I am the co founder of and researcher at the quantitative long term strategy organization Convergence (see here for our growing list of publications). Over the last eleven years I have worked with MIRI, CFAR, EA Global, Founders Fund, and Leverage, and done work in EA strategy, fundraising, networking, teaching, cognitive enhancement, and AI safety research. I have a MS degree in computer science and BS degrees in computer science, mathematics, and physics.
JustinShovelain
I’ve decided to try modelling testing and contact tracing over the weekend. If you wish to join and want to ping me my contact details are in the doc.
I think virus inactivation is a normal vaccination approach and is probably being pursued here? The hardest part is probably growing it in vitro at scale and perhaps ensuring that all of them are inactive.
Nice deduction about the relationship between this and conflict vs mistake theory! Similar and complementary to this post is the one I wrote on Moloch and the Pareto optimal frontier.
How so? I don’t follow your comment’s meaning.
Edited to add “I” immediately in front of “wish”.
By new “term” I meant to make the clear that this statement points to an operation that cannot be done with the original machine. Instead it calls this new module (say a halting oracle) that didn’t exist originally.
Are you trying to express the idea of adding new fundamental “terms” to your language describing things like halting oracles and such? And then discounting their weight by the shortest statement of said term’s properties expressed in the language that existed previously to including this additional “term?” If so, I agree that this is the natural way to extend priors out to handle arbitrary describable objects such as halting oracles.
Stated another way. You start with a language L. Let the definition of an esoteric mathematical object (say a halting oracle) E be D in the original language L. Then the prior probability of a program using that object is discounted by the description length of D. This gives us a prior over all “programs” containing arbitrary (describable) esoteric mathematical objects in their description.
I’m not yet sure how universal this approach is at allowing arbitrary esoteric mathematical objects (appealing to the Church-Turing thesis here would be assuming the conclusion) and am uncertain whether we can ignore the ones it cannot incorporate.
Interesting idea.
I agree that trusting newly formed ideas is risky, but there are several reasons to convey them anyway (non-comprehensive listing):
To recruit assistance in developing and verifying them
To convey an idea that is obvious in retrospect, an idea you can be confident in immediately
To signal cleverness and ability to think on one’s feet
To socially play with the ideas
What we are really after though is to asses how much weight to assign to an idea off the bat so we can calculate the opportunity costs of thinking about the idea in greater detail and asking for the idea to be fleshed out and conveyed fully. This overlaps somewhat with the confidence (context sensitive rules in determining) with which the speaker is conveying the idea. Also, how do you gauge how old an idea really is? Especially if it condenses gradually or is a simple combination out of very old parts? Still… some metric is better than no metric.
Vote this down for karma balance.
- 14 Mar 2010 8:23 UTC; 9 points) 's comment on Open Thread: March 2010, part 2 by (
Vote this up if you are the oldest child with siblings.
Vote this up if you are an only child.
Vote this up if you have older siblings.
Poll: Do you have older siblings or are an only child?
- 4 Dec 2011 20:59 UTC; 11 points) 's comment on 2011 Survey Results by (
I’m thinking of writing up a post clearly explaining update-less decision theory. I have a somewhat different way of looking at things than Wei Dia and will give my interpretation of his idea if there is demand. I might also need to do this anyway in preparation for some additional decision theory I plan to post to lesswrong. Is there demand?
Closely related to your point is the paper, “The Epistemic Benefit of Transient Diversity”
It describes and models the costs and benefits of independent invention and transient disagreement.
Why are you more concerned about something with unlimited ability to self reflect making a calculation error than about the above being a calculation error? The AI could implement the above if the calculation implicit in it is correct.
What keeps the AI from immediately changing itself to only care about the people’s current utility function? That’s a change with very high expected utility defined in terms of their current utility function and one with little tendency to change their current utility function.
Will you believe that a simple hack will work with lower confidence next time?
I’ll be there.
Hmm, darn. When I write I do have a tendency to see what ideas I meant to describe instead of seeing my actual exposition; I don’t like grammar checking my writing until I’ve had some time to forget details, I read right over my errors unless I pay special attention.
I did have a three LWers look over the article before I sent it and got the general criticism that it was a bit obscure and dense but understandable and interesting. I was probably too ambitious in trying to include everything within one post though, length vs clarity tradeoff.
To address your points:
Have you not felt or encountered people who have the opinion that our life goals may be uncertain, something to have opinions about, and are valid targets for argument? Also, is not uncertainty of our most fundamental goals something we must consider and evaluate (explicitly or implicitly) in order to verify that an artificial intelligence is provably Friendly?
Elaborating on the second statement, when I used “naturalistically” I wished to invoke the idea that the exploration I was doing was similar to classifying animals before we had taxonomies, we look around with our senses (or imagination and inference in this case) and see what we observe and lay no claim to systematic search or analysis. In this context I did a kind of imagination limited shallow search process without trying to systematically relate the concepts (combinatorial explosion and I’m not yet sure how to condense and analyze supergoal uncertainty).
As to the third point, what I did in this article is allocate a name “supergoal uncertainty”, roughly described it in the first paragraph and hopefully brought up the intuition, and then subsequently considered various definitions of “supergoal uncertainty” following from this intuition.
In retrospect, I probably errored on the clarity versus writing time trade-off and was perhaps biased in trying to get this uncomfortable writing task (I’m not a natural writer) off my plate so I can do other things.
I like the distinction that you’re making and that you gave it a clear name.
Relatedly, there is the method of Lagrangian multipliers for solving things in the subspace.
On a side note: there is a way to partially unify subspace optimum and local optimum by saying that the subspace optimum is a local optimum with respect to the local set of parameters you’re using to define the subspace. You’re at a local optimum with respect to defining the underlying space to optimize over (aka the subspace) and a local optimum within that space (the subspace). (Relatedly, moduli spaces.)