What are our domains of expertise? A marketplace of insights and issues

I work as a structural engineer in the aerospace industry. My main task involves finding out how load is redistributed throughout structural elements (basically an issue of the relative stiffness of the different load paths) and then checking components against their various failure modes to determine how close they are to failing in the different conditions they'll have to withstand. I also support related work, like determining accuracy of models based on flight data.

Rationality is related to my work in that determining how a model should be changed in light of flight test data (given the various sensors) is an elaborate application of Bayesian reasoning. Also, there is pressure to always "show the structure good", presenting the danger of writing your conclusion before you begin reasoning.

As a side interest, I like to learn about AI and any topic that I believe will provide insight on it, such as biology/evopsych, thermodynamics, consciousness, and information theory (the latter of which I've been deemed an expert on by Steven Landsburg, somehow). Information theory in particular looks like a fruitful topic to study because of the unifying vision it gives to all the others, and one of my projects has been to convert constraints of physical law into constaints on information, and I think it has enhanced my understanding of various topics.

My blind spot is in chemistry, especially organic, which I think would be helpful to learn as a case study in how a system can maintain very specific order against the 2nd law pressure, so knowing the nuts and bolts of how it works at the molecular level would be very helpful to me.

What is your main domain of expertise? (Your profession, your area of study, or even a hobby!)

I'm a games programmer, specializing in real-time 3D graphics. My degree is in Experimental Psychology and I maintain an amateur interest in that but don't have up to date domain expertise there.

What issues in your domain call most critically for sharp thinking?

Performance is a major concern in graphics programming (we have quite a lot of work to do in 33ms). Optimization in graphics requires both a deep understanding of the algorithms, programming language and hardware you are working with but also the ability to step outside the immediate problem and see creative shortcuts or workarounds that achieve the desired high level end result your artists are asking for by some alternative means.

Familiarity with the latest research in the offline rendering world is valuable but just as important is the ability to have an understanding of what attributes of a scene are important to human perception and a willingness to throw mathematical or physical correctness out the window to get the visual results you are after.

What do you know that could be of interest to the LessWrong community?

I think working a problem like 3D rendering with hard time constraints makes me more aware than average of the importance of tradeoffs between accuracy and timeliness. A brilliant technique that doesn't run in 1/30s on your target platform isn't nearly as useful as a creative hack that does. I tend to think that the value of a fast approximation over a slow exact result is sometimes underappreciated in discussions of AI and human rationality.

In terms of specific technical knowledge, the games industry has been ahead of most of the mainstream software industry in coming to grips with massively parallel hardware in the form of GPUs and novel parallel processors like the Cell in the PS3. This is potentially relevant to areas of interest to Less Wrong that require large amounts of computing power. I won't suggest AI specifically as the tendency to embrace shortcuts in graphics programming is perhaps not something that would be encouraged when creating an AI...

What might you learn from experts in other domains that could be useful in yours?

There are a lot of applications of compression in graphics. PCA was originally developed for statistical analysis and I believe has had some application in machine learning but is known in graphics as a compression technique. I suspect the connections between compression and learning are probably rather deep and profound.

Various somewhat esoteric bits of math have found their way into computer graphics. Quaternions are widely used as an efficient rotation representation and there is a fair amount of interest in geometric algebra. I imagine there are other useful areas of math that we could benefit from but that haven't come to the attention of the field.

We ruthlessly exploit any and every 'flaw' in human perception to optimize 3D graphics. If there's something that people tend not to notice we look for ways to avoid calculating it so we can use those cycles somewhere else. My Experimental Psychology background has been helpful in this regard.

"What is your main domain of expertise?"

I'll be starting grad school in math in the fall. I'm interested in the areas of applied math that deal with getting information from data -- when it's noisy, when it's high-dimensional, when it's uncertain. Way down the line, this is related to machine learning and image processing.

"What issues in your domain call most critically for sharp thinking?"

I think -- and I'm getting this impression not only from my own opinion but from professors I admire -- that we need to think more about philosophy of science and ask ourselves what, exactly, we're doing.

For example, consider an interdisciplinary problem about interpreting some biological data with computational techniques. A computer scientist will tend to look for solutions that treat the data as arbitrary strings, and "throw away" any physical significance, which means that he can only prove modest claims. A biologist will tend to use techniques that assume a lot of a priori knowledge about the specific experiment, and thus aren't generally applicable. Both extremes lack a nice quality of explanatory efficiency.

Especially when we're looking at data, and models to explain data, we're going to need to face the question "What makes an explanation good?" And my personal opinion is that philosophers of the LW variety can help.

