Moral philosopher Jeremy Waldron offers this powerful critique of “soft paternalism” or the use of state-sponsored “nudges” to change behavior (emphasis ours):
… it may help to think about a slightly different sort of nudge—an informational nudge, where we manipulate the information given to people who use certain heuristics, in order to achieve the behavioral change that we figure the proper processing of correct information would lead to.
For example: between 15 and 20 percent of regular smokers (let’s say men sixty years old, who have smoked a pack a day for forty years) will die of lung cancer. But regulators don’t publicize that number, even though it ought to frighten people away from smoking, because they figure that some smokers may irrationally take shelter in the complementary statistic of the 80–85 percent of smokers who will not die of lung cancer. So instead they say that smoking raises the chances of getting lung cancer. That will nudge many people toward the right behavior, even though it doesn’t in itself provide an assessment of how dangerous smoking actually is (at least not without a baseline percentage of nonsmokers who get cancer).
Or consider the way lawmakers nudge people away from drunk driving. There are about 112 million self-reported episodes of alcohol-impaired driving among adults in the US each year. Yet in 2010, the number of people who were killed in alcohol-impaired driving crashes (10,228) was an order of magnitude lower than that, i.e., almost one ten thousandth of the number of incidents of DWI. The lawmakers don’t say that 0.009 percent of drunk drivers cause fatal accidents (implying, correctly, that 99.991 percent of drunk drivers do not). They say instead that alcohol is responsible for nearly one third (31 percent) of all traffic-related deaths in the United States—which nudges people in the right direction, even though in itself it tells us next to nothing about how dangerous drunk driving is.
In other words, smoking and driving under the influence are, of course, risky activities — compared, that is, to not smoking and to not driving under the influence — but how great is the true risk? Is it ethical for our government to present a false or distorted picture of the actual magnitude of the true risk, as in the two examples above?
What theory of constitutional interpretation does Captain Kirk subscribe to? Hat tip: Will Baude.
Pop Quiz: What do presidential libraries, advertisements for prescription drugs, and pennies (yes, pennies!) have in common? They are all things that cost more than space exploration! (Hat tip: Tyler Cowen.)
Albert Silver recently conducted a fascinating computer experiment — a chess tournament between the Komodo 8 chess engine (running on an Android smart phone) playing against the Shredder chess engine (running on a much faster desktop computer — 50 times faster, to be exact). In Mr Silver’s words:
Since Komodo 8 exists on both the desktop as well as the Android smartphone, I decided to play a small match between it on a smartphone [an LG Optimus G Pro from 2013], facing Shredder on a modern, top of the line quad-core i7 processor.
Guess what happened?
Hat tip to Tyler Cowen for the pointer and for posing the question, “Is software outpacing hardware?“
That is the title of our latest paper on the blue bus problem, a favorite law-school hypothetical of torts and evidence professors. (We wrote up a first draft of our paper in Tarpon Springs, Florida during the summer of 2013 and made some stylistic as well as substantive revisions more recently in preparation for our paper’s forthcoming publication in volume 7 of the Washington University Jurisprudence Review.) Briefly, the main contribution of our paper is that we visualize the blue bus problem using Bayesian methods of probabilistic reasoning. By the way, although many legal scholars — most recently Edward Cheng — have applied Bayesian methods to the blue bus problem, none have taken a visual approach to the problem. Ironically, however, trial attorneys routinely rely on visual forms of evidence (e.g., pictures, objects, scale models, etc.) when presenting their cases to juries. In our blue bus paper, then, we follow the lead of trial lawyers and present a Bayesian approach to the blue bus problem in visual form using numerical frequencies instead of fractions or percentages. In addition to solving the blue bus problem, our larger aim is to reevaluate the problem of probabilistic proof and make the case for Bayesian methods in civil and criminal adjudication generally.
Addendum: By the way, while we’re on the subject of ESPN’s three-week suspension of Bill Simmons, check out this original analysis of the economics of employee suspensions here. (Tyler Cowen offers two possible economic explanations of employee suspensions.) This part of Professor Cowen’s post in particular caught our attention: “If I were the commissioner, I would be insulted by the suspension of Simmons. It suggests these are words which cannot be said, perhaps because they will elicit audience assent. The suspension also signals that ESPN regards the commissioner as quite thin-skinned and presumably — especially if he is indeed thin-skinned! — he could be offended by that too.”