What is discussion all about?

I find intriguing, and to some degree disappointing, that so many people I know have such a hard time understanding what is a discussion about. The confrontation of ideas is more often than not perceived as a personal attack, directed at one's personal belief. People tend to misunderstand the meaning of Ad Hominen attacks, while their ideas are being confronted, in the two possible ways: they either think the confrontation is personal, or they use the ad hominen subterfuge to gain leverage in the discussion. This usually only leads to frustration (which leads to the dark side).

In this sense, I found this TEDTalk enlightening. Philosopher Daniel Cohen, explains what exactly is the kind of argument I'm ranting about, the conceptual metaphor called "Argument as War" (more on this here). In this metaphor, the debate is perceived as a combat between points of view (represented, of course, by the debaters).

To win the debate, is to reduce the opponent to either agreeing with your point of view, or making him/her doubt himself/herself enough to give up arguing against you. The alternative, of course, is losing the debate, in which case you are forced either to change your point of view, or agree that your argumentation is just not good enough to keep discussing.

The most valid point he makes is: what do we gain, cognitively, by winning? Nothing. Except, of course, for a short ego massage. The person that actually gains something is the one that loses the argument, in the sense that he/she learns enough of the subject to change his/her mind.

My only addition to this interpretation is that we also learn things about the subject during the debate, no matter what the outcome. Whenever we confront our ideas, perspectives and points of view with another's, we have the chance of learning whatever facts or impressions they have on the subject that led to their different conclusion.

I like to think I always learn something in a good discussion, no matter if someone wins, or it ties. This is what drives me, and why I love a good debate.

Positive negation, negative affirmation, or else?

It is easy to notice that our cognitive abilities have much less problem processing a positive than a negative assertion. That is, it is just plain easier to understand that something is right, than saying something is not wrong, specially in long discourses like a mathematical demonstration, a lecture, thesis or paper.

I think this is the reasoning behind most lists on how to fail at something: instead of saying "don't these otherwise you you fail", one says that "do these in order to fail", often in a satirical mood. Interesting examples include a book called How to Fail: The Self-Hurt Guide, and this quick guide to fail in biology fields.

Scientific fields don't fall short of this trend, though. For example, an article was published last year entitled How Not to be a Bioinformatician. Rob Hyndman, in his blog (which I recently discovered looking for some LaTeX examples), has the post How to fail a PhD.

To contradict this trend, he also compiled the straightforward guide called How to avoid annoying a referee (which anybody in the scientific business should read and follow), expanding from this post in stats.stackexchange.com (which, in turn, follows the mindset described so far).

Of course one does not necessarily need to write guidelines in a jocular manner. One such (must-read) example is 1990's article from Gopen and Swan called The Science of Scientific Writing, in which they convey that most of the effort in communicating a result lies on the writer, and should not be deferred to the reader.

I find myself amused by the positive "how to fail" guides, though. They can make the point they want to address, while using a lighter tone. Maybe these are better ways of planting the seed of understanding something important, without taking the change of being perceived as boring.

Stochasticity x Determinism in elementary math

Most of the problems I'm having in studying theoretical topics nowadays stem from the fact that I've had null measure content of Statistics as a math student. I've seen interesting topics as Analysis, and Differential Geometry in undergrad, and useful stuff like Linear Algebra and Computational Linea Algebra in the masters course, but absolutely no Probability and Inference.

Nothing related to Data (not the android) at all. And this is mostly my fault. I knew before the Masters Course I wouldn't be pursuing a PhD in Math, and I knew my Math teachers wouldn't deal with topics I would most likely need in the near future (the one I'm living now).

I'm chasing the lost time, with books in Bayesian Data Analysis and Inference, but I although most of the times I understand what I read, I never seem to grok it. I will, certainly, in time, but time is a commodity a grad student doesn't have - I need Statistics now. As well as Biology, Ecology, Evolutionary Biology, and (why not?) a little Computer Science. So it's fair to say I'm chasing the lost time, and losing.

Prior to leaving I've seen the creation of a new undergrad course, Applied Math, in my former University; it started with concentrations in Finances, Mathematical Biology and Scientific Computing, and it soon became obvious to the faculty that some basic knowledge in Probability and Inference were a must, so it's been introduced as obligatory courses for all concentrations. My former advisor there told me he thought it was overkill at first but soon (in the first year or so) realized how suitable it was.

This is why I think it's a terrific idea (definitely worth spreading) this nice Arthur Benjamin fella presented on this talk on TED.



Obviously I don't think you should rip out everything related to Calculus (I like it, after all :) ). If you are really to grok Probability, you need a strong base in Calculus (from integrals, to maximizing Likelihood functions). But a change in paradigm is definitely well deserved. Our modern western societies are still studying according to old rules. Rules that fit well to the time and reality where they were idealized, but probably are just outdated now. We are a new society on overdrive, with a new (still changing) set of moral rules, new problems and challenges, new perspectives, new age limits. Why stick with the 19th century education philosophies? At least let's realize it's about time to discuss if it's worth changing it. See also another TED talk on this subject.

This all also brings an old question I've always had: is it a good thing that education curricula should be centralized? It's good to know beforehand what people must (might? should?) have learned looking at their curriculum. I'ts useful for the teacher/professor to know what to expect the student to know, and this also applies to the student. I've been bitten before, when the pre-requisites for a course weren't clear. I also have first hand experience of how good and dynamic an improvised class can be, when given by a motivated (and skilled) professor. OTOH, I also have firsthand experience in improvised classes that sucked.

Which is the lesser evil?

\pi = 3.0. Exactly.

Nothing to say about this. How can people even take anything for granted, surrendering their own indivituality? Free will, anyone?

creativity@TED

This presentation has got to be the funniest TED talk (if not, please provide a link in the comments).

But this of course is just a bonus point, because as most (or all) TED talks, this one's very insightful.

This is a talk by Sir Ken Robinson (wkp), about creativity, particularly how our typical school systems undermine most of the innate creativity children have.

"(...) the whole purpose of public education, throughout the world, is to produce university professors"




He goes on to say (after a few good jokes about university professors) why this is so. It appears that that our public education in a whole is centered about the idea of academicability. I still have to sleep on that for a while, but maybe this is one of those cases where something is too obvious to be noticed.

It was around the 19th century that public education was "invented (...) to meet the needs of industrialism". He goes on with other interesting insights, but there's enough spoilers from me for now.


On a related video, another good tip for those of you who like to think about creativity. Here's Amy Tan (wkp).



Of course, I still want to know what Creativity *really* is, which always brings me to what the hell Intelligence realy is. A friend of mine is now completely obsessed with AGI, and thanks to a tip I gave him from a Scientific American podcast, Singularity (wkp), so probably in a while I'll have some insights from him about these interesting topics.