"What do you know that could be of interest to the LessWrong community?"

Some mathematical concepts that I know are good metaphors or explanations for how we develop knowledge from data. Some are already familiar here (Bayesianism), and some possibly less so (PCA; diffusion geometry; entropy, in the information-theoretic sense; K-means clustering; random matrix theory.)

"What might you learn from other experts that might be useful in yours?"

Oh, god, where to begin. People who actually know how computers see/define/categorize would be invaluable (I'm only recently learning that I'm interested in questions posed in CS or EE, but I don't have much of a prior programming background.) Philosophers know what questions to ask. Statisticians know a lot about updating knowledge. Physics is where all the examples come from, and I don't know any physics. People in any line of work who have insights about how their own minds work can come up with ideas on how to make an algorithmic "mind" work.

Thank you for the invitation. I have lurked for some time but have recently written a few comments and intend to continue.

Expertize: I have worked in medical labs, research (genetic, biochemical, physiological, chemical) labs, computer support and analysis, lab management. I am now retired and on a pension. My hobby is neurobiology theorizing. I have been interested in this all my adult life because I am/was dyslexic.

Critical thinking domains in neurobiology: biological understanding of consciousness, memory, morals, communication.

What do I know: I can contribute a fair amount about how we think as opposed to how we think we think and I can bring a biological perspective to a blog that is heavy on the computer science, physics, economics and math areas. (I am also one of those rare females that do not react negatively to nerds.)

What can I learn: I have never read something by Eliezer and not felt I had learned something.

If you show me a photo of a non-modular analog synthesizer manufactured between the years 1971-1995, there is a good chance that I can name it and tell you how many oscillators it has.

I’ve been meaning to post on this thread because my background is apparently somewhat unusual here and I am happy to try to pitch in on questions where I may have some knowledge and experience. I majored in medieval history in college, went to law school, and worked in corporate defense litigation for most of the past eight years. (I do see that one other lawyer and one recent law grad have posted in this thread.) Most recently I’ve worked as a Visiting Fellow at SIAI.

I’m also female, which is also apparently unusual here. I used to really enjoy arguing/debate, but at this point, I find that I generally prefer collaborative and cooperative discussion.

I followed the Amanda Knox and the Cameron Todd Willingham posts and comments with some interest, but haven’t yet contributed. I am also mulling over some possible open thread comments or top-level posts related to rationality and the law, but they’re still very much in the idea stages.

I am also a long-time science fiction fan, which is probably more common here, although it was not as common among the SIAI folk as I had expected.

I'm an occasional commenter, not a lurker, but I tend to stay on the fringes of conversations.

What is your main domain of expertise?

I'm an economist and policy analyst working for the New Zealand government. So I have expertise in the operation of (one specific) government, economics and the policy development process.

What issues in your domain call most critically for sharp thinking?

In policy work, bad thinking can cost millions or even billions of dollars, and destroy lives. The more important something is, the more important rationality becomes when thinking about that thing.

What do you know that could be of interest to the LessWrong community?

I had been toying with the idea of writing an article discussing how to think about evidence in policy (an environment where evidence is often rare and low quality) and why I think Bayesian Rationality is much more useful than Traditional Rationality in an evidence-poor environment.

What might you learn from experts in other domains that could be useful in yours?

I don't really know, I read Less Wrong for entertainment as much as edification.

What is our main domain of expertise?

I'm a prosecutor. This requires... well, it's helped greatly by knowledge of many different subjects, though primarily law.

What issues in your domain call most critically for sharp thinking?

Mostly, it's just a general ability to absorb large amounts of information and put it together. Cross-examination requires very high-speed sharp thinking and some showtime skills.

What do you know that might be of interest to the LW community?

I'm sure some would be interested in how criminal law is practiced, but that's more than a post. If you've got specific questions, hey, I'm around.

What do you know that doesn't add much to the discussion?

This is longer.

Bayes' Theorem applies to decayed DNA hits, so that's useful. There's a generally-accepted view that lawyers think differently, but I think there's substantial cross-over from law-thinking to engineering-thinking, at least when it's done right.

In many cases, there are issues that are less technical and more generally psychological; I have only a little special expertise, but I can tell you that the guy who reported his car stolen who is missing his pants had something happen that is not difficult to deduce.

There are many areas where I'm expert enough for my job, but far from expert-expert. I'm quite familiar with collision reconstruction, and my physics background is sufficient to understand the math. I resuscitated some aged accounting knowledge (I wouldn't call it expertise, quite) for a trial a couple years ago.

