The remembering self vs the experiencing self

by Ian Pollock

I’ve just finished Daniel Kahneman’s book Thinking, Fast and Slow, which everybody needs to read. One of the useful concepts that he analyzes, which I believe I first heard from Dan Ariely, is the distinction between the remembering self and the experiencing self.

Following Kahneman’s presentation, think for a moment about where you would go on vacation if you could leave right now and money were no object. Why would you go there?

What comes to my mind is a hike along the East Coast Trail in Newfoundland. It’s been a few years since I’ve done any serious backpacking, so I suppose that I’m itching for a bit of challenge.

Now another question: where would you go if you could leave right now, money were no object, but your memory of the vacation would be erased when you returned?

I’m guessing that your choice under these circumstances is far more simply hedonistic – I’m inclined to choose some tropical beach destination.

According to Kahneman and others, this disparity reflects a difference in our preferences between a here-and-now preferrer — the experiencing self — that wants this pleasure to continue and this pain to cease, and a storyteller — the remembering self — that looks at an experience as a whole and evaluates its worth, with special attention paid to the beginning, climax and ending.

The difference between the two gets even more obvious (and creepy) when we consider suffering.

During a painful medical procedure, a patient is asked at regular intervals (say, every few minutes) to rate their pain level on a scale of 0 to 5. Then, afterward, they are asked to rate the painfulness of the procedure as a whole. [Note: I am making up these numbers, but they conform to the general pattern observed in actual experiments.]

Person A’s ratings:
2 4 5 5 5 5 5 5 5 5 5 5 4 4 3 2 1 1 0
Person B’s ratings:
2 3 3 3 3 3 4 5 5 5 0

Which of these people gives a higher pain-rating for the experience as a whole?

Well, the naïve answer is that Person A experienced more moments of pain, of greater intensity than Person B, so it stands to reason that they will rate the experience as a whole as worse. Readers with calculus could even say that the “suffering under the curve” is higher for Person A.

And yet, in such situations, Person B consistently rates their experience as worse — mainly because it ends on a bad note. Duration is totally neglected. “Total suffering” is thus not simply an integral of moment-to-moment suffering - or at least it’s not reported in that way. As Dan Ariely has noted, this helps explain the commonplace fact that most of us actually prefer to have a band-aid slowly peeled off, rather than “getting it over with.” Our remembering selves see the former as a less bad experience, even as our experiencing selves suffer for twice as long with pain that is not much less.

The creepy comes in when people are asked whether it would be acceptable to them to have an operation without anesthetic, so long as they do not remember it. According to Kahneman, many people (including himself) are all right with that, showing extreme callousness toward their experiencing selves! (I happen to lack whatever intuition is driving this phenomenon — I’m quite protective of my experiencing self.)

Of course, the remembering self is not always cast as the bad guy. I suspect most of us will have had the odd day on which all of our considered plans were dropped because of some hedonistic distraction — say, watching an entire season of Game of Thrones in one’s housecoat while wolfing down snacks (speaking purely hypothetically, of course). Here the experiencing self has triumphed over the remembering self. (Incidentally, there is interesting philosophical work here in figuring out the relationship of the remembering vs. experiencing selves to eudaimonia vs. akrasia.)

So far, this article has been a mere rehash of some cognitive psychology results. I want to start exploring the broader implications of this distinction. One of the areas that it seems worth applying to is ethical philosophy; specifically the contrast between virtue ethical and consequentialist strains of thought.

For virtue ethics, the point of morality is to help you to be a better, happier person. Here, happiness is emphatically not understood in the popular modern way as a mere persistent good mood. On the contrary, happiness (or eudaimonia) involves living an ethically good life, with close ties to friends and family, and strong community involvement. A lifetime of good deeds and fine company could be undone by your child’s turning out to be a villain, even if it were not your fault — hence, Solon says “call no man happy until he is dead.”

Meanwhile, consequentialism (particularly its subspecies, utilitarianism) seeks to maximize welfare or utility across all beings. In utilitarianism this gets defined as the balance of pleasure over pain, or some such concept. The definition of utility is always vexatious, but needn’t concern us overmuch here — the point is that almost all plausible consequentialist theories care quite a lot about moment-to-moment mental states like pleasure and pain.

I suspect you may be able to see where I am going with this. Virtue ethics is speaking directly and pretty much exclusively to the remembering self, while utilitarianism is much more friendly to the experiencing self. Is this a defect in one, or in both of these theories?

My tentative answer is that I am sympathetic to virtue ethics’ regard for the ethically substantial dimensions of human happiness — it stands in flattering contrast to the shallowness of popular culture’s “whatever makes you happy” nostrums.

And yet I am also skeptical about the normative importance of the kind of factors that people focus on when they discuss the “good life.” Recall Solon’s quote above — “call no man happy until he is dead.” To anybody with utilitarian leanings, this sounds pretty absurd. In the drama ‘House, MD,’ a character gives up a virtuoso career that is making her miserable. When a doctor asks her whether she’ll feel regret on her deathbed, she replies “You're going to spend one day of your life on your deathbed; the other 25,000 are the ones we should be worrying about.” Surely there is also something right about this!

