NOTES ON A DIFFERENT ‘PATTERN THAT CONNECTS’Posted: February 15, 2019
The Design or Planning Argument that connects claims of Meaning, Science, Know-How, Needs, Desires, Ethics Morals, Justice and Aesthetics…
There is much discussion these days about the relationship between different domains of knowledge; relationships that easily turn into divisive and unproductive controversies. Borrowing a phrase from the community of research of C. Alexander’s ‘Pattern Language’, an examination of the different kinds of knowledge making up the arguments used in planning, design, policy-making shows how this argument ‘pattern’ connects the reasoning patterns of the different domains.
THE “STANDARD PLANNING ARGUMENT
The common structure of ‘pros and cons’ exchanged in discussions about whether a plan should be adopted for implementation I call the ‘standard design /planning argument’ can be described as follows: (The letters D, F, I, E in the following stand for ‘deontic’ (ought) claims, fact-claims, instrumental claim, explanatory claim, respectively.)
Proposal: D (X) (Plan X ought to be adopted / implemented)
Instrumental premise 1: FI ((X —> Y) | C) (Plan X will have effect / result/consequence Y given conditions C
Deontic premise 2: D (Y) Outcome Y ought to be pursued / aimed for
Factual premise 3: F (C) Conditions C are (or will be) given
These premises (which in practice aren’t always all made explicit, assuming some premises as ‘taken for granted’) draw on and are supported by very different kinds of ‘knowledge’. To fully appreciate — understand and giving it due consideration — such arguments in the process of reaching a decision about a proposed plan, a person must understand, and if necessary raise questions to clarify their meaning, content, and forms of supporting ‘evidence’:
MEANING, DISTINCTION, DEFINITION: CONCEPTUAL KNOWLEDGE
‘X’, ‘Y’, ‘C’: and relationship R —-> Understanding , meaning of the terms / words (as understood by proponent and audience to be persuaded): Explanation, description, definition; Relationship of concepts;
‘Plan X’: Idea, vision, desirable outcome, state of affairs, solution to a problem: description in context;
‘Effect’ or ‘consequence ’Y’: State of affairs, Result, Meaning,/implication)
Relationship R of ‘X —> Y’. E.g. cause – effect, implication, part-whole relation;
Condition ‘C’: Data: about state of affairs (‘now’); Others’ intentions, desires, needs, plans. (Actually, a systematic description of the conditions C would amount to a complete ‘systems model’ showing all the factors in the ‘whole system’ and their relationships…)
Argument pattern: D(X) <—( FI ((X—>Y)|C) & D(Y) & F(C): the reasoning ‘rule’ (among other standard argument patterns)
WHAT THE WORLD ‘IS’ LIKE: ‘DATA’, fact-claims, descriptions
F (C) Descriptions about current and past states of affairs, basis and EVIDENCE for claims about such ‘facts’;
HOW THE WORLD ‘WORKS’:
FI (X —> Y) Or FI (X —>REL—>Y)|C The instrumental premise, expressing a ‘law’ (natural, logical, or man-made agreement’) ( also expressing a belief in causality) that makes it possible to achieve some proposed change with a specific plan of action. Technical ‘know-how’ engineering, management skills.
WHAT ‘OUGHT’ TO BE DONE OR AIMED FOR:
D (X) and (D (Y): ‘Deontic’ premises and claims: The proposed plan or action, and the desired or undesirable effects it will bring about (or avoid). Also: ‘It’s the law’ (regulation); or. Command: “Authority A said so”.
EACH TYPE OF KNOWLEDGE IS SUPPORTED BY DIFFERENT ARGUMENT PATTERNS
The ‘standard planning argument’ above has many ‘pattern’ variations, depending on the distribution of assertion or negation signs for each of the premises, and of the nature of the relationship claims in the instrumental premise. Not all of those are equally plausible as argumentation patterns in themselves; some are outright counterproductive or self-contradictory. So the reasoning pattern of each argument must itself be assessed — even the explicit use (stating all parts) of such an argument does not guarantee overall plausibility.
Things are even getting more complicated when we realize that the pattern and its plausibility as intended by a proponent of the argument may be different from the pattern actually assessed by an evaluator: if one or several premise elements are assigned a different assertion or negation sign by the person judging, it is thereby becoming a different pattern in that person’s mind.
The extent to which this complication may affect the evaluation of the arguments supporting the other knowledge type claims involved here — for example, the ‘evidence’ supporting fact-claims, the reasoning supporting scientific hypothesis-testing, such as the inductive pattern of a hypothesis H corroboration by evidence E : ((H —-> E) & E ) —> H (inconclusive) or refutation: ((H—> E ( & ~E) —> ~H; (conclusive); the explanations of the meaning of terms — may have to be examined in different ways than the usual textbook treatment that study the conclusiveness of arguments, mainly as intended by the proponent. This task still calls for more attention.
The aim of this little inquiry, to start with, is to point out that each of the types of knowledge is supported by a set off different argument types. This includes all the argument types and patterns discussed in standard textbooks (where planning argument and arguments including ‘ought’ premises have not been given adequate attention). Serious but unnecessary — controversies often arise from lack of attention to this fact: attempts to justify plans resting on only one such set of patterns, or inappropriately applying the rules of one domain to the others.
