Defeasible and Abductive Reasoning: A Common Foundation for Lawyers and Designers
This essay explores the commonalities between defeasible reasoning and abductive reasoning and argues there is a basis for common ground between legal reasoning and design thinking. There is a finality to both law and design: Judgments must be rendered, contracts must be executed, cases must be settled or tried. Similarly, products must be manufactured, buildings must be built, and advertising must appear. The underlying challenge for both law and design is how to reach a level of certainty despite the reality of incomplete information at, and subsequent to, the final decision point. Not surprisingly, this common challenge has spawned common reasoning approaches, and therein lies the opportunity for mutual dialogue.
Defeasible Reasoning and Law
Defeasible reasoning reaches conclusions that are acknowledged to be contingent on its antecedents remaining unfalsified. By definition, defeasible reasoning is non-monotonic, in that the truth statement may not survive the addition of a new antecedent. Prakken and Sartor (2004) describe it as follows: “The conclusions of the reasoning process do not grow inevitably as further input information is provided.” According to Prakken and Sartor (2004) the concept of defeasibility was introduced to legal theory by Hart (1951), when he adopted the real property concept of defeasible interest to a legal argument fraught with contingencies. They go on to describe three aspects of defeasible reasoning: inference-based, process-based, and theory-based.
Inference-based defeasibility theories examine the information at hand and make judgments on which conclusions are, or are not, appropriate on the basis of that information alone.  Pollock (1995) refers to defeasible reasoning as the resolution between two conflicting desired outcomes inherent in human reasoning: “Beliefs are adopted on the basis of arguments that appeal to small sets of previously held information, but the beliefs can later be retracted in the face of new information.
McCarthy (1987) refers to this as a problem of qualification, and Peczenik (1989) reaches a similar conclusion: “It should enable a legal agent to form judgments on the basis of the knowledge he has, and the thinking he is presently able to do, and correct (and possibly withdraw) such conclusions as soon as he is able to take into account further legally relevant information.”
Hage (1997) takes the perspective of balancing antecedent reasons, the stronger of which is meant to carry the day, but Prakken and Sartor (1996) and Pollock and Cruz (1999) prefer the approach of recursive, iterative “argument games,” in which legal conclusions are arrived at by judging which conflicting antecedent reasons create the strongest inference through the process of a “dialectical interaction of competing inferences.”
In an element unique to legal reasoning, the outcome of the battle between antecedent arguments will be influenced by the procedural aspects of the legal system, which will regulate the shifting burdens of proof, evidence admissibility, etc. An analysis based on pure logic will not always be sufficient. This does not appear to be directly relevant to commonality with design thinking, however it is worth noting that formal process forms an essential part of legal defeasibility.
Inference- and process-based defeasibility both deal with the application of a theory to a specific issue or set of facts, whereas theory-based defeasibility deals not with the application of a theory, rather the choice between theories. Theory-based defeasibility “results from the evaluation and the choice of theories which explain and systematise the available input information: When a better theory becomes available, inferior theories are to be abandoned.”
The choice between theories harkens back to discussions of philosophy of science, including Popper (1959), Lakatos (1978), Thagard (1992) and Kuhn (1962).  Prakken and Sartor (2004) make the case for a measured approach to theory change, given the importance of consistency and predictability in the law, with the objective being the notion of coherence, defined by Peczenik (1997) as: “The more the statements belonging to a given theory approximate a perfect supportive structure, the more coherent the theory is.
Abductive Reasoning and Design
Just as defeasible reasoning undergirds certain streams of legal thought, so does abductive reasoning form the basis of certain streams of design thinking, per Martin (2009), Martin (2010), Dew (2007), Kolko (2010), Tuzet (2006), etc. Abductive reasoning leads to a conclusion that is openly acknowledged as being one possible outcome of many. Aristotle characterized abduction as a probable, minor premise extrapolated from a certain, major premise, and modern logicians have layered on a focus on the “importance of reasoning from causes to effects.”  Stated as a syllogism:
“The surprising fact C is observed. But if A were true, C would be a matter of course. Hence there is reason to suspect that A is true.”
As Gabbay and Woods (2006) argue, abductions are “justifications of use without being evidence of the truth of the hypothesis in question,” and in that sense abduction is inherently pragmatic. In fact the power of abduction lies in its ability to explain phenomenon, make predictions that are empirically verifiable, simplify existing explanations, and unifying laws and theories that otherwise may not be seen as consistent., Abductive reasoning is well suited for tackling wicked problems, AI, computer science, philosophy of science, belief dynamics and legal reasoning.