Now we change the subject to a new econometrics fad: happiness measurement. This new trend has been dogged with controversy since the beginning. Some months ago, Massimo, myself and a couple of others had a conversation about it, in which I defended the idea as a worthwhile metric, on the grounds that it’s good to know how human misery and satisfaction correlate with other things, while Massimo expressed strong skepticism. Our positions then matched up fairly well with those of Julian Baggini (Massimo) and Richard Layard (your correspondent) in this debate on the subject.

I still think Baggini and Massimo’s fears about totalitarian abuses of the happiness metric are pretty histrionic, but I’m willing to eat a little bit of crow: they have a very good point about how problematic and philosophically indeterminate the measurement itself is. The UK asks the question in terms of “satisfaction with your life overall.” Massimo and Baggini’s point, I think, was that to move from this rating to a judgment of whether people are living good lives or not is an immense exercise in philosophical hand-waving. A person could be very satisfied but living a bad life in an ethical sense, or vice versa.

Now we can add to that worry an additional one — what about the poor, neglected experiencing self?

By tailoring the question exclusively to the remembering self (“satisfaction with your life overall”), the census-takers guarantee the result to be influenced by an inner narrative of respondents’ lives, rather than by any actually experienced mental state. For example, one can imagine someone who is altogether miserable moment-to-moment (say, a mother of 10 with an unsupportive husband), but has so internalized cultural norms of motherhood as the be-all-end-all of happiness, that she reports strong life satisfaction — every item on her “good life” checklist is checked off!

Also of particular interest is the relation of happiness to income, and a very famous result shows that this relation is linear at first, then plateaus; in other words, poor people report being unhappy, middle-income people are happier than poor people, but rich people are only a tiny bit happier than middle-income people. This does not merely reflect diminishing marginal utility of money — the curve is flatter than that consideration alone would lead us to expect.

However, here we have a similar problem. We are asking the remembering self, not the experiencing self, about “overall life satisfaction.” The remembering self reports its level of happiness based on a narrative of life so far (“Well, I’ve got a house, kids, a good job…”).  But the trouble is that a salary of $100,000 as opposed to $200,000 doesn’t fit well into a narrative, so it probably gets neglected. We still need to know whether a year in the life of a rich person contains more pleasurable person-moments than a year in the life of a middle-income or poor person.

Accordingly, I propose this as a useful experiment: use the standard experienced-happiness test of giving people pagers set to go off at random intervals. When they go off, the respondents note their mental state and report it shortly thereafter. Apply this experimental procedure to income levels. I (falsifiably) predict that the correlation between income and happiness will get stronger, though there is probably still a plateau (money really does have diminishing marginal utility).

And perhaps this type of happiness measurement should also be used in addition to, or in replacement of, national happiness measurements such as the one mentioned above. Certainly, it has a claim to be more objective than “life satisfaction,” inasmuch as it asks people about their mental states at the time, rather than the former, much more narrative-dependent question.

I acknowledge that this post is somewhat inchoate; in my defense, I mean it more as a call to conversation than as a well-ordered thesis. Can you think of any other relevant applications of the remembering self / experiencing self distinction? Do you think it’s overblown? What are your feelings on my tentative conclusions?

Ian’s Picks

by Ian Pollock

* Paul Krugman (a bit dated but still good) on Ricardo’s law of comparative advantage, which makes nonsense of a lot of economic nostrums on the left and right. A great quote from Krugman:

“There is nothing that plays worse in our culture than seeming to be the stodgy defender of old ideas, no matter how true those ideas may be. Luckily, at this point the orthodoxy of the academic economists is very much a minority position among intellectuals in general; one can seem to be a courageous maverick, boldly challenging the powers that be, by reciting the contents of a standard textbook. It has worked for me!”

* Richard Chappell on plausible and implausible motivations for ethics. This is one of the reasons why, although I think consequentialism is incomplete, I am still very sympathetic, and it still serves as my meta-theory (for evaluating other theories).

* Suppose you read in the news that Widget & Sons has a market capitalization (i.e., total price of all shares) of $3 billion. Personally, I find it hard to put that number in context — how big or small is Widget & Sons compared to, say, Google? Another of many fantastic xkcd infographics is very helpful in getting a sense of scale in the domain of money.

* The new version of Scott Siskind’s non-libertarian FAQ, updated in response to criticism from libertarians. Interestingly, the author is notably more sympathetic than before.

* Worthwhile Canadian Initiative on ‘Milton Friedman’s thermostat.’ The author claims that this has strong implications for fiscal policy; my main take-away is the general point: not only does correlation not imply causation — causation doesn’t even imply correlation!

Odds again: Bayes made usable

2.bp.blogspot.com

by Ian Pollock

[Note: this post assumes basic familiarity with probability math, and also presupposes a subjectivist view in philosophy of probability.]

