I forget exactly where I heard this, who said, or who it was about.\u00a0 All I remember about the pithy little saying I am about to express (rather than continuing to allude to it) is the laughs that it caused.\u00a0 I was driving along listening to some show about politics when one of the commentators suggested that some member of the government was \u2018often wrong but never in doubt\u2019.<\/p>\n
Once my laughter faded \u2013 a process that took some time as that gem struck my funny bone \u2013 I began to reflect not only on the truth that was being conveyed but also why it worked that way.\u00a0 So many of our most prominent citizens, from all professions, seem to not understand just what logic is all about.<\/p>\n
The examples are so numerous that I\u2019ve begun to filter them out to the point where I can\u2019t even cite a specific one.\u00a0 But the scenario is quite clear.\u00a0 A media figure cites a study that, perhaps, mildly suggests that item A and item B are correlated and runs with it to suggest that A causes B.\u00a0\u00a0 A politician takes the words of another politician out of context, twists and turns them this way and that, and ends by constructing something with exactly the opposite meaning.\u00a0 This typically occurs in its most egregious form when there are big stakes on the line, the kind that engender large emotions, but it isn\u2019t confined to that.<\/p>\n
The effect is quite clear but, what about the cause?\u00a0 Now, if I am not careful, I\u2019ll end up doing exactly what I am criticizing \u2013 drawing sweeping generalizations supported by a paucity of data but a lot of belief.\u00a0 So let me say simply that I think that what causes wrong conclusions walking hand-in-hand with little or no doubt is that it is uncomfortable to deal with the doubt.<\/p>\n
Each time we try to make an inductive argument we are dealing, whether formally or not, with statistical data and probabilistic inferences.\u00a0 As Harry Gensler points out<\/p>\n
Deductive reasoning is an all or nothing undertaking.\u00a0 Everything is locked down, certain, and the outcomes are never in doubt.\u00a0 The rules for proceeding from premises are established and have no room for negotiation.\u00a0 The application can be in error but sufficient effort always results in valid reasoning.\u00a0 The only open question is the soundness of the argument, which hinges on whether the premises are true.<\/p>\n
In contrast with deductive arguments, inductive ones generally get murkier as data are added. Certainly a sufficient number of observations are needed to grasp a pattern, but too many observations begin to undermine it.\u00a0 In addition, patterns are simple when they involve one or two variables but as the number of considerations grow so too do the number of combinations, each with its own rule.\u00a0 Inductive arguments always take the form of statistical syllogisms that works most cleanly the less we know.\u00a0 These arguments may not be reliable (the analog to sound) but they can be quite strong (the analog to valid) if the probabilities we assign to the premises are high.\u00a0 This is most easily done if we don\u2019t have a host of additional factors making exceptions here and there.<\/p>\n
Gensler provides a nice example of this point using college football and I want to give him full credit for a good teaching device.\u00a0 That said, I will present its flavor only after having switched to professional football.<\/p>\n
Suppose we know, having analyzed the total plays called by the Pittsburgh Steelers, that 80% of the time they throw the ball deep on a second and short yardage situation when they are at least 30 yards from their own end zone.\u00a0 Suppose, also that we see during this Sunday\u2019s divisional playoff game between them and the Denver Broncos, that the Steelers have 2nd<\/sup>-and-3 down with the ball on Denver\u2019s 47-yard line.\u00a0 We can reason thus:<\/p>\n This seems simple enough, but Gensler often adds to this form the additional line that reads \u2018This is all we know\u2019.\u00a0 At first glance this may seem to be superfluous but as the next example shows, saying that we want to limit our facts may actually beneficial.<\/p>\n Suppose we know, again from the sample of plays, that the Steelers run 70% of the time when they are ahead by at least 10 points.\u00a0 Now if we knew nothing about down and distance but knew that they were winning 20-3, we might reason<\/p>\n So far so good!\u00a0 But now consider that the score is 20-3 and that they have the ball on Denver\u2019s 47-yard line in a short-yardage second down.\u00a0 What should we conclude?\u00a0 Do they run or pass.\u00a0 Perhaps they should just punt.\u00a0 Now layer in additional considerations like the time left in the game, weather conditions, and critical injuries and the situation really gets complicated.<\/p>\n And this is exactly why I think that there is such a correlation between certainty and intellectual short-sightedness.\u00a0 It is easier and more comforting to focus on a single aspect of a complex scenario, find a pattern and merciless apply it.\u00a0 The result is a logic ostrich, with its head in the sand, comforted that it can\u2019t see the messy possibilities.\u00a0 Socrates was right \u2013 the only wisdom is in knowing that one is not wise (although it is possible that an ostrich is still better looking than Socrates).<\/p>\n","protected":false},"excerpt":{"rendered":"\n
\n