A Theory of Preliminary Fact Investigation
Yeshiva University - Benjamin N. Cardozo School of Law
George Mason University; George Mason University - Antonin Scalia Law School, Faculty
UC Davis Law Review, Vol. 24, p. 931, 1991
How do human beings know? And how can human beings make sure that they know the truth? These are old questions. However, their their shape has changed, or so some people think. Until very recently - roughly until the middle of the twentieth century - many observers believed that the question of the foundations of human knowledge is an unanswerable philosophical riddle. Today, however, there are signs of a shift in attitude toward epistemological issues. A diverse group of theorists views the riddle of human knowledge as a practical problem that admits of answers. These epistemological optimists would reject the wry suggestion that "cognitive science" is an oxymoron; they believe that a science of the mind is possible. Indeed, some of these optimists are hyperoptimists. In recent years "neural networks" have become one of the "hottest" topics in the field of computer logic and artificial intelligence. Some students of cognitive science believe that "neurocomputational" logic may allow them to model and mimic the operations of the brain, and not just understand them.
We share the view that real progress in understanding human knowledge is now possible. In one respect, however, we part ways with the more enthusiastic advocates of artificial intelligence, neural networks, computational models of the mind, and the like. We believe that imagination plays an essential role in all human knowledge and we believe that no model of the mind, no matter how esoteric or subtle, can duplicate, much less replace, the imaginative activities of the human mind. Despite our skepticism about machine-minds, however, we think it is important to use logic to map the operations of the mind. Logic portrays human thought in an orderly way. Logical pictures of possible ways of thinking can facilitate orderly and imaginative reasoning about facts.
Fact investigation in litigation is hard to do well. One of the causes of investigative failure is conceptual failure; effective investigation requires good thinking. This Article describes describes a device for ordering thought during preliminary fact investigation: a network of twelve systems for marshalling evidence. Although this network is not a machine that somehow churns out good investigative decisions all by itself, it is a useful tool for the analysis of investigative problems. The network of evidence marshalling strategies described in this Article facilitates good thinking about problems of evidence in the early stages of fact investigation in litigation.
In Part I of the Article we provide a bird's eye view of our theory. We identify twelve separate systems or strategies for marshalling evidence; we provide a brief description of each these methods of marshalling evidence; and we suggest how these various marshalling strategies can influence each other. A diagram depicts the entire theory as a network of linked marshalling operations.
In Part II we describe several marshalling strategies in more detail. In particular, we discuss how factual hypotheses are constructed, refined, and also "coarsened." We pay close attention to the impact of evidentiary trifles and details on the formation of factual hypotheses and conjectures. Evidentiary details support and suggest various possibilities, and a detail combined with one or more other details may suggest and support yet further possibilities. Since different combinations of details suggest and support different possibilities, arranging and combining evidentiary trifles in various ways can be a useful heuristic exercise. However, even a small number of details can be combined in many different ways. Shuffling details in a random fashion to see what they suggest is inefficient. We describe several systematic procedures for combining details and for flushing out the possibilities that different combinations of details might suggest or support.
In Part II we also discuss strategies for eliminating hypotheses and possibilities, but strategies for generating factual hypotheses and conjectures remain our primary concern. Although shuffling combinations of details is a useful strategy for generating hypotheses, it is not always sufficient. Imagination and conjecture play an essential role in effective fact investigation. While almost of our methods for flushing possibilities out of details and combinations of details require the use of imagination, not all of these strategies involve fancy or conjecture. For example, we describe a strategy of marshalling evidence by "possibilities." This strategy involves imaginative reasoning but not conjecture because marshalling by possibilities supposes that every possibility must be directly supported by evidence. However, it is often useful - and it may be essential - to entertain possibilities and hypotheses that go beyond, or "outrun," the available evidence. Hence, some of the "abductive" marshalling strategies we describe generate hypotheses that are not directly supported by evidence. For example, we discuss of the role of "stories" in hypothesis formation. Stories, or "scenarios," combine elements of fact and fancy.
The Article concludes with some general observations about the nature of our theory. We argue that our network of evidence marshalling systems, though complex, is "user friendly," at least in principle. The intellectual processes and operations we describe do not have a "transcendental" character or origin, but are "natural" to ordinary thinking human beings. It is true that the workings of our network of marshalling systems can be very intricate: the twelve marshalling systems we describe can interact in complex ways and users of our network may be forced to pay attention to several marshalling operations simultaneously. However, the obstacles to the use of our marshalling systems are no greater than those presently faced by real-world investigators, who must already mentally walk and chew gum at the same time. The purpose of our theory is to facilitate the management of already complex tasks.
Our final observations concern the computer-generated diagrams and devices we use to depict the network of evidence marshalling operations. We argue that our computer-generated visual representations serve a theoretical purpose as well as a practical one. These representations are metaphors. The fact that they are user-friendly - the fact that they make complex strategies for organizing evidence more understandable and intelligible - is some evidence of the validity of our theory. Our theory is a map of the mind. If it is a good map, it should make our thinking more clear.
Number of Pages in PDF File: 55
Date posted: April 13, 2005