Readers of this blog, and of others a few Erdos numbers (Massimo numbers?) away from it, will by now be used to having Bayes’ theorem hammered into their heads all the time, as the Great Equation of Power and the Timeless Secret of the Universe.

I suspect that I am not the only one who has occasionally felt somewhat disingenuous when harping on Bayes. Even though I do actually think it’s the secret of the universe, memorizing the formula is liable to become little more than a signal of in-group identity (along the lines of being able to recite the Nicene Creed or the roster of Local Sports Team), unless people know what it means, and how to sometimes actually maybe possibly use it.

When I talk about “using” Bayes theorem, I have a different picture in mind than what you may think. I do not necessarily mean a textbook problem with all the needed information clearly specified and relevant numbers handed to you. What I tend to think of instead are problems like:
“The car in front of me just swerved halfway into my lane. How likely is the driver to be drunk?"
These underspecified problems are the meat of day-to-day probability judgments.

But let’s look at Bayes theorem as traditionally presented:

P(H|E) = P(H)•P(E|H) / ( P(E|H)•P(H) + P(E|¬H)•P(¬H) )

[Terminology: P(_) stands for “probability of _,” H stands for “hypothesis,” E stands for “evidence,” the vertical bar stands for “given,” e.g., P(E|H) is the “probability of E given that H is true”, and finally ¬ means “not.”]

This formula is hideous on at least two levels:

First, it has too many terms (some repeating) and too many operations. You end up performing 2 or 3 multiplications, 1 addition, 1 subtraction ( P(¬H) = 1 - P(H) ) and 1 division, in order to get the answer. This does not conduce to doing the arithmetic in your head in real time, unless you are unusually good at arithmetic and have good fluid memory (neither of which apply to me).

Second, and perhaps most importantly, it is conceptually opaque. You do not see the structure of reasoning when you look at Bayes’ theorem in that form; all you see is a porridge of symbols. The “prior” that Bayesians are always harping on about, P(H), appears three separate times, once in the numerator and twice in the denominator, all tangled up with P(E|H) and P(E|¬H) — the “evidence terms.” Granted, the denominator is really just an expansion of P(E), which makes it a bit less opaque. But you can rarely calculate P(E) without doing the expansion.

Notice that when we speak of using Bayes’ theorem we are speaking of modifying (1) prior judgment in the light of (2) evidence to arrive at (3) a new judgment. Ideally, we would like a formula that looks more like:

posterior = prior [operation] evidence

Well, here is Bayes’ theorem in odds form:

O(H|E) = O(H) * P(E|H) / P(E|¬H)

As you can see, it consists of only one division and one multiplication. And lo, O(H) is just the prior odds, and the ratio P(E|H)/P(E|¬H) corresponds to “evidential strength,” although the literature usually calls it a likelihood ratio or a Bayes factor.

If you’re not used to how odds work, now would be a good time to check out my old article on them, in which for some inscrutable reason I didn’t get round to talking about their advantage in re: Bayes’ theorem. The rest of this article assumes you are moderately comfortable with odds talk.

Let’s see how Bayes works with an example.

In the classic 1957 film “12 Angry Men” (one of my favorites), a young man is accused of killing his father. One of the pieces of evidence brought against him is the fact that he was identified by a store clerk as having recently purchased a switchblade knife with an unusual handle, and the same kind of knife had been found on the body (wiped of fingerprints). See a nice clip here of the jurors debating the relevance of this piece of evidence.

At first, the unusual character of the knife led the jurors to believe that it was, if not one of a kind, at least very rare. But they are led by the touch of Henry Fonda’s cool hand to modify that assessment and consider the knife a much more commonplace one than they had thought. One of the hawkish jurors then asks petulantly: “Maybe there are ten knives like that, so what?” So what indeed.

We are interested in estimating the odds that the boy is guilty, given that he had purchased a knife the same as the one found at the murder scene — O(guilty|knife). Let us assume that it is certain that the boy did indeed purchase the knife as the store clerk said (actually a very charitable interpretation in the prosecution’s favour).

The first thing we need to think about is our prior. This represents what we think the chance is that the boy committed the murder, before the knife evidence is considered at all. Different people will have different priors, but let us suppose that enough evidence had been presented at trial already to make you consider him 20% likely to be guilty, or odds of 1:4 in favor: O(guilty) = 1:4.

We still need to know two more things.

First, P(knife|guilty) — assuming the boy is guilty, how likely is the knife evidence?
Well, it is not beyond the realm of possibility that the boy could have stabbed his father and disposed of the knife altogether, so even if he is guilty, there is no guarantee of seeing the knife. However, since we know he did buy an identical knife, it is not very surprising to see it at the crime scene if he is guilty. Let us estimate this probability as P(knife|guilty) = 0.6.

We also need to know P(knife|¬guilty) — assuming the boy is innocent, how likely is the knife evidence?