Abduction is also used in designing business strategy, industrial products, architecture and related fields. From Dew (2007) we have: “The genesis of new designs […] lies in making inferential leaps from a collection of raw data about a design situation to some plausible hypothesis about the underlying issue. […] Therefore, good abductive thinking is a pre-condition for intelligent designing.” Kolko (2007) defines this type of “design synthesis as an abductive sensemaking process of manipulating, organizing, pruning and filtering data in the context of a design problem, in an effort to produce information and knowledge […],” [using methods that emphasize] prioritizing, judging and forging connections.”
The material presented indicates that there are indeed similarities between defeasible and abductive reasoning, and it is argued that there is common theoretical, logical and philosophical ground between defeasible reasoning as applied to law, and abductive reasoning as applied to design. Both modes of reasoning are non-monotonic, and they both lead to particular outcomes while accounting for uncertainty. Defeasible reasoning makes decisions which are openly qualified as being contingent on antecedents remaining unfalsified, and abductive reasoning makes decisions which are openly qualified as being one possible solution of many. Not only do that have commonalities, but one may actually be a subset of the other. For example, from legal perspective Gabbay and Woods (2006,) and Thagard (2004) argue that abduction is important to legal reasoning, and from a design perspective Dew (2007) states that one major characteristic of abduction is defeasibility.
This conclusion opens a wide range of future research. Are there opportunities for legal thinkers to learn from the processes used by design thinkers, and vice versa? What implications might that have on the practice of law or on judicial process? What meta-theory might be appropriate for holistically combining the two types of reasoning, and what implications might that have for the alignment of other seemingly disparate theories? The time appears to be right for inquiries of this nature, and there sufficient commonality from which to start.
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 H. Prakken and G. Sartor, “The Three Faces of Defeasibility in the Law,” Ratio Juris 17, no. 1 (2004): 118.
 H. L. A. Hart, “The Ascription of Responsibility and Rights,” in Logic and Language, ed. A. Flew, (Oxford: Blackwell, 1951), 145–66.
 Ibid., quoted in Prakken and Sartor, “Three Faces,” 121.
 Prakken and Sartor, “Three Faces,” 125.
 J. L. Pollock, Knowledge and Justification. (Princeton, N.J.: Princeton University Press, 1995), 40, quoted in Prakken and Sartor, “Three Faces,” 119.
 J. McCarthy, “Circumscription—A Form of Non-monotonic Reasoning.” In Readings in Non-monotonic Reasoning, edited by M. L. Ginsberg, 145–51. Los Altos, Cal.: Morgan Kaufmann, 1987, quoted in Prakken and Sartor, “Three Faces,” 119.
 A. Peczenik, “The Passion for Reason.” In The Law in Philosophical Perspective, ed. L. J. Wintgens (Dordrecht: Kluwer, 1997), 77, quoted in Prakken and Sartor, “Three Faces,” 119.
 J. C. Hage. “Reasoning With Rules.” An Essay on Legal Reasoning and Its Underlying Logic. (Dordrecht: Kluwer, 1997), quoted in Prakken and Sartor, “Three Faces,” 123.
 Prakken and Sartor, “Three Faces,” 121.
 Prakken and Sartor, “Three Faces,” 121.
 Ibid., 123.
 Ibid., 128.
 Ibid., 136.
 Ibid., 130-131.
 Ibid., 130-131.
 A. Peczenik, “Passion,” 196, quoted in Prakken and Sartor, “Three Faces,” 132.
 R. Martin, The Design of Business: Why Design Thinking is the Next Competitive Advantage. (Boston, Massachusetts: Harvard Business Press, 2009).
 R. Martin, “Design thinking: achieving insights via the ‘knowledge funnel’,” Strategy & Leadership 38, no. 2 (2010): 37-41.
 G. Tuzet, Projectual Abduction. (Oxford: Oxford University Press, 2006): 156-160.
 D. Gabbay and J. Woods. Advice on Abductive Logic. (Oxford: Oxford University Press, 2006).
 Ibid., 190.
 Ibid, 190.
 Ibid., 190.
 It can be argued that this paper is an example of the latter case.
 R. Buchanan, “Wicked Problems in Design Thinking.” In Margolin, V. and R. Buchanan, eds., The Idea of Design (Boston:MIT Press, 1995): 3-20.
 Gabbay and Woods, Advice, 199.
 N. Dew. “Abduction: A Pre-Condition For The Intelligent Design Of Strategy.” Journal of Business Strategy 28, no. 4 (2007): 38.
 Kolko, J. “Abductive Thinking and Sensemaking: The Drivers of Design Synthesis.” Design Issues 26, no. 1 (2010): 27.
 Gabbay and Woods, Advice, 199.
 P. Thagard. “Causal Inference In Legal Decision Making: Explanatory Coherence vs. Bayesian Networks.” Applied Artificial Intelligence 18, no. 3/4 (2004): 249.
 Dew, “Abduction,” 38.
Copyright (c) 2011 Mark Szabo