Building Phenomenological Bridges
Naturalized induction is an open problem in Friendly Artificial Intelligence (OPFAI). The problem, in brief: Our current leading models of induction do not allow reasoners to treat their own computations as processes in the world.
The problem's roots lie in algorithmic information theory and formal epistemology, but finding answers will require us to wade into debates on everything from theoretical physics to anthropic reasoning and self-reference. This post will lay the groundwork for a sequence of posts (titled 'Artificial Naturalism') introducing different aspects of this OPFAI.
AI perception and belief: A toy model
A more concrete problem: Construct an algorithm that, given a sequence of the colors cyan, magenta, and yellow, predicts the next colored field.

Colors: CYYM CYYY CYCM CYYY ????
This is an instance of the general problem 'From an incomplete data series, how can a reasoner best make predictions about future data?'. In practice, any agent that acquires information from its environment and makes predictions about what's coming next will need to have two map-like1 subprocesses:
1. Something that generates the agent's predictions, its expectations. By analogy with human scientists, we can call this prediction-generator the agent's hypotheses or beliefs.
2. Something that transmits new information to the agent's prediction-generator so that its hypotheses can be updated. Employing another anthropomorphic analogy, we can call this process the agent's data or perceptions.
Characterizing the superintelligence which we are concerned about
What is this “superintelligence” we are concerned about? In writing articles on FAI topics, I took the easy way out and defined the focus of attention as an AI that can far outdo humans in all areas. But this just a useful shortcut, not what we are really talking about.
In this essay, I will try to better rcharacterize the topic of interest.
Some possibilities that have been brought up include intelligences
- which are human-like,
- which are conscious,
- which can outperform humans in some or all areas,
- which can self-improve,
- or which meet a semi-formal or formal definition of intelligence or of above-human intelligence.
All these are important features in possible future AIs which we should be thinking about.But what really counts is whether an AI can outwit us when its goals are pitted against ours.
1. Human-like intelligence. We are humans, we care about human welfare; and humans are the primary intelligence which cooperates and competes with us; so human intelligence is our primary model. Machines that “think like humans” are an intuitive focus on discussions of AI; Turing took this as the basis for his practical test for intelligence
Future AIs might have exactly this type of intelligence, particularly if they are emulated brains, what Robin Hanson calls “ems.”
If human-like AI is the only AI to come, then not much will have happened: We already have seven billion humans, and a few more will simply extend economic trends. If, as Hanson describes, the ems need fewer resources than humans, then we can expect extreme economic impact. If such AI has certain differences from us humans, like the ability to self-improve, then it will fall under the other categories, as described below.
A Transhumanist Poem
**Note: I'm not a poet. I hardly ever write poetry, and when I do, it's usually because I've stayed up all night. However, this seemed like a very appropriate poem for Less Wrong. Not sure if it's appropriate as a top-level post. Someone please tell me if not.**
Imagine
The first man
Who held a stick in rough hands
And drew lines on a cold stone wall
Imagine when the others looked
When they said, I see the antelope
I see it.
Later on their children's children
Would build temples, and sing songs
To their many-faced gods.
Stone idols, empty staring eyes
Offerings laid on a cold stone altar
And left to rot.
Yet later still there would be steamships
And trains, and numbers to measure the stars
Small suns ignited in the desert
One man's first step on an airless plain
Now we look backwards
At the ones who came before us
Who lived, and swiftly died.
The first man's flesh is in all of us now
And for his and his children's sake
We imagine a world with no more death
And we see ourselves reflected
In the silicon eyes
Of our final creation
What I would like the SIAI to publish
Major update here.
Related to: Should I believe what the SIAI claims?
Reply to: Ben Goertzel: The Singularity Institute's Scary Idea (and Why I Don't Buy It)
... pointing out that something scary is possible, is a very different thing from having an argument that it’s likely. — Ben Goertzel
What I ask for:
I want the SIAI or someone who is convinced of the Scary Idea1 to state concisely and mathematically (and with possible extensive references if necessary) the decision procedure that led they to make the development of friendly artificial intelligence their top priority. I want them to state the numbers of their subjective probability distributions2 and exemplify their chain of reasoning, how they came up with those numbers and not others by way of sober calculations.