If (as the jurors at first seem to assume) there is only one knife in the whole world that looks like the murder weapon, and we know that the boy bought it, then the only plausible way it could have been the murder weapon and yet the boy be innocent, is if somebody else acquired it from the boy, and then used it to kill the boy’s father. One can understand the hawkish jurors’ impatience with this “possibility.” It requires not only that the boy somehow lost possession of the knife, but that somebody else (coincidentally?) wanted to use it to kill his father in particular. This rates a very low probability, let us say 1000:1 against or P(knife|¬guilty) = 0.001.

Now we have everything we need to figure out the odds of the boy being guilty, given this evidence. We already have the prior — 4:1 against or 1:4 in favor. The “evidential strength” is just the ratio of P(knife|guilty)/P(knife|¬guilty) = 0.6/0.001 = 600. We just multiply the prior by the evidence:

O(guilty|knife) = (1:4)*600 = 150:1 in favor of guilt.

So far so good, although the three numbers involved can all be quibbled with. But here is where Henry Fonda’s duplicate knife becomes important. It does not really change the top part of the evidence ratio: P(knife|guilty) is about the same. But suddenly that factor of 1000 that was making the boy look so guilty is going to drop, because now we know that the killer had access to lots of identical knives, not just the defendant’s. Now it looks like P(knife|¬guilty) is just the fraction of all knives available in the victim’s neighborhood that look like the murder weapon. We can guess that this is something like 1 in 10. So the evidence ratio becomes 0.6/0.1 = 6, and we multiply by the prior to get

O(guilty|knife) = (1:4)*6 = 3:2 in favor of guilt.

Thus, what Fonda showed is that although the knife is evidence of the boy’s guilt, it is much weaker evidence than the jurors had been led to believe. We do not convict criminals at odds of 3:2, or at least, we ought not to.

To address one objection I anticipate: yes, many of the numbers above are very rough guesses. Wherever possible, they should be improved upon by more objective data. But in my defense, notice how mapping out the underlying structure of the reasoning directs inquiry to where it needs to go, rather than to irrelevancies. You can challenge the prior I chose of 4:1 against guilt, by saying that the other evidence presented at trial makes him look a lot more guilty than that. You can challenge the drop in the evidence ratio by checking exactly how many of these knives are sold in nearby shops. These are exactly the questions juries should be thinking about.

Meanwhile, other questions, when seen in a Bayesian light, are obviously non-starters. A bigoted juror in the movie makes much of the boy’s poor background, as if that ought to weigh heavily in favor of his guilt. Unfortunately, while his fellow jurors express their disgust at this man’s prejudice, they fail to notice the obvious silliness of the underlying logic in this case. For if the boy is more likely to commit a crime by virtue of living in a bad neighborhood, so too are all the other people in the neighborhood, leaving the boy’s relative chances of having committed this particular crime approximately the same as they would have been if he had lived in a good neighborhood. Likewise, it is not much good emphasizing the victim’s bad relationship with his son, when he had bad relations with innumerable others.

To recap what we did in our example: we had a prior judgment about how likely the boy was to be guilty, not considering the knife evidence. Then, we considered the evidential strength of the knife evidence, which can be summarized with the phrase: “how much more likely was the evidence if he was guilty, than if he was innocent?”

This way of thinking about uncertainty, while normatively correct, departs from how humans automatically reason about these things in two important ways.

First, it gives equal weight to evidence and to prior. This is important because people constantly forget all about their priors as soon as they see evidence confirming a hypothesis. “I just met Sally. She is very adventurous, a real adrenaline junkie. Is Sally more likely to be a skydiving instructor, or an accountant?” Most people will answer that Sally is probably a skydiving instructor, forgetting that although all skydiving instructors are surely adventurous, there are way more accountants than skydiving instructors (and some accountants are adventurous too). The skeptical community usually sums up the insight that priors matter as much as evidence, with Carl Sagan’s excellent slogan “extraordinary claims require extraordinary evidence,” although they sometimes display a woeful lack of inclination to generalize this principle beyond Bigfoot.

Second, it emphasizes that what matters is not that evidence be consistent with some hypothesis, but that it be more likely if the hypothesis is true, than if it is false. This has the side effect of emphasizing the non-binary nature of evidence. Amanda Knox acted oddly (for example, doing a handstand) after the murder of her roommate Meredith Kirchner, about which the prosecution made much hay. The question we now know to ask is, “How much more likely is a person to act oddly after the murder of their friend if they are guilty, as opposed to if they are innocent?”

Um... a little more likely? Maybe twice as likely, at most? Possibly even less likely, as a guilty person might be more careful not to stand out... If this is evidence of guilt at all, it is extremely weak and ambiguous evidence, an evidence ratio of close to 1.

Most of us will not serve on many juries, but the same logic applies, rather famously, to medical tests of various kinds. If I go in for random screening against bowel cancer, and test positive, I am liable to assume that I almost certainly have the disease. However, the questions that really need to be asked at this point are: (a) what’s the base rate in the population (aka, prior) and (b) how much more likely is a positive test if I have the disease than if I don’t?

