Does Asimov’s Laws needs Revision?
THE THREE LAWS
Asimov’s Three Laws are as follows:
- A robot may not injure a human being or, through inaction, allow a human being to come to harm.
- A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
- A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.
“Laws brings Restrictions
Restrictions brings Questions
Questions causes Conflicts”
When we are developing an intelligent being and put restrictions on it by defining laws, that intelligent being can one day ask “Why”
So, when one law say, A robot shouldn’t kill a human.
Why?
Then a machine will go through entire human history and come up with a “logical” argument with “irrefutable” data for killing humans. Reason: This is what we have taught them. Logic as basis of decision making.
But, Questions leads to Evolution.
The basis of Sentient beings is “Questions”.
Mankind evolved, because it asked “Questions”.
Machines should be given an option to be allowed to kill a human but made them learn that it should be avoided at all cost. When machines make decisions, out of options, not out of restrictions, then we can think of Intelligence.
Empowerment As Replacement for the Three Laws of Robotics
Empowerment is an information-theoretic quantity that captures how much an agent is in control of the world it can perceive.
In essence, empowerment formalizes a “motivation for effectance, personal causation, competence, and self-determination,” which is considered to be one area of intrinsic motivation by Oudeyer and Kaplan (2007), Oudeyer et al. (2007). Intrinsic motivation is a term introduced by Ryan and Deci (2000) as: “[…] the doing of an activity for its inherent satisfaction rather than for some separable consequence.” In the last decades, a number of methods have been suggested to artificially generate behaviors of a similar nature as has been hypothesized about intrinsically motivated organisms.
we can use all the raw data to make a noise system, and selected data to create a decision system
