[ExI] 'Friendly' AI won't make any difference

Colin Hales col.hales at gmail.com
Sat Feb 27 00:48:03 UTC 2016

Hi Anders,

Yes you got my basic approach right. But I do not ask any of you to have an
opinion and I am not interested in opinions. Especially not in any
assessment of what might be or not be dangerous. Not because I want to be a
contrarian prick. But because I want some science. I want something you can
argue for, with evidence. That makes it science. None of the commentariat
involved in this even knows what actual science is. They think they can
'define' things! Want me to show you magic? MEASURE SOMETHING. Do some
actual science.

"......do not allow neat safety proofs. We need to develop a better way of
thinking about complex adaptive technological systems and how to handle

'SAFETY PROOF!!?" Don't you see that the very idea of a proof or even
saying anything even remotely relevant was dumped as an option 60 years
ago?  Anniversary year, 2016. Sixty years of blindness. All of it, before
the AGI risk handwringing commentator even opens their mouth, or lifts a
hand over a keyboard, is meretricious maundering at best.

OK I'll have another go at getting this 60 year old slumbering twat to wake
up. I'll do it empirically.  I am going to use some upper case. Apologies
in advance.
The science of what is currently called 'artificial intelligence' has not
started yet. Scientific behaviour, for centuries, _until the Dartmouth
conference_, was 100% involved in 2 mutually coupled, resonating activities
that resulted in predictive abstract statements that sometimes get called
'laws of nature':

1) Encounter and/or replicate nature's essential physics.
2) Construct abstractions that could be manually computed and interpreted
as involved in what was explored as the essential physics.

Compare/contrast models of nature, replicated nature with natural original
physics. We just saw two spectacular examples: Higgs Boson and
Gravitational waves. Actual empirical work.


Essential physics: e.g. A heart has pump physics. A kidney has filtration
physics. A plane has air-flight-surface physics. Combustion has oxidation
physics. and on and on and on and on and on and on and on and on and on and
on and on and on and on and on and on and on and on ...... thousands of
examples. Centuries of practice.

And that non-stop continuous run of success ENDED at the Dartmouth
conference in 1956. How?

(1) was abandoned.

Brains may have essential physics. But if you never ever ever ever look for
it, but instead, replace it with endless machinations of potential (2)'s
(neuromorphic hardware model-computation or software or quantum hardware
whatever), then you are not doing science. That is what stopped in 1956. It
is as if an entire community stopped doing actual science by assuming, for
no principled reason or empirical reason, that there is no physics
essential and unique to a brain. An intuition. A guess. Nothing more.

FACT. Measurable birth defect in the science of AI. Obvious, complete,
pervasive, ongoing.

The hypothesis X = "there is 'no essential physics' of the brain" may be
true! But you, me everyone on the entire planet does not know that. This is
because the empirical science that determines the essential physics
involves 2 kinds of tests:

A) Assume X true, emulate everything, compute models... then
compare/contrast with the natural brain.;
B) Assume X is false, replicate hypothesised essential physics ... compar3e
nature, replication and emulation. DO ACTUAL SCIENCE.

This year is the 60th anniversary of the 100% expenditure of all AI budgets
world wide entirely on TEST A.

There are 2 cases of test B (apart from mine) Ashby and Walter in the early
1950s. They did not use computers.
Their work could have become (1) science and (B) testing. But that was lost
in the great cybernetics rout of 1956-65.

I can see potential essential physics in the brain. I am doing (1)/(2) AND
(B). I don't know if it is essential. NOBODY DOES. That is the point.

If you don't have the essential physics of the brain then NO ACTUAL BRAIN.
All the endless bullshit about AGI risks is based on completely malformed
non-scientific uninformed mumbo-jumbo. The only way to handle any risk is
to actually build it and then experiment. The entire field of risk
assessment is totally screwed up because it is literally missing half the
science. And it is the only half that matters.

Using a flight analogy, this is what AI actually is at the moment:

1) 100% flight simulators. (studies of models of intelligence, sometimes in
robot clothing).
2) %Nil actual flight. ZERO intelligence. Not just small or low or
variable. ZERO. Like there is zero flight in a flight simulator.

FFS. Use a Searle analogy:

(i) WEAK FLIGHT = Computed models are a flight simulator (a study of
flight, not actual flight)
(ii) STRONG-FLIGHT = Computed models of flight carried out with the
expectation that the computation will FLY!!!!!

(i) WEAK FIRE = Computed models are a combustion simulator (a study of
fire, not actual fire)
(ii) STRONG-FIRE = Computed models of fire carried out with the expectation
that the computation will BURN

60 years of expecting (ii) for the brain and only for the brain, endlessly
expecting something different by doing the same thing over and over and
over? Complete insanity! Expecting the computer to 'fly' or 'burn'(be
human/natural-intellect) ?? Without 1 test that does actual science?