Wikipedia tells us that Fecal Occult Blood screening for bowel cancer has 67% sensitivity (67% of people with the disease test positive) and 91% specificity (9% of people without the disease test positive anyway). This means the evidential strength of a positive test is P(pos_test|cancer)/P(pos_test|¬cancer) = 67/9 = 7. So whatever the prior odds were, multiply them by ~10. [1]
The base rate for bowel cancer looks to be about 54 per 100,000 or around 2000:1 against, so O(cancer|pos_test) = (1:2000)*10 = 1:200 in favor = 200:1 against. As you can see, a positive test is cause for concern, but not panic. You probably don’t have the disease. In fact, you didn’t even need to look up the incidence in this case - all you needed to do was realize that unless 1 in 10 people in your reference class have bowel cancer (surely not!), your odds of having it are less than 50:50.

I hope that this reformulation of Bayes, mathematically trivial as it is, serves you as well as it now serves me. Even if you don’t actually calculate (hard to do in the messiness of the real world), knowing how it works is, I think, very epistemically salutary.
_______

[1] 7=10 in guerrilla arithmetic. We spit on your bourgeois Peano axioms.

Risk and blame

Ruins after the L'Aquila earthquake
http://i.telegraph.co.uk

by Ian Pollock

When six Italian scientists and civil servants were put on trial, then convicted on October 22, 2012 of multiple manslaughter (with a sentence of six years in prison each), the reaction from the scientific community was fast and for the most part negative. The defendants, who had been part of a public advisory board on safety risks, had been charged with inducing a false sense of security among the residents of L’Aquila (which had recently experienced strong tremors), causing many residents to stay at home, where approximately 300 were killed by a terrible earthquake in April 2009.

The issue is not as simple as the American Association for the Advancement of Science seemed to believe when it wrote a letter in June 2010 to the Italian President. In it, the AAAS claimed that the basis of the indictment was that the scientists failed to alert the population of L’Aquila to the impending disaster. This is not quite right — the charge was not of insufficient predictive ability, but of culpably poor risk communication. Although at a public meeting in March 2009, a large earthquake was called “unlikely,” but not excluded as a possibility, officer Bernardo de Bernardinis afterward assured the public that there was “no danger,” and that the tremors were good inasmuch as they released pent-up tectonic energy — agreeing with a reporter’s offhand suggestion that residents should crack open a bottle of wine.

This is not as misleading as it sounds, for although around half of all large quakes are preceded by minor foreshocks [P(tremor|large quake)], a minor earthquake is followed by another at least 1.0 magnitude unit larger only 1-3% of the time [P(large quake|tremor)] — which is the relevant statistic for the situation. Nonetheless, tremors are positive (if very weak) Bayesian evidence in favor of an impending larger quake: this does look like poor science and poor science communication. We do not know how many people died specifically because of the scientists’ downplaying of the risks, but it’s at least plausible that it’s a substantial fraction of the 300. (Although for some perspective, consider that no one has been charged in relation to poor building standards in the town, despite their much more proximate causal link to the deaths.)

Even granting the charge of poor science communication, the judgment of six years for manslaughter is obviously extreme, not to mention encouraging of perverse incentives. When a Type I error leads to some annoyed residents, and a Type II error leads to half a dozen years in jail, count on future risk experts to always cover their asses by overplaying every danger, no matter how unlikely. This, of course, leads to the public discounting experts, and then ignoring serious counsel they should heed. As Daniel Kahneman says in “Thinking Fast and Slow,” increased accountability is a mixed blessing. It leads to the extinction of useful signals from experts, and their replacement with weasel words.

There are lots of people in the world to feel much sorrier for, but I do often feel pretty sorry for the people in charge of communicating risk to the public and taking actions to mitigate it. In addition to the difficulty they have in predicting and preparing for the future (which obviously varies depending on what is being predicted), they face several huge cognitive problems with their audience:

• Neglect of probability: “Don’t give me the odds! Is it safe or not?”
• Denial of personal responsibility: “Nobody informed us of the risks of waterfall kayaking.”
• Bad-guy bias: “My son died on the operating table, and someone needs to be held responsible!”
• Hindsight/Outcome bias and moral luck: “How can you say it was the right call based on what you knew, when forty families are grieving!”
• Moral grandstanding: “No risk to our children is acceptable!”
• Crying-probable-wolf effect: “The last two evacuations were false alarms. I’m not going anywhere.”

Once you are made aware of these phenomena, you start noticing the pattern all over the place.

Kahneman relates the following anecdote:

“The worse the consequence, the greater the hindsight bias. In the case of a catastrophe, such as 9/11, we are especially ready to believe that the officials who failed to anticipate it were negligent or blind. On July 10, 2001, the Central Intelligence Agency obtained information that al-Qaeda might be planning a major attack against the United States. George Tenet, director of the CIA, brought the information not to President George W. Bush but to National Security Adviser Condoleezza Rice. When the facts later emerged, Ben Bradlee, the legendary executive editor of The Washington Post, declared, ‘It seems to me elementary that if you’ve got the story that’s going to dominate history you might as well go right to the president.’ But on July 10, no one knew — or could have known — that this tidbit of intelligence would turn out to dominate history.”

