The article's commentary on the _Asian Disease_ problem which states "the number of certain deaths is the same in both versions of the problem.." is incorrect. In case A, the number of certain deaths is 400,000, in case B it's 0.
Or am I reading it incorrectly ?
My interpretation was that in the first situation, there is a possibility that everyone dies if you choose medicine A, therefore B was the right choice. Similarly, in the second situation, there is a possibility that everyone lives if you choose medicine A, therefore A was the right choice. Maybe I'm misunderstanding but there does not appear to be enough information in the question to determine the exact probabilities.
Medicine A will always save 200,000 people, with 400,000 dying.
Medicine B will save all 600,000 people 33.3% of the time, but everyone will die 66% of the time.
The expected number of deaths (the 'expected value' in game theory) is the same for both cases (200,000). Medicine A is easy to calculate (200,000 * 1.00 = 200,000). For Medicine B, the calculation is 600,000 * 0.33 + 0 * 0.66 = 200,000.
The idea is that the average number of deaths is the same for both cases; you are just trading the certainty of Medicine A (where you know you will save exactly 200,000) vs the chance to save everyone, but the risk of losing everyone.
"If you choose Medicine A, 400,000 people will die."
Tells you that 400k people will die if you choose medicine A. It says nothing about what will happen to the remaining 200k. I believe it is illogical to assume that the sentence implies the remaining 200k live. Note that if you were to ask me in real life, I'd probably be happy to make that assumption but that doesn't change the fact that it is an assumption based on missing information.
When you follow that by saying "If you choose Medicine A, 400,000 people will die", it is not illogical to assume that they don't mean "oh yeah, the other 200k will also die, too" This isn't a Mitch Hedberg joke.
In these scenarios, we are expected to make many basic assumptions that aren't included in the scenario. We are safe to assume that there isn't an unmentioned side effect of Medicine B that will leave everyone paralyzed, or that Medicine A won't turn the survivors into zombies.
His comedy was very hit-and-miss, but some of it was spectacularly funny.
I'm sure this form of problem analysis gives psychological experimenters fits.
see for eg:
And here is the problem framed in terms of gains:
If you choose Medicine A, 200,000 people will be saved. If you choose Medicine B, there is a 33.3% chance that 600,000 people will be saved and a 66.6% chance that no one will be saved.
Which medicine do you choose?
Although the number of certain deaths is the same in both versions of the problem, people take the safer option
The lack of scale prevents an analysis of proportionality.
For example:
600k out of 500,000,000? or 600k out of 1,000,000 or 1,000,000,000?
Given the downsides are equal, the omission begs the qeustion about the rate of success. The rate of success is not a trivial source of people's bias, because empirically "non-success" is often accompanied by adverse effects (a/k/a side effects) as well as additional cost. The result is a leading question. In other words, the language is manipulative.
But do we really need this study to tell us this? C'mon, that is stupid. And has nothing to do with Mandela.
The entire article is just a layer over this showing the supposed effects of asking the question in a foreign language (other comments have explained the likely problems of the experiment), and then another layer over that wrapping it in "this is totally relevant to you because Madiba".
I mean, yeah. Mandela was right. But not because of the foreign language effect.
The problem is that the rational answer to this depends on a huge amount of background information, eg, the value of certainly having some money, versus the benefit of the additional money.
Further, they account for stuff like that by using large sample sizes. Different people are choosing both options. It's just that the proportions hold despite this.
They've spent a good 30 years confirming this. If you really want to criticize it, it'd be worth putting together a list of studies investigating this and analyzing their methodologies for problems.
http://en.wikipedia.org/wiki/Framing_(social_sciences)#Frami...
B: 1/3 probability of 600k cures, 2/3 probability of 0 cures; expected value = 200k survivors
Of course, as software writers, we have probably been trained to analyze algorithms for expected performance and for the best and worst cases. Real-time programmers should always choose option A, as it has the best worst-case performance. Some programmers will choose A because it has lower computational complexity. Others will choose option B because it has better best-case performance, and in the worst case is no worse than doing nothing at all.
The scenario is supposed to be mathematically ambiguous, but the people who designed it obviously did not consider factors beyond just the average case and whether the numbers are framed positively or negatively.
You're reading it incorrectly. It's saying that the number of certain deaths is the same, whether it's phrased as "400,000 deaths" or "saving 200,000 people".