The paper should also account for the following uncertainties:
- Comparison with other existential risks and how catastrophic risks from artificial intelligence outweigh them.
- Potential negative consequences3 of slowing down research on artificial intelligence (a risks and benefits analysis).
- The likelihood of a gradual and controllable development versus the likelihood of an intelligence explosion.
- The likelihood of unfriendly AI4 versus friendly and respectively abulic5 AI.
- The ability of superhuman intelligence and cognitive flexibility as characteristics alone to constitute a serious risk given the absence of enabling technologies like advanced nanotechnology.
- The feasibility of “provably non-dangerous AGI”.
- The disagreement of the overwhelming majority of scientists working on artificial intelligence.
- That some people who are aware of the SIAI’s perspective do not accept it (e.g. Robin Hanson, Ben Goertzel, Nick Bostrom, Ray Kurzweil and Greg Egan).
- Possible conclusions that can be drawn from the Fermi paradox6 regarding risks associated with superhuman AI versus other potential risks ahead.
Further I would like the paper to include and lay out a formal and systematic summary of what the SIAI expects researchers who work on artificial general intelligence to do and why they should do so. I would like to see a clear logical argument for why people working on artificial general intelligence should listen to what the SIAI has to say.
Examples:
Here are are two examples of what I'm looking for:
The first example is Robin Hanson demonstrating his estimation of the simulation argument. The second example is Tyler Cowen and Alex Tabarrok presenting the reasons for their evaluation of the importance of asteroid deflection.
Reasons:
I'm wary of using inferences derived from reasonable but unproven hypothesis as foundations for further speculative thinking and calls for action. Although the SIAI does a good job on stating reasons to justify its existence and monetary support, it does neither substantiate its initial premises to an extent that an outsider could draw the conclusions about the probability of associated risks nor does it clarify its position regarding contemporary research in a concise and systematic way. Nevertheless such estimations are given, such as that there is a high likelihood of humanity's demise given that we develop superhuman artificial general intelligence without first defining mathematically how to prove the benevolence of the former. But those estimations are not outlined, no decision procedure is provided on how to arrive at the given numbers. One cannot reassess the estimations without the necessary variables and formulas. This I believe is unsatisfactory, it lacks transparency and a foundational and reproducible corroboration of one's first principles. This is not to say that it is wrong to state probability estimations and update them given new evidence, but that although those ideas can very well serve as an urge to caution they are not compelling without further substantiation.
1. If anyone is actively trying to build advanced AGI succeeds, we’re highly likely to cause an involuntary end to the human race.
2. Stop taking the numbers so damn seriously, and think in terms of subjective probability distributions [...], Michael Anissimov (existential.ieet.org mailing list, 2010-07-11)
3. Could being overcautious be itself an existential risk that might significantly outweigh the risk(s) posed by the subject of caution? Suppose that most civilizations err on the side of caution. This might cause them to either evolve much slower so that the chance of a fatal natural disaster to occur before sufficient technology is developed to survive it, rises to 100%, or stops them from evolving at all for being unable to prove something being 100% safe before trying it and thus never taking the necessary steps to become less vulnerable to naturally existing existential risks. Further reading: Why safety is not safe
4. If one pulled a random mind from the space of all possible minds, the odds of it being friendly to humans (as opposed to, e.g., utterly ignoring us, and being willing to repurpose our molecules for its own ends) are very low.
5. Loss or impairment of the ability to make decisions or act independently.
6. The Fermi paradox does allow for and provide the only conclusions and data we can analyze that amount to empirical criticism of concepts like that of a Paperclip maximizer and general risks from superhuman AI's with non-human values without working directly on AGI to test those hypothesis ourselves. If you accept the premise that life is not unique and special then one other technological civilisation in the observable universe should be sufficient to leave potentially observable traces of technological tinkering. Due to the absence of any signs of intelligence out there, especially paper-clippers burning the cosmic commons, we might conclude that unfriendly AI could not be the most dangerous existential risk that we should worry about.
View more: Next
= 783df68a0f980790206b9ea87794c5b6)
Subscribe to RSS Feed
= f037147d6e6c911a85753b9abdedda8d)