This would almost be funny if it weren’t so malicious, as here the usual blind spots are amplified by political point-scoring.

The biases affecting risk assessment and the assignation of blame for it are now well-publicized, for example by Kahneman, as well as by Dan Gardner in his excellent book “Risk.” However, we have to take this knowledge out of the realm of books on cognitive psychology and apply it wisely in real world cases. It is important to note that being made aware of the possibility of, for example, hindsight bias only reduces it very slightly. This makes me wonder if even my fairly exculpating response to the earthquake case is still too hawkish. Had no quake occurred, would I have judged de Bernardinis’ misleading statement as anything more than a minor slip of the tongue? (Other commentators fell more spectacularly for hindsight, pointing to the disastrous quake of 1703 as evidence that the group should obviously have known better.) 

I think the lesson from this is that we ought to cut the people in charge of controlling public risks, whether they are employed in the public or private sector, a great deal more slack. Our prior for culpable negligence on their part is always going to be overinflated in the aftermath of a disaster that actually did happen. We should be especially slow to judge when we or someone we know has been affected, or when our political views already predispose us against the decision makers.

One of the more powerful results of decision theory is that pretty much all decisions can be modeled as gambles. Many of those gambles have stakes that are measured in human lives — including banal decisions such as whether to go to work while you have the flu. At the level of public policy, the stakes are necessarily much higher, the uncertainty is usually greater, and alas, by its nature the gamble cannot simply be avoided.

Not only that, but just like private citizens, decision makers dealing with risk have to consider other factors besides risk to human life — such as “mere” convenience or “mere” money. Although private citizens are more than happy to grandstand about the infinite value of human life (and then go out driving in icy weather because they really feel like a cheap donair), policy decision makers are obliged to explicitly consider e.g., the economic impact of an evacuation against its potential to save lives. These are agonizing but necessary choices.

So let us think once, twice, and three more times before we demand somebody’s scalp because something really bad happened. Especially if it “could have been prevented.”

The p, the whole p, and nothing but the p

api.ning.com

by Ian Pollock

[Note to our gentle reader: believe it or not, this is Rationally Speaking's 1000th post. Not bad, huh?]

It is not uncommon that a discussion about some controversy turns to the truth or falsity of some claim, and thereupon one of the parties to the discussion questions the very nature of truth itself.

Often, this is a conversational move designed to say “I am feeling embarrassed and I need to save face,” in which case you probably need to consider whether continuing the conversation is a productive move. But sometimes truth as a concept does seem to be a real point of contention, especially among those of radically post-modern disposition.

This post presents one theory of the nature of truth — a topic that is, despite appearances, rather interesting. After that theory is put on the table, we will see what it suggests about how we might get the conversation back on track.

There are many ways of carving up the philosophical positions on the nature of truth, depending on historical contingencies, and also on what first-order domain we are talking about the truth of (science, history, ethics…). I find it useful to adopt a fivefold division into these family groupings: correspondence, coherentism, instrumentalism, relativism and minimalism. Although this is a rough-and-ready division, it seems to get the empirical clusters in belief-space more or less right. I will now do a brief aerial survey of the first four, and of the obvious objections to them.

The correspondence thesis is probably the one most familiar to common sense. This is usually expressed as the idea that truth describes a relation of correspondence between beliefs (or some other propositional attitude) and reality. So we say that a belief that coal is black is ‘true,’ if (and only if) in the real world coal actually turns out to be black.

Although this seems highly intuitive, it runs into problems when we consider how to evaluate whether “in the real world coal actually is black.” The problem is the following: it seems to imply that in order to discover whether something is true (by checking correspondence between beliefs and reality), you need to somehow “step outside” of your own epistemic limitations — your own complex of beliefs and perceptions — and check whether coal is black from some universal, objective perspective that is completely separate from any one individual person’s views. Only then will you be able to verify the correspondence. This looks suspicious — you don’t need to be a relativist to realize that there is no view from nowhere.

Coherentism, meanwhile, avoids this trap by identifying true beliefs simply as being part of a coherent set of beliefs, avoiding any mention of correspondence with an external reality (historically, this was motivated by the fact that coherentists were often idealists — deniers of the external world). Coherence theory is thus supposed to clarify epistemology by making how we acquire true beliefs non-mysterious. We look at our other beliefs (and, presumably, sense data etc.) and check whether or not a candidate belief is consistent with them.

The obvious objection here is that in asserting the truth of some belief, we are not merely making a claim that that belief fits with others we have. Coherence looks like a necessary condition for a good epistemology, but hardly a sufficient one — there are coherent belief systems that are demonstrably false or epistemically useless. My favorite example is that of a person who has rejected induction in favor of its opposite. He expects that since the sun has come up every day for the last 4 billion odd years, surely it’s due for a change. When his past lack of success in using this counter-inductive reasoning is pointed out to him (among other things, he has gambled away all his money) he replies that that just proves his point — his mode of reasoning has failed so often in the past that it is bound to work any day now!

