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Three Laws of Robotics
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I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

Human expert knowledge does not reduce to closed logic systems and this attribute of human knowledge is called heuristic.

The movie I Robot () dramatizes some of the issues with knowledge as an attribute of so-called artificial and human intelligence. This link is a summary of Isaac Asimov's Three Laws of Robotics:

https://webhome.auburn.edu/~vestmon/robotics.html

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law. 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

How does a Knowledge-Based System, programmed with explicit knowledge and logic, avoid injuring a human being through action or inaction? How does a neural network system, with implicit brain activity, learn to recognize what it means to prevent harm to human beings through action or inaction of the robot system? In common law an animal or child cannot understand the meaning of harm to another person, and a child without the capacity to govern action by the use of reason, cannot act to avoid or prevent harm to another person. There is a logic to harm and benefit of others in the dramatic context but can we map that logic to an explicit knowledge-based system? So far I would characterize such efforts as Mission Impossible!

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

Human expert knowledge does not reduce to closed logic systems and this attribute of human knowledge is called heuristic.

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

Human expert knowledge does not reduce to closed logic systems and this attribute of human knowledge is called heuristic.

The movie I Robot () dramatizes some of the issues with knowledge as an attribute of so-called artificial and human intelligence. This link is a summary of Isaac Asimov's Three Laws of Robotics:

https://webhome.auburn.edu/~vestmon/robotics.html

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law. 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

How does a Knowledge-Based System, programmed with explicit knowledge and logic, avoid injuring a human being through action or inaction? How does a neural network system, with implicit brain activity, learn to recognize what it means to prevent harm to human beings through action or inaction of the robot system? In common law an animal or child cannot understand the meaning of harm to another person, and a child without the capacity to govern action by the use of reason, cannot act to avoid or prevent harm to another person. There is a logic to harm and benefit of others in the dramatic context but can we map that logic to an explicit knowledge-based system? So far I would characterize such efforts as Mission Impossible!

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

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SystemTheory
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I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

Human expert knowledge does not reduce to closed logic systems and this attribute of human knowledge is called heuristic.

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

Human expert knowledge does not reduce to closed logic systems and this attribute of human knowledge is called heuristic.

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

deleted 441 characters in body
Source Link
SystemTheory
  • 3.2k
  • 4
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I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

I took an engineering course called Knowledge-Based Systems back in 1990. These are also known as expert systems, but I think expert systems include implicit knowledge stored in artificial or biological neural networks. Knowledge-based systems are based on explicit knowledge and logic and are known to be brittle:

https://ksi.cpsc.ucalgary.ca/KAW/KAW96/compton/compton.html

This pdf is a slide presentation of expert systems where the system is a "black box" to the user:

https://cse.hkust.edu.hk/~dekai/600G/notes/KM_Slides_Ch08.pdf

I think IBM Watson, the computer system that won Jeopardy, was a Knowledge-Based System with a Bayesian inference engine to rank possible answers as better or worse in the context of the question. But it may have had elements of large language model I have not done a study of the system engineering. Human knowledge is open in the general context and even human expert knowledge does not seem to be closed under any system of human logic.

deleted 441 characters in body
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