Here at Less Wrong, the Future of Humanity Institute and the Singularity Institute, a recurring theme is trying to steer the future of the planet away from disaster. Often, the best way to avert a particular disaster is quite hard for ordinary people to understand as it requires one to think through an argument in a cool, unemotional way; more often than not the best solution will be lost in a mass of low signal-to-noise ratio squabbling and/or emoting. Whatever the substance of the debate, the overall meta-problem is quite well captured by this catch from this month's rationality quotes:
"People are mostly sane enough, of course, in the affairs of common life: the getting of food, shelter, and so on. But the moment they attempt any depth or generality of thought, they go mad almost infallibly.
Attempting to target the meta-problem of getting people to be slightly less mad when it comes to abstract or general thought, especially public policy, is a tempting option. Robin Hanson's futarchy proposal is one way to combat this madness (which it does by removing most people from the policymaking loop). However, another important route to combating human idiocy is to find technologies that make humans smarter. Nick Bostrom proposed that we should work hard looking for ways to enhance the cognition of research scientists, because even a small increase in the average intelligence of research scientists would increase research output by a large amount, as there are lots of scientists. But improving the decisionmaking process of our society would probably have an even more profound effect; if we could improve the intelligence of the average voter by about one standard deviation, it is easy to speculate that the political decisionmaking process would work much better. For example, understanding simple logical arguments and simple quantitative analyses is stretching the capabilities of someone at IQ 100, so it seems that the marginal effect of overall IQ increases would be quite a large marginal increases in the probability that a politician was incentivized to focus on a logical argument over an emotionally appealing slander as the main focus of their campaign.
As a concrete example, consider the initial US reaction to rising oil prices and the need for US-produced energy: pushing corn ethanol, because a strong farming lobby liked the idea of having extra revenue. Now, if the *average voter* could understand the concept of photosynthetic efficiency, and could understand a simple numerical calculation showing how inefficient corn is at converting solar energy to stored energy in ethanol, this policy choice would have been dead in the water. But the average voter cannot do simple physics, whereas they can understand the emotional appeal of "support our local farmers!". Even today, there are still politicians who defend corn ethanol because they want to pander to local interest groups. Another concrete example is some of the more useless responses that the UK public has been engaging in - and being encouraged to engage in - to prevent global warming. People were encouraged to unplug their mobile phone chargers when the chargers weren't being used. David McKay had to wage a personal war against such idiocy - see this Guardian article. The universal response to my criticism of people advocating this was "it all adds up!". I quote:
There's a lack of numeracy in the public discussion of energy. Where people do use numbers, they select them to sound big and score points in arguments, rather than to aid thoughtful discussion.
Toby Ord has a project on efficient charity, he has worked out that the difference in outcomes per dollar for alleviating human suffering in Africa can vary by 3 orders of magnitude. But most people in the developed world don't know what an "order of magnitude" is, or why it is a useful concept. This efficient charity concept demonstrated that the derivative
d(Outcomes)/d(Average IQ)
may be extremely large, and may be subject to powerful threshold effects. In this case, there is probably an average IQ threshold above which the average person can easily understand the concept of efficient charity, and thus all the money gets given to the most efficient charities, and the amount of suffering-alleviation in Africa goes up by a factor of 1000, even though the average IQ of the donor community may only have jumped from 100 to 140, say.
It may well be the case that finding a cognitive enhancer suitable for general use is the best way to tackle the diverse array of risks we face. People with enhanced IQ would also probably find it easier (and be more willing) to absorb cognitive biases material; to see this, try and explain the concept of "cognitive biases" to someone who is unlucky enough to be of below average IQ, and then go an explain it to someone who is smarter than you. It is certainly the case that even people of below average IQ *do sometimes*, in favourable circumstances, take note of quantitative rational arguments, but in the maelstrom of politics such quantitative analyses get eaten alive by more emotive arguments like "SUPPORT OUR FARMERS!" or "SUPPORT OUR TROOPS!" or "EVOLUTION IS ONLY A THEORY!" or "IT ALL ADDS UP!".
1) Mathematica's programming language does not confine you to a particular style of thinking. If you are a Lisp fancier, you can write entirely Lispy code. Likewise Haskell. There is even a capability for relatively painless dataflow programming.
2) Wolfram Inc. took great pains to make interfacing with the outside world from within the app as seamless as possible. For example, you can suck in a spreadsheet file directly into a multidimensional array. There is import and export capability for hundreds of formats, including obscure scientific and engineering ones. In case the built-in formats do not suffice, defining custom ones is surprisingly easy.
3) A non-headache-inducing replacement for regular expressions. Enough said.
4) Graphical objects (likewise audio and other streams) are first-class data types. They are able to appear as both the inputs and outputs of functions.
5) Lastly, and most importantly: fully interactive program development. The rest of the programming universe lives a life of endlessly repeated "compile and pray" cycles. Mathematica permits you to meaningfully evaluate and edit in place every line of code you write. I am otherwise an Emacs junkie, yet I have never felt the slightest desire to touch Emacs when working on Mathematica code. The programmer's traditional need to wade through and shovel giant piles of text from one place to another while writing code is almost entirely absent when working in this language.
The downsides of Mathematica (slow, proprietary, expensive, etc.) are widely known. Thus far, the advantages have vastly outweighed the problems for my particular kind of work. However, I have found that I now feel extremely confined when forced to work in any other programming language. Perhaps this risk should be added to the list of disadvantages.
Wolfram had (at least in the early days of Mathematica) a very interesting relationship with Lisp. He seems to have initially rejected many of its ideas, but it is clear that they somehow crept back into his work as time went by.