For example: from time to time, prevalent ‘approaches’ or methods for doing things in society seem to focus on one of these types of premises with something like faith of their exclusive significance: F —> D: What we ought to do follows ‘DATA’ — the fallacy of ‘OUGHT following ‘IS’: the constraint of ‘the facts’: FI —> D. “ We can do this, therefore we should do it’; D —> D ‘Wishful thinking’: we ought to aim for it because we want it; or: We ought to do it (X) because it follows the goal or principle (Y); even: “Do X because it’s right”.
A different way of stating this is that the exclusive reliance on one of these premise types represent different (‘philosophical’?) attitudes about the dominant type of knowledge to guide design and planning: Science (Facts, Laws of nature), Technology (Engineering: the things we can do); Management skills (Social things we can do: ‘leadership’ and psychology); Religion and ethics, morality principles, societal laws, Political Ideologies.
All of these are fallacious ‘reasons’ for doing or not doing things— because they ignore the other kinds of premises of the planning argument and the many other arguments, about a proposed plan. We must consider all the pros and cons, and all the premises they rest on, even if they aren’t all made explicit.
It is also necessary to look at some of the different types of judgments we use to assess these different claims.
THE DIFFERENT TYPES OF JUDGMENTS NEEDED FOR EACH PREMISE TYPE:
Each of these premises must be evaluated, judged, in order to arrive at a judgment about the merit of the argument as a whole. Much has been made and written about the criterion of TRUTH or its absence FALSITY about claims; and the notion that a claim about some state of affairs in the real world must be either true or false — that it corresponds to the actual state of affairs out there. This leads to the careless jump to express our judgments on the binary scale of ‘true’ and ‘false’.
But we must keep in mind not only that we actually do not make our judgments about the real states of affairs but according to how sure, how certain we are about whether a claim corresponds to reality: Most thing we do not know ‘for sure’, and even some factual issues are not true (or false all the time under all conditions but with some degree of PROBABILITY. This calls for a different scale upon which we should talk about and explain our judgments: the common probability scale is one of zero to one or zero to 100 ‘percent’.
For all its common acceptance, the probability scale does not allow us to express a different kind of judgment: that we simply ‘don’t know’, cannot judge whether a claim is true. false, probable. To express this admission of inability to judge ‘judgment’ by assigning the claim a 50% probability is misleading, it sound like a confident assessment that it will be true about 50% of the time. So a better scale, one with a midpoint of zero ‘Don’t know’ and for example, a +1 score for the judgment ‘completely confident that a claim is true, 100% probable, i.e . certain, and a -1 score expressing the same complete confidence that it is not.
Even the criterion of ‘probability’ does not adequately express what our judgments about the meaning, the adequacy of a description of something (describing a car as ‘having four wheels’ may be true as far as the number of wheels in concerned, but useless when the description intends to help us find the car in the large parking lot…) or — most importantly, assess the deontic premise, the ‘ought’ claims. We argue about those claims precisely because they are neither true nor probable yet — by definition: we try to decide whether we should attempt to make them come true or not. For all these judgments, something like PLAUSIBILITY, expressed on the continuous +1/-1 scale, with the zero ‘don’t know’ midpoint, will be better.
One more judgment criterion is needed for the assessment of plans. The usual concern that has been the focus of argumentation has been the question whether an argument — a single ‘clinching’ argument — supports the conclusion: If all men are mortal and Socrates is a man, it follows inescapably that Socrates is mortal; no further argumentation is needed. But the assessment of plans does NOT rest on single arguments (except possibly the convincing proof that a plan simply is impossible because it contradicts laws of natural (or human laws we do not wish or dare to violate). Plans are assessed by ‘weighing the pros and cons’. They don’t all carry the same ‘weight’. Systems Thinking urges us to find out ALL potential consequences of actions and plans (including the nasty ’unforeseen consequences’ that result from the nonlinear behavior caused from the interacting relationships and relationship loops in the ‘whole system’ network). We must form arguments (of the above kind for each of those consequences) and assess their merit. This ‘weighing’ requires a judgment about the importance or better: WEIGHT OF RELATIVE IMPORTANCE of an argument — how much weight does one pro or con carry in comparison with all the other pros and cons?
The way we examine and construct overall opinions about the proposed plan from all the partial judgments (which has been the focus of my studies on planning arguments) still needs considerable work.
Thorough, systematic deliberation about proposed plan will require us to make all these judgments about the different kinds of premises, of all pro and con arguments, and how they relate to each other. The planning argument contains and connects all the different forms of knowledge; planning decisions are not adequately supported ONLY by either the FACTS (DATA), the possibility of doing something just because we have the tools, the INSTRUMENTAL knowledge, or just because we feel or WISH (or CONSCIOUSNESS/ AWARENESS) that some outcome OUGHT to be realized. Promoting plans and policies on the sole merit of one of these kinds of judgment types is not likely to be persuasive let alone constructive — especially when the different participants in a discourse are adherents of different types of judgments: TRUTH does not apply to all claims, and just DATA aren’t supporting what our plans should be like. Looking more carefully at the patterns of planning arguments might help us to understand these differences, and how the planning argument connects them.