Putting a model in robot clothes, automating the behaviour of the model,
makes an elaborate puppet. It may be useful. It may have a social impact
(jobs). SO WHAT! The whole existential 'robots are gonna kill us all'
argument from non-scientific ignorance is a complete nonsense.

AI (Flight) has not even started yet. It's all 'automated intelligence'.
Deep automation. Deep learning. Whatever.
None of it is actual 'artificial intelligence' because all of it throws the
essential brain physics out, replacing it with the physics of a
computational substrate. We threw it all out on day 1 and it's still thrown
out. Am I making myself clear?

Dammit I am sick of point out the obvious.

I have to admit I now know how Laviosier felt about phlogiston. Phlogiston
lasted 100 years. So called 'AI' is turning 60. I hate that I was born and
have lived nearly 1 year longer than the whole of so-called AI era. I have
watched this all my life. All I am asking is for a return to an untried
normalcy: actual science ... a departure that was never chosen by anyone,
never justified, has no physical principle supporting it and no evidence,
and no literature trail justifying any of it.

Forget it. Carry on. I'll just go hide again. At least I have proved to
myself again why I hate this idiotic situation.


On Fri, Feb 26, 2016 at 8:50 PM, Anders Sandberg <anders at aleph.se> wrote:

> On 2016-02-25 22:43, Colin Hales wrote:
> Evaluations of the AI risk landscape are, so far, completely and utterly
> vacuous and misguided. It completely misses an entire technological outcome
> that totally changes everything.
> OK, let me see if I understand what you say. (1) Most people doing AI and
> AI risk are wrong about content and strategy. (2) Real AGI is model-less,
> something that just behaves. (3) The current risk conversation is about
> model-based AI, and (4) you think that approach is totally flawed. (5)  You
> are building a self-adapting hierarchical control system which you think
> will be the real thing.
> Assuming this reading is not too flawed:
> I agree with (1). I think there is a fair number of people who have
> correct ideas... but we may not know who. There are good theoretical
> reasons to think most AI-future talk is bad (the Armstrong and Sotala
> paper). There are also good theoretical reasons to think that there is
> great value in getting  better at this (essentially the argument in
> Bostrom's Superintelligence), although we do not know how much this can be
> improved.
> I disagree with (2), in the sense that we know model-less systems like
> animals do implement AGI of a kind but that does not imply a model-based
> approximation to them does not implement it. Since design of model-less
> systems, especially with desired properties, is very hard, it is often more
> feasible to make a model system. Kidneys are actually just physical
> structures, but when trying to make an artificial kidney it makes sense to
> regard it as a filtering system with certain properties.
> I agree with (3) strongly, and think this is a problem! Overall, the
> architectures that you can say sensible things about risk in are somewhat
> limited: neuromorphic or emergent systems are opaque and do not allow neat
> safety proofs. We need to develop a better way of thinking about complex
> adaptive technological systems and how to handle them.
> However, as per above, I do not think model-based systems are necessarily
> flawed, so I disagree with (4). It might very well be that less-model based
> systems like brain emulations are the ticket, but it remains to be seen.
> (5): I am not entirely certain that counts as being model-less. Sure, you
> are not basing it on some GOFAI logic system or elaborate theory (I
> assume), just the right kind of adaptation. But even the concept of control
> is a model.
> If you think your system will be the real deal, ask yourself: why would it
> be a good thing? Why would it be safe (or possible to make safe)?
> [ Most AGI people I have talked with tend to answer the first question
> either by scientific/engineering curiosity or that getting more
> intelligence into the world is useful. I buy the second answer, the first
> one is pretty bad if there is no good answer to the second question. The
> answers I tend to get to the second question are typically (A) it will not
> be so powerful it is dangerous, (B) it will be smart enough to be safe, (C)
> during development I will nip misbehaviors in the bud, or (D) it does not
> matter. (A) is sometimes expressed like "there are people and animals with
> general intelligence and they are safe, so by analogy AGI will be safe".
> This is obviously flawed (people are not safe, and do pose an xrisk). (A)
> is often based on underestimating the power of intelligence, kind of
> underselling the importance of AGI. (B) is wrong, since we have
> counter-examples (e.g. AIXI): one actually needs to show that one's
> particular architecture will somehow converge on niceness, it does not
> happen by default (a surprising number of AGI people I have chatted with
> have very naive ideas of metaethics). (C) assumes that early lack of
> misbehavior is evidence against late misbehavior, something that looks
> doubtful. (D) is fatalistic and downright dangerous. We would never accept
> that from a vehicle engineer or somebody working with nuclear power. ]
> {Now you know the answers I hope you will not give :-) }
> --
> Dr Anders Sandberg
> Future of Humanity Institute
> Oxford Martin School
> Oxford University
> _______________________________________________
> extropy-chat mailing list
> extropy-chat at lists.extropy.org
> http://lists.extropy.org/mailman/listinfo.cgi/extropy-chat
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