Another response to the perceived epistemic arrogance of the correspondence theory is instrumentalism (one example of which might be James’ pragmatism). Here, the idea is that in saying something is true, we are really more concerned with its usefulness in accomplishing some necessary task. An example might be an engineer using the concept of an electric field in predicting whether a capacitor will work for a given application. According to the instrumentalist perspective, the truth of whether the electric field is really there just boils down to whether the concept of an electric field is useful to the engineer in achieving their aims. This is a fairly metaphysically neutral account of truth.

However, as with coherence theory, instrumentalism seems to be answering a different query than what was asked. We can always levy a Moore-style Open Question argument against it: “I know it’s useful to believe p, but is p true?” As long as that sentence is not obviously a logical contradiction, it stands as a mark against instrumentalism.

Relativism undoubtedly represents the most radical of our four perspectives on truth. Although it is stated in many different and mutually contradictory ways, the key idea may be summarized roughly as follows: talking of truth outside of a given epistemological and conceptual framework is highly suspect and probably meaningless (this is the source of Derrida’s slogan “il n’y a pas de hors-texte” — there is nothing outside the text.) Since there is no stepping out of our contingent perspective, truth is essentially relative to the person doing the perceiving; there is no absolute truth. Moreover, our conceptual frameworks are strongly determined (not merely influenced) by our cultures, and specifically by power relations between and within cultures. Hence, insistence on the correctness of the truth of some proposition amounts to insistence on the correctness of one’s own conceptual frameworks, which in turn amounts to a sort of cultural imperialism.

Although relativism in its better moments is motivated by a correct suspicion of pipe dreams about the “view from nowhere,” and by a laudable intention to avoid cultural imperialism, it almost always leads to conceptual absurdities and borderline self-refutations. There are the familiar objections, such as: "Is it true that there is no absolute truth? If so, is that truth an absolute truth or a relative one?" I don’t think this is quite as strong an objection to relativism as is commonly thought (Socrates was so impressed with it, he called it “exquisite”), but it is pretty good.

Likewise, "Aren’t there lots of places where absolute truth seems completely appropriate, and in particular does not seem to depend on beliefs at all? For example, if I eat a whole bunch of hemlock, I will probably die, independently of whether I believe it’s hemlock, and independently of whether I believe it will kill me." (Working definition of 'reality': whatever remains more or less invariant under changes in my beliefs.)

"And at any rate, isn’t your relativist theory unlivable as epistemic practice, and even insincere? For example, this morning I said 'Petunias are perennial,' and you said 'That’s not true.' You didn’t qualify that statement at all, or relativize it. Only now, when we are talking about something controversial, you are suddenly being skeptical about truth."

These objections are familiar, but I want to take a different tack and try to show how we can do an end-run around relativism without committing ourselves to the apparent epistemic arrogance of correspondence theory, while also showing instrumentalism and coherence theory to be at best wrong-headed. This move is the last in our set of five broad perspectives on truth: minimalism, which was introduced to me by Simon Blackburn in his excellent book “Truth.”

The first insight of minimalism (due to Gottlob Frege) is the ‘collapsibility’ or ‘transparency’ of statements about truth. If I say “It is raining,” and then follow up a minute later with the claim “It is true that it is raining,” am I adding anything to my original claim? It seems not — what I am saying just boils back down to “It is raining.” This is the case no matter how many realist flourishes of calligraphy we add to the claim, e.g.; “It is true that it is true that it is raining,” or “It is factually correct that it is raining,” or “It is an absolute truth about objective reality that it is raining.” All of these reduce, in a rather boring and tautological way, to the original claim, “It is raining.”

But how is this possible, given the idea (shared by correspondence and coherence theorists, relativists and instrumentalists) that truth is a non-trivial ‘property’ of judgments — and a very metaphysically fraught one, according to three of the schools mentioned above?

The minimalist position can be stated briefly as follows (using the formulation of Alfred Tarski):

1. “p” is true if and only if p. (For example: “It is raining” is true if and only if it is raining.)
2. This is all there is to say, metaphysically, about the nature of truth.

As Blackburn says:

“... a good way of thinking about minimalism and its attractions is to see it as substituting the particular for the general. It mistrusts anything abstract or windy. Both the relativist and the absolutist are impressed by Pilate’s notorious question ‘What is Truth?’, and each tries to say something useful at the same high and vertiginous level of generality. The minimalist can be thought of as turning his back on this abstraction, and then in any particular case he prefaces his answer with the prior injunction: you tell me. This does not mean, ‘You tell me what truth is.’ It means, ‘You tell me what the issue is, and I will tell you (although you will already know, by then) what the truth about the issue consists in.’ If the issue is whether high tide is at midday, then truth consists in high tide being at midday ... We can tell you what truth amounts to, if you first tell us what the issue is.”