What might you learn, assuming lawyers are capable of learning, from other LW'ers?

I know very little biology or medicine; I have to talk to people if there's a technical issue and I don't have enough knowledge to see when something's going wrong.

I don't have any serious problem attending autopsies, or viewing unpleasant photos of violent outcomes, but I find medical stuff really - to use a technical legal term - icky.

--JRM

What is your main domain of expertise?

In Germany there is a study course called industrial management which is half engineering and half business administration. The intend is to train students to understand both and coordinate business processes and technical processes. That would be my main domain of expertise. But I'm also a programmer and system administrator.

• What issues in your domain call most critically for sharp thinking?*

Business administration is not as simple as most managers seem to think. Instead a business administrator needs to understand what is going on and what results any taken measure will produce and what the constraints of any given methodology are.

What do you know that could be of interest to the LessWrong community?

I know economics, I understand how people interact inside organizations, I know some engineering.

I'm a postdoc working in a statistics group within a systems biology institute. In my PhD research I applied Bayesian statistics to the analysis of proteomics data. In terms of expertise, I accord myself journeyman status in statistical model formulation and in the implementation of MCMC algorithms to sample from a posterior distribution.

Most people commenting seem to be involved in science and technology (myself included), with a few in business. Are there any artists or people doing something entirely different out there?

To answer the main question, I am an MD/PhD student in neurobiology.

• What is your main domain of expertise? (Your profession, your area of study, or even a hobby!)

I have just finished degrees in law and philosophy, which I guess counts for some amount of expertise. I'm now studying both at graduate level. For the past three years or so, I've also been tutoring "traditional rationality" courses in philosophy. Before that, I was a high-school math tutor for about 8 years. Overall, I'd rate my teaching skills as somewhat higher-level than the areas I've studied formally.

I'm a bit of a generalist - I've also studied chinese, human biology, and mathematics.

• What issues in your domain call most critically for sharp thinking?

Legal and philosophical reasoning often deal with vaguely defined folk-concepts such as causation. Fitting these into good reasoning often means finding precise criteria to look for in the observable world.

Lawyers are also prone to emphasise persuasion, without necessarily being rational about it. Being trained to see both sides of an issue means we risk a failure to conclude based on evidence. It's easier to say "each side has arguments".

• What do you know that could be of interest to the LessWrong community?

I know that a few simple ideas in argumentation theory can be quite powerful in augmenting people's rationality. The course I've taught most often focuses on evaluating arguments, by performing two tasks: firstly assessing the "logical strength" of inferences, and secondly assessing the "plausibility of premises".

I also know that many students struggle to understand this simple rationalist tool. I suspect most who do understand it may not apply it outside the domain of passing-philosophy-exams.

• What might you learn from experts in other domains that could be useful in yours?

I'd like to know more about mathematical descriptions of reasoning. Statistical and probabilistic reasoning can be important in assessing legal liability, and I'm far from expert at this. Also, Bayesians seem to identify problems with "statistical significance" based on arbitrary p-value thresholds. Understanding this seems important to developing a rational philosophy of science, both academically and for myself.

What is your main domain of expertise?

Application and system administration of ERP software and computer operating systems.

What issues in your domain call most critically for sharp thinking?

Decision making and business process formulation.

What do you know that could be of interest to the LessWrong community?

Most problems are not technical in nature; they are problems with the people and the processes. This could mean you need to change the culture, you need to train people, you need to route things differently, or gain a better understanding of the workflow. Too many people say, "Let's implement a piece of software and that will make everything better." No, it won't. Stop listening to the marketers and sales people and start analyzing your processes.

Excellent idea for a thread.

I'm a moderately frequent commenter and very occasional poster here, reading since the beginning.

In the 1970s I studied pure mathematics as an undergraduate and theoretical computer science as a postgrad, and then worked in the latter field for some years. However, I now regard all the work I did there as a waste of time, despite the citation counts, and since around 1996 began to move into more practical areas.

I got interested in control theory and the particular subfield that has been the subject of most of my top-level posts here (intro), and have developed in physical simulation a walking robot based on those principles.

I've also developed software for script-driven real time procedural animation of human upper body movement as part of a project for animating deaf sign language. I think it works pretty well, and I'd love to extend it to more general animation for the obvious application area, video games -- with all respect to the deaf, animated sign language is very much a niche application. I haven't had time to seriously work on this, since what actually pays my salary at present is developing finite element methods and software for simulating biological organ growth.

I also wrote the article on artificial languages for the 3rd edition of the Routledge Linguistics Encyclopedia, and was the Klingon consultant for series 7 of "Big Brother". ghImlu'meH QaQ jaj vaghdich!

