Deduction has the function of a decision. Deduction can be defined as the act of subsuming a case under a general rule. This means that the resulting action (what in a syllogism would be the conclusion) is identified by the application of a general rule (if x, then y) to a particular case b.
If x then y.
b is x.
Such a framework for decision is also called “purposive-rational action” (see my previous post). This model or frame of decision-making is in essence the practical side of algorithmic thinking. Algorithmic thinking proceeds this way. It is the generation of a chain of practical deductions. Since it’s logical, it can easily be embedded in a computer and in this way it makes decisions without any further human intervention (provided that a viable system of input and output is in place).
This approach based on practical deductions “works” – so to say, if we can connect the particular case at hand back to a known category – a sort of specimen. This is what the act of subsuming a case under a general rule actually means. So, a case is never taken for what it is, but as a member of a broader category. This makes very hard for a practical deductive system to handle any case that is not immediately connected back to a known category.
Interestingly, a practical deductive system may actually force a particular case into a known category. Practical deductive systems are in fact procrustean beds (I will come back to this point in another post). There are indeed false positive and false negative to deal with.
Practical deductions never quite deal with individual cases. A case is always a token of a type – to use a more technical jargon. In other words, it needs to engage with abstraction. Which means in this case to reduce or attenuate the number of levels of (possible) descriptions (see Mark Johnson’s post on this). Assigning a case to a broader category means precisely reducing the variety of ways in which we can describe something to a single one (or a few). This is the problem when we simply classify things.
Leaving procrustean beds aside for the time being, practical deductions are not particularly good when it comes to actual decision-making. Indeed, they look good. Very good. That’s because they rely on purposeful deliberation: we know what we are going to do and why. However, they are not able to adapt. They need explicit knowledge. They do not tolerate uncertainty and ignorance. While practical deductions are safe and provide a good deal of certainty and control, they inevitably deal with fixed abstract entities and therefore do not adapt to circumstances. (Seemingly, practical deductivism maps pretty much on what the great Alexander Luria said about classical science, which he viewed as “the reduction of living reality with all its richness of detail to abstract schemas”.)
Let me now turn to practical abductions, which I started dealing with in a previous post.
Essentially, in practical abductions we are not able to recognize the case at hand. And that impairs the possibility to apply a practical deductivist approach. An interesting example is unlocking the door. If everything works, what we have to do is to put the key in the lock and turn the key left (or counterclockwise). The thing is, if something goes wrong (because of a faulty lock, for example), we are plunged into a state of ignorance: what should we do? Practical deduction is a powerless option precisely because it requires that the case is known. The case at hand cannot be subsumed under the general rule, simply because we don’t know what the case is. We need therefore a creative type of practical inference. Here is where practical abduction comes into play.
In the syllogistic framework, an abduction is composed of a major premise, which is a piece of knowledge, a habit, a rule, or, more in general, something that we assume to be true; a minor premise, which is something like a cue, a trace left that we detect in the here and now. The conclusion of the abduction establishes a state of things – a case. So, I can make the following example:
Paul comes to office with his laptop (Major premise – habit).
I see Paul’s laptop on his desk (Minor premise – cue)
Paul has come to the office (Conclusion – case)
What makes abduction particularly interesting is that the generation of a conclusion depends on the selection of a major premise, which happens in connection with the cue, the trace left. In a non-practical abduction the conclusion we reach is an explanation.
In a practical abduction we have something similar. First of all, we have something like a cue, a trace left. In our example it is that we can’t turn the key right. The major premise is not a piece of knowledge, but an action, a doing. It can be, for example, pulling the key out of the lock by a few millimeters. This action is somehow cued by the situation. We simply can’t turn the key right. Now, this action – this doing – has then an effect on the world. So, the “conclusion” is not an explanation like in the case of a non-practical abduction. It is some sort of change that we see happening in the world. If we prefer, it is a manipulation of the world brought about by an action (pulling out the key) cued by something in the environment (we can’t turn the key right) that we took as relevant.
What is interesting is that the conclusion in the practical abduction is known only after we have actually acted. This is what gives the sense of tentativeness to practical abduction. Indeed, the resulting change can meet our expectations or not. Or it may create something that eventually meet our expectations, although it was not intended to be so. This is the case of serendipity. Now, what is interesting to stress is that this way of proceeding is not algorithmic, that is, governed by rules that we apply to known cases. The selection of the major premise – the action – has a pure heuristic function. We do something in the expectation that the change produced will somehow be helpful for us to understand a bit better the world around us. But there is no certainty.