To do a thorough analysis of an argument requires a certain discipline. The best approach I know of is due to Michael Scriven and specifically his book Reasoning (1976), which is out of print. Here I present my own version of this process, in compressed form, in seven steps. Roughly, the idea is to first build up the argument into its strongest possible form and then to try to tear the argument asunder. The result should be a good understanding of both the strengths and weaknesses of the argument as it was stated.
I present this as a process for analysing someone else’s argument as it might appear in some ordinary text. However, it may be applied elsewhere, for example, to your own arguments, with a view to improving them. Also, I present this as a kind of ideal. Since in reality we are all constrained by time, it’s unlikely that anyone will continually apply all of the steps to every argument of interest. It’s worthwhile applying all of them to some arguments, however.
The AA Seven Step Program
1. Clarify Meanings.
The first step to critiquing an argument is to understand it. Words that are new to you, or used in unusual ways, might require you to use a dictionary or an encyclopedia. This step may require a certain amount of detective work, for example, learning more about the author and the argument’s history, so as to understand the context and to disambiguate some of the expressions used. Lewis Carroll’s Humpty Dumpty was of course wrong to say that a word means “just what I choose it to mean”, but that doesn’t mean that what authors think they mean is irrelevant. This is also a step where there may be some opportunity to identify whether equivocation is playing some role in the argument; that is, to identify whether some words or phrases are being used in multiple senses, and perhaps misleadingly.
As Tim Wilson, the Australian Human Rights Commissioner, writes: “Before anyone screams ‘free speech’, they should actually know what they are talking about.”
In this, Tim Wilson is exactly right. He writes this, however, in the context of a defence of his Prime Minister’s recent move to restrict the freedom of political speech by public servants. I shall post an analysis of this issue soon after this post, partly to debunk Wilson’s posturing and partly to illustrate the methods explained here.
2. Identify Propositions.
Propositions are assertions about the world, ruling some possible states of affairs in or out. In an argument, some one or more propositions will be premises — assumptions of the argument — while some one or more other propositions will be final conclusions. In between will be intermediate conclusions that are derived, directly or indirectly, from the premises and which are further used to derive other propositions. The rest of the argument will be, in effect, chaff — rhetorical flourishes, irrelevancies, noise. In this step all the relevant propositions should be identified and tentatively identified as premise, intermediate conclusion, final conclusion.
Propositions and sentences may or may not correspond. A sentence may easily contain many propositions. For example, the sentence “Boat people harbor terrorists and criminals and are not our kind of people” one might find three propositions. Propositions may also be spread over multiple sentences, where the sentences are complete grammatically, but somehow incomplete conceptually.
There are, of course, certain words and phrases which may introduce or indicate a role. Statements about observation, testimony, etc., would tend to suggest that premises are being discussed, while “thus” and “therefore” would tend to indicate conclusions. This kind of syntactical marker won’t carry us very far, however, since meanings can be stretched (I can “observe” a conclusion) and, importantly, intermediate conclusions are both premises and conclusions, giving rise to both kinds of marker. The real objective in tagging the propositions is to make the best sense of the argument as possible, so while graphing the argument (in the next step) you may well decide on a different way of classifying propositions as conclusions and premises.
3. Graph the Argument.
Graphing an argument, with each proposition appearing as a node and inferential steps as arrows relating premises and conclusions, is usually a useful exercise. It forces you to make the argumentative steps explicit. The most common way arguments go wrong is by leaving some, or much, of the reasoning implicit, where, unexamined, its imperfections remain unexposed. Per Louis Brandeis, “sunlight is said to be the best of disinfectants.”
While graphing you will need to think about which premises go together to support which conclusions. The goal here will not to be to make these subarguments (parents and their immediate children) valid, but they should be put together so as to be as strong as possible, given the propositions actually in hand. If they are not, you have done a bad job.
Argument mapping has become more popular as computer tools for doing it have become available. For example, Tim van Gelder’s Rationale is widely used in teaching critical thinking. A good alternative, especially once the basics of argument analysis and mapping have been learned, is to use Bayesian networks for laying out arguments and assessing their merits. Bayesian networks have the distinct advantage over pure mapping tools that they can reflect the degrees of strength that premises confer on conclusions. Netica would be a good place to start investigating Bayesian nets for argument analysis, having a relatively friendly GUI; although there is a licence fee, the free download can be used for small maps without any licence.