I'm currently studying stochastic calculus with a view to figuring out just what, if anything, classical control theory and Bayesian reasoning have to do with each other.

If this sounds like a resume touting for work, it's intended to. :-)

What a nice thread idea. I'm a first year grad student in "engineering physics". My research focus is plasma physics and magnetic confinement fusion, but right now I'm still mainly trudging through classes. My main expertise is in classical physics, mainly fluid mechanics, electrodynamics, and applied math.

What issues in your domain call most critically for sharp thinking?

In problem solving in our domain there is a need for sharp thinking, but I tend to think that this is actually just an illusion, and the really hard part comes outside of the actual calculations. In doing a calculation you have to kind of figure out what's going on, but usually if you know all the assumptions and the correct methods, this is just a matter of working out the details. The hard part is understanding what assumptions are valid, and knowing what to do when you get stuck.

What do you know that could be of interest to the LessWrong community?

General meta-level thoughts on math and science, mainly. These are philosophical and practical, in the sense of "Why are math and physics so connected?", or "Why is someone good at math?" or "What is the essential difficulty in doing this physics?" These are all questions I've thought about quite a bit in the course of my education.

What might you learn from experts in other domains that could be useful in yours?

I think there is stuff to learn in the basic meta-level philosophical and logical techniques that come into play in the forum, for example, when people break down other arguments or address flaws in reasoning. I wish I had more practice in things like basic logic and argumentation (e.g., the different types of argument.) It's very useful for physics and especially math, which relies on the fidelity of your reasoning process.

I'm not a lurker, but a regular commenter (and a 'top contributor' for the site's entire first year), but I'm not sure I've filled this in elsewhere...

What is your main domain of expertise?

Short list: computer ethics, web development, generalist philosopher

I'm not sure if I have anything I'd like to call 'expertise', but I'm about as well-versed as anyone on the computer ethics literature and I've a decent grasp of normative ethics and philosophical logic (though I've a growing distaste for the style of academic philosophy). When I'm not working on my dissertation, I'm doing web development as a day job, and side academic interests are the web, video games, new media, and transhumanism. In truth, I'm more of a generalist, so I (hopefully) can produce insights that insiders in a field would miss.

My (hopefully) forthcoming doctorate is in computer ethics; my dissertation is on how to build ethical robots. My undergraduate degree is in Philosophy, where I focused on ethics and computer ethics, and minored in asian studies and computer science.

I've been called a "serious academic" and put in the category "leading futurists and technologists", though I don't know which I find more dubious. And I don't think "one of the world's foremost Yudkowsky scholars" would be much of a stretch.

What issues in your domain call most critically for sharp thinking?

That's an odd question. I'm not sure if that's equivalent to "What issues in your domain are most critical" or "What issues in your domain are most likely to be corrupted by standard human failures of rationality" or some combination of the two.

The big problem that brought about the field of computer ethics is: New technology creates situations that our existing institutions (and intuitions) aren't built for, and so what should we do about it?

What might you learn from experts in other domains that could be useful in yours?

Being something of a generalist, I'm always hoping to be backed up by someone with more domain-specific knowledge.

I'm an assistant professor of mathematics at the University of Wyoming. I specialize in discrete geometry, especially geometry and combinatorics of polyhedra. Maelin already gave a good account of the way in which mathematics calls upon (or does not call upon) rationality.

I also have a pretty good amateur's familiarity with contemporary philosophy in the analytic tradition and with the philosophy of mathematics.

Main area of expertise? I have completed a degree in Science with an extra Honours year, majoring in pure mathematics (especially abstract algebra) and with a hefty side serving of formal logic and computer programming as well. I arrived at mathematics after planning to study physics, leaving high school, finding physics to be terribly taught and full of things that I now realise at the time I lacked the mental sophistication for, and realising I found the maths more interesting.

Last year and this year have been dedicated first to earning money, now to travelling around Europe, and soon to earning money again. Next year I will begin studying teaching with the intent of becoming a high school maths teacher. I've spent a few years tutoring in mathematics and also worked part-time as a teacher's aide for a semester last year.

What demands sharp thinking? Sharp thinking is pretty vital in pure mathematics but it's probably not something that needs to be consciously practised so much, owing to the already rigid structure of mathematics. Whilst I'm confident that rationality is valuable in teaching, I'm not entirely sure I could verbalise exactly how. I have a talent for explaining things and I enjoy explaining mathematics, which is the main reason I'm going into teaching. I can't think of any examples of ways that being a sharp rationalist will be -directly- helpful although some may exist.

