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Achieving Friendly Artificial Intelligence

Are the robots going to take over?

The Matrix and Terminator movies present a nightmare world in which artificially intelligent machines pit themselves against humanity with devastating consequences. Could something like that really happen?

Fastfroward’s Phil Bowermaster and Stephen Gordon welcome a panel of leading thinkers on artificial intelligence to explore these issues:

In the near future, is machine intelligence going to equal or overtake human intelligence in terms of speed and capability?

If so, what can we do to make sure these new intelligences are on our side?

Eliezer Yudkowsky is the world’s foremost researcher on Friendly AI and recursive self-improvement. He is a research fellow with the Singularity Institute for Artificial Intelligence.

James Hughes is the Executive Director of the Institute for Ethics and Emerging Technologies, and he is the producer and host of the weekly syndicated public affairs talk show Changesurfer Radio

Ben Goertzel is a Fellow of the IEET, the chief science officer and acting CEO of Novamente and Director of Research for the Singularity Institute for Artificial Intelligence.




COMMENTS
The solution to this problem is already contained within the recently issued U.S. patent
concerning ethical artificial intelligence entitled:
Inductive Inference Affective Language Analyzer
Simulating Artificial Intelligence (patent No. 6,587,846)
by inventor/author John E. LaMuth M. S.
As implied in its title, this innovation is the 1st affect-
ive language analyzer incorporating ethical/motivational
terms, serving in the role of interactive computer
interface. It enables a computer to reason and speak in an
ethical fashion, serving in roles specifying sound human
judgement: such as public relations or security functions.
This innovation is formally based on a multi-level
hierarchy of the traditional groupings of virtues, values,
and ideals, collectively arranged as subsets within a
hierarchy of metaperspectives - as partially depicted below.

Glory--Prudence Honor--Justice
Providence--Faith Liberty--Hope
Grace--Beauty Free-will--Truth
Tranquility--Ecstasy Equality--Bliss

Dignity--Temperance Integrity--Fortitude
Civility--Charity Austerity--Decency
Magnanim.--Goodness Equanimity--Wisdom
Love--Joy Peace--Harmony

The systematic organization underlying this ethical
hierarchy allows for extreme efficiency in programming,
eliminating much of the associated redundancy, providing
a precise determination of motivational parameters at
issue during a given verbal interchange.
This AI platform is organized as a tandem-nested expert
system, composed of a primary affective-language analyzer
overseen by a master control-unit (that coordinates the
verbal interactions over real time). Through an elaborate
matching procedure, the precise motivational parameters
are accurately determined (defined as the passive-monitoring
mode). This basic determination, in turn, serves as the
basis for a response repertoire tailored to the computer
(the true AI simulation mode). This innovation is completely
novel in its ability to simulate emotionally charged language:
an achievement that has previously eluded AI researchers due
to the lack of an adequate model of motivation in general.
As such, it represents a pure language simulation, effectively
bypassing many of the limitations plaguing current robotic
research. Affiliated potential applications extend to the
roles of switchboard/receptionist and personal
assistant/companion (in a time-share mode).
Although only a cursory outline of applications is possible for
this (90 page) patent, a more detailed treatment is posted at:
http://www.ethicalvalues.com
Please consider me for future FF-Radio panel discussion...
As long as the developer of the AI machine lets someone pull the plug (and didn't design the machine to fight off those who try to pull the plug), I don't worry about robots taking over.
John's comments highlight the mistaken assumption that AI researchers have been making for decades, i.e., that simulating intelligence through top-down programming is fundamentally different from emergent post-singularity General AI. Any linguistic system is by nature descriptive - a metalanguage, if you will - and as such is ontologically distinct from the object set being described. Although John is correct in stressing the value of a hierarchical model, any Turing-based instantiation is architecturally insufficient for the successful creation of true GAI.
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