4. Make it Valid.
This is perhaps the most interesting and challenging of the steps. First, however, a qualification: many arguments are intrinsically or intentionally inductive (probabilistic). Their premises are meant to make a conclusion probable, and not certain. For a trivial example consider a classic enumerative induction: In our history the sun has risen every morning; therefore, tomorrow the sun also rises. There is no certainty, but plenty of probability. Good inductive arguments are already good arguments and don’t need to be made valid. Of course, inductive arguments can also be rendered valid, for you can always add a premise such as “Those things which are probable are true.” But that is really a pointless step. You may as well simply make it as good an inductive argument as you can.
To make each subargument valid, enthymemes (hidden premises) will need to be found and filled in. They shall have to be sufficient to render the conclusion necessarily true, given all of its premises (which is what a valid argument is). In general, they should not be more than sufficient. That is, you should not be building a “Straw Man” — an argument which asserts far more than what its author meant. For example, if an argument’s validity requires that some boat people are terrorists, you wouldn’t want to fill in as hidden premise the assertion that all boat people are terrorists.
This is often called the Principle of Charity. To be sure, charity can be taken too far; for example, if the argument already states that all boat people are terrorists, then, even if the argument doesn’t need it, a fair presentation will include it. Attending to what the author wrote, what the author meant, what the author implied or connoted by what was written, and what the author thought was meant, are all a part of filling in the argument.
Counterexampling is a key technique for this step: imagine some possible world where all of the stated premises are true and yet somehow, perhaps amazingly, the conclusion is false. That is a possible world demonstrating that the argument is not yet valid. You need to add some premise which will make the conclusion false and try again. For example, suppose someone asserts that Gertie, being a swan, must be white. Then we should try to imagine a possible world that includes black swans (that doesn’t take much imagination, since we live in such a possible world:-), in order to note that the argument is assuming that all swans are white.
Having the best version of the argument that we can produce before us, we should now criticize it. Since it is now valid, we are hardly going to be able to criticize the inferential steps. But what we have done in making it valid is to expose all of the argument’s weaknesses in its premises, if there are any weaknesses. So we can now canvass the premises, new (hidden) and old (explicit), for those we might find implausible. Generally, arguers prefer to hide their arguments’ weaknesses, consciously or not, and so the implausibilities will be found in the previously hidden premises, now exposed. We can follow our judgments of implausibility, hunting down and constructing the best arguments we can against those premises, applying the Seven Steps recursively as often as we may need. The result of this step should be a pretty thorough accounting of the merits and demerits of the argument.
6. Consider Alternatives.
If you want a good understanding of the issue at hand, then you will need to survey the relevant literature at least for the main alternative points of view and run them through the first five steps as well. That said, the end of Step 5 is a natural stopping point: the argument may already be assessed on its own terms. If you have built a Bayesian network for it, for example, you may be able to assess precisely the weight given to its conclusion by its premises.1 If you extend the network to a Bayesian decision network with actions and utilities, you will be able to assess relevant actions or interventions, as well.
While you can stop with Step 5, gathering alternative arguments and mapping them should not be considered frosting on the cake. Even though an argument in isolation can be assessed on its own merits, considering the alternatives, especially those put by those who are your ideological contraries, will often lead to a reassessment of your analytical work to this point. Indeed, if you are an open-minded Fox, perhaps they will typically lead to a reassessment.
With multiple argument maps in front of you — or better still, Bayesian networks modeling the main relevant arguments — you can interrogate them to find which conclusions are genuinely supported by the available premises. The premises by this time should include only those which are themselves reasonably well justified. In particular, the weak premises from the initial argument should have been recursively exposed as weak by you having drilled deeper than them (so they are no longer premises); hence, they should no longer be conferring any phony support on the original conclusion.
I shall be illustrating the Seven Step program, or the products of it, on this blog with many arguments. I rather enjoy ripping the common arguments in political speech to shreds.
1 Of course, the precise probabilities entered into a Bayesian network representing an argument may or may not be read over-precisely. If they are rough estimates — corresponding, say, to high, medium and low — then you should just be using the network to assess the more general aspects of the argument, rather than precise probabilities. Bayesian nets can be used to reason Bayesianly, whether or not the probabilities are precise, contrary to canards presented by some anti-Bayesians.