I am a regular commenter, evidently, but I am also a mechanical engineering grad student with a focus on thermal management of electronic packaging. Most of what I do ranges from applied Newtonian physics to empirical modeling.

I am also a webcomics nerd - I enjoy the medium, and as a consequence have learned a few things both about fandom communities and about the business of webcomicking.

My main domain of expertise is quantum information theory, encompassing quantum physics, but focusing on what types of information processing this makes both possible, and efficient, for various values of efficient.

I'm also well-schooled in a variety of math, and have experience in programming, Unix systems administration, and asynchronous hardware design.

EDIT: My credentials: I have undergraduate degree in physics from Caltech, and I'm currently working on my PhD thesis (ABD) at UNM.

Any expertise in overcoming physical disabilities to communicate/interface with the world more effectively?

Well, not a complete lurker, posted a couple of thoughts following the rabbinical dictum of "the bashful shall not learn" - I have sizable if somewhat weird jewish orthodox background. I guess that is a domain of expertise by itself.

More recently I made a career switch from general programming to reporting to data mining types of stuff (this was a planned transition over 3 years). Still way behind on many mathy things but know enough to be useful to my employer. Learned pretty much everything myself, though I have gone to a low-quality college while being a "non-degree rabbinical student" (a yeshiva bachur not aiming for smicha in the lingo).

I don't have any rational superpower yet, but search for truth and some fortuitous accidents brought me thus far, so who knows ;)

I'm an applied mathematician. I am finishing my PhD on natural language processing. I worked on many industry projects, some relevant keywords are data mining, text mining, network analysis, speech recognition, and optimization on spatial data.

Years ago I learned computational complexity theory. Occasionally I still teach it at my old university. After the PhD, my next plan is to finish my problem book on computational complexity. The computational complexity approach to problems influences everything I do.

I love my work, but frankly, I don't come to LW to talk about data mining. I believe my hobbies and side projects are more relevant and interesting here. I have two hobby projects that should really be tackled by physicists. I hope I don't deviate too much from the spirit of this thread if I answer the "What might you learn from experts in other domains that could be useful in yours?" by introducing my projects as questions to physicists:

1. Let us assume that you an all-powerful optimization process, and your goal is to finish an extremely long computation (say, a search for a very large Hamiltonian cycle) in the shortest possible amount of time. You have millions of galaxies to turn into computronium. What is the optimal expansion speed of your computer, considering our current understanding of particle physics, general relativity and thermodynamics?

2. Of all the possible Universes in Tegmark's level IV Multiverse, most don't even have a concept of Time. How can we decide whether or not a specific Universe is in fact a Space-Time Continuum?

sociology phd student. too much of a generalist for my own good. compared to the people at this site my comparative advantage is probably my understanding of public policy (especially education policy), economics, survey design and analysis, applied statistics, and of course sociology.

Cryptography and sexual politics.

What is our main domain of expertise?

I'm a prosecutor. This requires... well, it's helped greatly by knowledge of many different subjects, though primarily law.

What issues in your domain call most critically for sharp thinking?

Mostly, it's just a general ability to absorb large amounts of information and put it together. Cross-examination requires very high-speed sharp thinking and some showtime skills.

What do you know that might be of interest to the LW community?

I'm sure some would be interested in how criminal law is practiced, but that's more than a post. If you've got specific questions, hey, I'm around.

What do you know that doesn't add much to the discussion?

This is longer.

Bayes' Theorem applies to decayed DNA hits, so that's useful. There's a generally-accepted view that lawyers think differently, but I think there's substantial cross-over from law-thinking to engineering-thinking, at least when it's done right.

In many cases, there are issues that are less technical and more generally psychological; I have only a little special expertise, but I can tell you that the guy who reported his car stolen who is missing his pants had something happen that is not difficult to deduce.

There are many areas where I'm expert enough for my job, but far from expert-expert. I'm quite familiar with collision reconstruction, and my physics background is sufficient to understand the math. I resuscitated some aged accounting knowledge (I wouldn't call it expertise, quite) for a trial a couple years ago.

What might you learn, assuming lawyers are capable of learning, from other LW'ers?

I know very little biology or medicine; I have to talk to people if there's a technical issue and I don't have enough knowledge to see when something's going wrong.

I don't have any serious problem attending autopsies, or viewing unpleasant photos of violent outcomes, but I find medical stuff really - to use a technical legal term - icky.

--JRM

I've amassed quite a bit of knowledge about conspiracy theories and geopolitics. Regarding 9/11 I think I have a fairly good understanding of what went on behind the scenes.