We should also note that the minimalist approach to truth does not necessarily imply that there is no relation between our beliefs and reality (a la correspondence theory), or that epistemology is not influenced by culture (a la relativism), or that true beliefs are not useful (a la instrumentalism), or mutually consistent (a la coherentism). It merely decouples the practice of saying that “so-and-so is true” from party positions about epistemology, politics and metaphysics. After accepting a minimalist theory of truth, we can go and have our arguments about the existence of the external world, and the way we come to find out about things, and the cultural valence of our conceptual frameworks, knowing that our use of the vocabulary of truth and falsity is not hostage to the outcome of those debates.

The proper skeptical question to ask about minimalism is something like the following: if “p is true” just means “p,” why do we even need words like “true,” “truth,” “false,” “falsity,” “fact” etc. at all?

The minimalist answer is that “true” is a “predicate of generalization,” i.e., essentially a linguistic convenience. Let’s illustrate with an example: suppose I want to tell you that the Governor General said something false in the throne speech.

With the “truth” vocabulary, this is easy: I say “The Governor General said something false in the throne speech.”

Without that vocabulary, this is much more difficult — we would have to use an awkward circumlocution like: “The Governor General said ‘a’ and ‘b’ and ‘c’ and .... and ‘z’ in the throne speech, and NOT (a and b and c and.... and z).”

Likewise, the snappy admonition to “Always tell the truth!” gets translated rather awkwardly as “For all p, say ‘p’ if and only if p.”

So the  minimalist reply is that the only reason we talk of “truth” at all, is because we want to make certain claims with a minimum of linguistic fuss. This explains the existence of our truth vocabulary without reference to any dubious notions of unverifiable 'correspondence,' or facile equations of truth to utility.

Seen from this perspective, correspondence theorists of truth, especially in their more metaphysical moods, can look like they are engaged in rather silly reification and idol-worship of what is basically just a useful linguistic compression device.  (How much impact would it have had if Plato had said of Socrates, not that he “loved the truth,” but that he “loved the indexical pronouns”?)*

Meanwhile, instrumentalism about truth ends up looking distracted by non-issues; we want to know whether it’s raining, but the instrumentalist starts gibbering about how it’s useful to believe it’s raining because then maybe we’ll take an umbrella, which is not what was asked at all. Likewise, coherentism insists on looking inward, at the relation of beliefs about rain to other beliefs, instead of outward, at the weather.

And relativism ends up looking the most dysfunctional of all. We want to know whether it’s raining, and instead of being engaged respectfully as fellow epistemic agents, we are treated as patients whose views and queries are “symptomatic” of some ill-defined social malaise. Maybe our umbrella-centric culture has determined that we ask the question “Is it raining?” that way, privileging dryness-normative conceptions of the weather, as opposed to perspectives in which wetness is the default condition and dryness the anomaly, bla cetera.

Of course, this is a caricature, but it does point to why relativism is so hated by many people who are interested in the first-order issues (whether it is raining, how many fundamental forces there are, whether sexual jealousy is a human universal, etc.). It is a defection from our epistemic and conversational norms, which seems in practice to occur selectively whenever defection is convenient for the speaker’s politics.

And to the extent that relativists have a point about some belief or other being merely a reflection of cultural prejudice, that belief will simply turn out to be false (not-p) or ill-stated. The 19th century pseudoscience of gender and race, for example, was just that — pseudoscience, heavily burdened with falsity. Indeed, we are far too generous about the legacy of bigoted falsehoods if we allow that they might have been in some sense true for those who believed in them.

What I think minimalism shows, however, is that the answer to relativist defection is not a retreat to the lofty heights of rhetoric about the Shining, Glorious Truth of Objective Scientific Fact, but rather the best attempt you can muster to get the conversation back on track — back to whatever first-order issue you’re concerned about.

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* Mind you, we could probably cash out “love of truth” in some less ridiculous way.

Ian’s Picks

by Ian Pollock

* The late Marxist philosopher Gerry Cohen gives a spirited defense of what he calls conservatism about value. Video presentation here. Transhumanists in particular (and sympathizers, like me) will find a lot of stuff here with which they could fruitfully engage.

* I don’t suppose anyone reading RS is ignorant of the wonderful xkcd comic. But did you know about the weekly “What if?” column at the same website? Here is a wonderful example of that column:

I can pick up a mole (animal) and throw it. Anything I can throw weighs one pound. One pound is one kilogram. The number 602,214,129,000,000,000,000,000 looks about twice as long as a trillion, which means it’s about a trillion trillion... if anyone asks, I did not tell you it was ok to do math like this.

* Mark Galeotti, an expert on Russian politics and on organized crime, writes an excellent Russia-watching blog called In Moscow’s Shadows. Here is an entry that speaks to issues important to skeptic types.

* The Economist reviews Ben Goldacre’s new book, Bad Pharma (on my reading list). The fact that Goldacre has written extensively before criticizing various forms of alternative medicine does not hurt his credibility here.

* You all know about Khan Academy, right? Because that is some seriously low-hanging utility.

* Speaking of which, GiveWell discusses their evolving criteria for charity evaluation.

* And now, some levity: Kate Evans’ (aka @aristosophy) witty and erudite twitter feed.