Argument maps are not “a tool for argumentation”; they’re not intended to be used in every context in which people argue. If they were, we all probably would have heard of them already at some point, if just as “that weird thing I see no reason to use.”
Argument maps are intended to either analyze or formalize the sides of an argument, in one of two contexts:
• contexts like civic policy, where a third party (e.g. an analyst working for a politician) wants to create an executive summary of a debate for consumption by a policy-maker, usually by watching/reading, and then “digesting”, a lot of arguments. (In this context, it also helps to be able to merge argument maps, efficiently unifying nodes that are semantically similar while keeping their dissimilar children.)
• In cases of formal debate, where the goal of the debaters is, as often as not, not for one side to dominate the other with rhetoric, but rather for everyone to “adversarially collaborate” to discover the complete shape of the debate—to map all the pros and cons—so that they can then go over the mapped argument and judge its merits for themselves, rather than working form the incomplete information they started with (usually just the information held by their “side.”)
Combine these two, and you get “barristers on both sides of a court, working for a judge as analysts to help them understand both sides of a case”—as in truth-discovering (rather than guilt-deciding) judicial systems like Scotland’s; or as in grand juries or coroner’s inquests.
(You can also use argument maps in your personal life, if you want to be really objective about deciding whether to believe something. But the contexts in which there are so many good arguments on both sides that you’d get a different answer than the one you’d get by just listening to the debate with an open mind, would be rare. For a cute analogy, they’re “asymptotes of discourse”: places where you’re dividing infinite evidence by infinite evidence, and so need something more powerful than regular mental arithmetic to get a solution.)
"In cases of formal debate, where the goal of the debaters is, as often as not, not for one side to dominate the other with rhetoric, but rather for everyone to “adversarially collaborate” to discover the complete shape of the debate—to map all the pros and cons—so that they can then go over the mapped argument and judge its merits for themselves, rather than working form the incomplete information they started with (usually just the information held by their “side.”)"
I did formal (policy) debate and my goal was always to win. Are there forms of formal debate which are really oriented towards sketching out a complete argument landscape?
Policy debate is a formal style of competitive debate, characterized by a high degree of "game" like behavior and, most notably, the act of making arguments as fast as possible, so as to literally make it impossible for your opponent to answer them all.
Mostly its a high school thing, but there are some college leagues.
To answer your questions:
- Winning made me feel smart and cool.
- Never, but I also don't feel I was right either, really. I mean the relationship to the substance of the ideas in the debate is so tenuous. It really is a kind of high speed game of conceptual chess, more than an argument.
- The policy debater takes up and puts down positions like tools. One round you might make an argument you defeated in the previous round. You might argue against your very own position.
- As a data scientist (and a scientist and philosopher in general) I'm with you about truth being important (as far as that goes) but policy debate is much more about developing a facility with ideas. A certain detachment from specific ideas is actually very important to finding the true ones, and policy debate helps you see that.
On the other hand, it does make people cynical. I see a lot of what is wrong with this country in my training as a debater. Its a thing taught mostly to rich kids at private schools and it teaches them to bullshit, which is a critical skill if you're to lord it over the plebes. The world might be better off it we didn't know how.
My view these days is that I'm quite skeptical of strong claims made either way and that I prefer virtue ethics, which say we should focus less on complex schemes to understand and manipulate the world and more on our character moment to moment.
I've been studying the informal fallacies and it dismayed me to discover that lawyers typically USE, instead of AVOID, many of these fallacies... precisely because it wins cases. Their purpose is to win, not to be the most correct.
Winning is thus a perverse incentive in truth discovery. Maybe conflating competition with truth discovery was a bad idea? I guess, it's impossible to dispassionately plead a court case when livelihoods are at stake, and thus competition is inevitable...
I would like to think that if I was a lawyer arguing a case, and I knew that using a certain fallacy would work, I wouldn't use it... but who knows.
> I did formal (policy) debate and my goal was always to win. Are there forms of formal debate which are really oriented towards sketching out a complete argument landscape?
I don't think this exists yet, but it should. It may just end up with everyone arguing over what the meaning of "truth" is, but I'd still watch it.
In principle, the adversarial system of justice in the United Systems is supposed to sort of work in this way (though the judgement is by a third party). Even though each party is focused on winning, the structure is supposed to give rise to fairness by construction.
A better example might be an inquisitorial justice system, in which a theoretically neutral party attempts to reach a conclusion and a defensible support for it.
> merge argument maps, efficiently unifying nodes that are semantically similar
Is the merging done automatically? If so, this together with some other comments in the thread seems to imply that the software has an ontology mapped onto the arguments—which to my knowledge was so far a pipe dream for most people, on the order a bit below generic AI and somewhere around Watson. Am I mistaken, is there anything practical in this space? Or does the semantic mapping just mean lotsa handiwork?
I wrote and defended a thesis proposal on this topic in which the goal was to automate, to the greatest degree possible, merging nodes which mean the same thing. One example is "CO2 causes climate change" and "Climate change is caused by carbon dioxide", both saying the same thing, but neither of which would submit to a simple string comparison. As it turns out, there are Watson-like agents beginning to emerge in the open source arena, including OpenSherlock, my project, which is taking forever to complete owing to the enormous amount of experimental work that must be accomplished.
It's not. Common vs civil law (i.e. where law comes from) is orthogonal to the roles of the fact-finder and parties in a dispute at trial. Most Americans will be familiar with an adversarial model, where each side's lawyer is making the best case for their side. In Scotland, the responsibility is aligned differently, towards helping the judge to discover the truth.
"In civil law countries, judges are often described as “investigators.” They generally take the lead in the proceedings by bringing charges, establishing facts through witness examination and applying remedies found in legal codes."
"In contrast, in a common law country, lawyers make presentations to the judge (and sometimes the jury) and examine witnesses themselves."
Also, asked my wife who is Scottish litigator:
Most law that is case law but not criminal legislation is civil law. We not have an inquisitorial system system but in practice judges do ask questions regarding legal submissions made by parties.
Argument maps are intended to either analyze or formalize the sides of an argument, in one of two contexts:
• contexts like civic policy, where a third party (e.g. an analyst working for a politician) wants to create an executive summary of a debate for consumption by a policy-maker, usually by watching/reading, and then “digesting”, a lot of arguments. (In this context, it also helps to be able to merge argument maps, efficiently unifying nodes that are semantically similar while keeping their dissimilar children.)
• In cases of formal debate, where the goal of the debaters is, as often as not, not for one side to dominate the other with rhetoric, but rather for everyone to “adversarially collaborate” to discover the complete shape of the debate—to map all the pros and cons—so that they can then go over the mapped argument and judge its merits for themselves, rather than working form the incomplete information they started with (usually just the information held by their “side.”)
Combine these two, and you get “barristers on both sides of a court, working for a judge as analysts to help them understand both sides of a case”—as in truth-discovering (rather than guilt-deciding) judicial systems like Scotland’s; or as in grand juries or coroner’s inquests.
(You can also use argument maps in your personal life, if you want to be really objective about deciding whether to believe something. But the contexts in which there are so many good arguments on both sides that you’d get a different answer than the one you’d get by just listening to the debate with an open mind, would be rare. For a cute analogy, they’re “asymptotes of discourse”: places where you’re dividing infinite evidence by infinite evidence, and so need something more powerful than regular mental arithmetic to get a solution.)