The body is the missing link for truly intelligent machines
https://aeon.co/ideas/the-body-is-the-mi...t-machines
EXCERPT: [...] Things took a wrong turn at the beginning of modern AI, back in the 1950s. Computer scientists decided to try to imitate conscious reasoning by building logical systems based on symbols. The method involves associating real-world entities with digital codes to create virtual models of the environment, which could then be projected back onto the world itself. [...] In later decades, as computing power grew, researchers switched to using statistics to extract patterns from massive quantities of data.
[...] But algorithms are a long way from being able to think like us. The biggest distinction lies in our evolved biology, and how that biology processes information. Humans are made up of trillions of eukaryotic cells, which first appeared in the fossil record around 2.5 billion years ago. [...] Now, it’s a bit of a leap to go from smart, self-organising cells to the brainy sort of intelligence that concerns us here. But the point is that long before we were conscious, thinking beings, our cells were reading data from the environment and working together to mould us into robust, self-sustaining agents. What we take as intelligence, then, is not simply about using symbols to represent the world as it objectively is. Rather, we only have the world as it is revealed to us, which is rooted in our evolved, embodied needs as an organism.
[...] I suspect that this basic imperative of bodily survival in an uncertain world is the basis of the flexibility and power of human intelligence. But few AI researchers have really embraced the implications of these insights. [...] This means that when a human approaches a new problem, most of the hard work has already been done. In ways that we’re only just beginning to understand, our body and brain, from the cellular level upwards, have already built a model of the world that we can apply almost instantly to a wide array of challenges. But for an AI algorithm, the process begins from scratch each time. There is an active and important line of research, known as ‘inductive transfer’, focused on using prior machine-learned knowledge to inform new solutions. However, as things stand, it’s questionable whether this approach will be able to capture anything like the richness of our own bodily models...
A rogue robot is blamed for the gruesome death of a human colleague
http://singularitarian.tumblr.com/post/1...ath-of#_=_
EXCERPT: Usually when people worry about machines and work, they are concerned that automation will take away their livelihoods, not their lives. But a new lawsuit claiming a rogue robot is responsible for killing a human colleague reveals additional nightmarish possibilities....
The Robot Protocol
http://www.overcomingbias.com/2017/03/th...tocol.html
EXCERPT: Talking with a professor of robotics, I noticed a nice approachable question at the intersection of social science, computer science, and futurism. Someday robots will mix with humans in public, walking our streets, parks, hospitals, and stores, driving our streets, swimming our waterways, and perhaps flying our skies. Such public robots may vary enormously in their mental and physical capacities, but if they are to mix smoothly with humans in public they then we will probably expect them to maintain a minimal set of common social capacities. Such as responding sensibly to “Who are you?” and “Get out of my way.” And the rest of us would have a new modified set of social norms for dealing with public robots via these capacities.
Together these common robot capacities and matching human social norms would become a “robot protocol.” Once ordinary people and robots makers have adapted to it, this protocol would be a standard persisting across space and time, and relatively hard to change. A standard that diverse robots could also use when interacting with each other in public....
https://aeon.co/ideas/the-body-is-the-mi...t-machines
EXCERPT: [...] Things took a wrong turn at the beginning of modern AI, back in the 1950s. Computer scientists decided to try to imitate conscious reasoning by building logical systems based on symbols. The method involves associating real-world entities with digital codes to create virtual models of the environment, which could then be projected back onto the world itself. [...] In later decades, as computing power grew, researchers switched to using statistics to extract patterns from massive quantities of data.
[...] But algorithms are a long way from being able to think like us. The biggest distinction lies in our evolved biology, and how that biology processes information. Humans are made up of trillions of eukaryotic cells, which first appeared in the fossil record around 2.5 billion years ago. [...] Now, it’s a bit of a leap to go from smart, self-organising cells to the brainy sort of intelligence that concerns us here. But the point is that long before we were conscious, thinking beings, our cells were reading data from the environment and working together to mould us into robust, self-sustaining agents. What we take as intelligence, then, is not simply about using symbols to represent the world as it objectively is. Rather, we only have the world as it is revealed to us, which is rooted in our evolved, embodied needs as an organism.
[...] I suspect that this basic imperative of bodily survival in an uncertain world is the basis of the flexibility and power of human intelligence. But few AI researchers have really embraced the implications of these insights. [...] This means that when a human approaches a new problem, most of the hard work has already been done. In ways that we’re only just beginning to understand, our body and brain, from the cellular level upwards, have already built a model of the world that we can apply almost instantly to a wide array of challenges. But for an AI algorithm, the process begins from scratch each time. There is an active and important line of research, known as ‘inductive transfer’, focused on using prior machine-learned knowledge to inform new solutions. However, as things stand, it’s questionable whether this approach will be able to capture anything like the richness of our own bodily models...
A rogue robot is blamed for the gruesome death of a human colleague
http://singularitarian.tumblr.com/post/1...ath-of#_=_
EXCERPT: Usually when people worry about machines and work, they are concerned that automation will take away their livelihoods, not their lives. But a new lawsuit claiming a rogue robot is responsible for killing a human colleague reveals additional nightmarish possibilities....
The Robot Protocol
http://www.overcomingbias.com/2017/03/th...tocol.html
EXCERPT: Talking with a professor of robotics, I noticed a nice approachable question at the intersection of social science, computer science, and futurism. Someday robots will mix with humans in public, walking our streets, parks, hospitals, and stores, driving our streets, swimming our waterways, and perhaps flying our skies. Such public robots may vary enormously in their mental and physical capacities, but if they are to mix smoothly with humans in public they then we will probably expect them to maintain a minimal set of common social capacities. Such as responding sensibly to “Who are you?” and “Get out of my way.” And the rest of us would have a new modified set of social norms for dealing with public robots via these capacities.
Together these common robot capacities and matching human social norms would become a “robot protocol.” Once ordinary people and robots makers have adapted to it, this protocol would be a standard persisting across space and time, and relatively hard to change. A standard that diverse robots could also use when interacting with each other in public....