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Safety of AI and robots. Roland Pihlakas Institute of Technology in University of Tartu 26. April 2008. You may do it like. Good states - goals Bad states - don’t do-s. In contrast, proposed approach is kind of orthogonal.
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Safety of AI and robots Roland Pihlakas Institute of Technology in University of Tartu 26. April 2008
You may do it like • Good states - goals • Bad states - don’t do-s
In contrast, proposed approach is kind of orthogonal • Implicit: avoid any irreversibilities (does not need pre-specified bad states) • Explicit: goals (good states)
A small addition... • Implicit: avoid any irreversibilities (no pre-specified bad states) • Explicit: rights (still no pre-specified states; instead - sorts of states) • Explicit: goals (good states)
In short • 1. Rights • 2. Goals
An analogy: the three laws of robotics • 1. Don’t do harm. => Avoid irreversibilities • 2. Do what you are ordered to do. • a. Goals • b. May include explicitly stated bad states • 3. Be optimal, be tidy, clean up reversible temporary changes. Recommendations.
“passive” safety - avoid only own mistakes
Goals value of indicator current measured preferred state planned action
Reversibilities first action value of indicator current measured first measured state second action
IR-reversibilities No-no action: don’t do this - don’t cause irreversible states value of indicator state to avoid first measured state cannot achieve - cannot reverse the first action
Permissions Not reversible, but okay action value of indicator state,which we dont need toavoid first measured state cannot achieve - cannot reverse the first action
Implementation • Logical programming; planning is using theorem provers • Statistical / machine learning; control system
A safe AI should not increase entropy, except only temporarily.