=Paper=
{{Paper
|id=Vol-3614/paper3
|storemode=property
|title=The Role of Intermediate Factors in Explaining Precedential Constraint
|pdfUrl=https://ceur-ws.org/Vol-3614/paper3.pdf
|volume=Vol-3614
|authors=Trevor Bench-Capon
|dblpUrl=https://dblp.org/rec/conf/cmna/Bench-Capon23
}}
==The Role of Intermediate Factors in Explaining Precedential Constraint
==
https://ceur-ws.org/Vol-3614/paper3.pdf
The Role of Intermediate Factors in Explaining
Precedential Constraint
Trevor Bench-Capon
University of Liverpool, UK
Abstract
Formal accounts of precedential constraint have attracted much attention in AI and Law over the past
decade. A recent development in this area has been the proposal to give a finer grained account using
the intermediate factors taken from factor hierarchies of the sort found in CATO. Canavotto and Horty
show, however, that cases constrained in the hierarchical setting are unconstrained when using only base
level factors, and vice versa. We argue that the intermediate factors should play no part in constraining
outcomes, but they are invaluable in explaining the reasoning applicable to the case.
Keywords
Precedential Constraint, Factor Hierarchy, IRAC, Explanation.
1. Introduction
Modelling reasoning with precedent cases has been a central topic of AI and Law since its very
beginnings [1]. The key element of legal reasoning with precedents is the principle of stare
decisis (“stand by what has been decided”). This principle is designed to ensure that like cases
are treated alike, and makes decisions in precedent cases binding on courts in future decisions1 .
Most current thinking on the topic has its roots [2] in the HYPO system of Edwina Rissland and
Kevin Ashley [3], which addreesed the domain of US Trade Secret Misappropriation. Particularly
influential has been an immediate successor to HYPO, CATO2 , [4] developed by Ashley with
his PhD student, Vincent Aleven.
CATO represents cases as sets of factors, stereotypical patterns of fact representing a reason
to decide for a particular party to the dispute. The factors present in cases are termed base level
factors. The factors are in turn reasons for the presence or absence of intermediate factors, also
sometimes called abstract factors. These factors are organised into a set of hierarchies, one for
each issue. Issues are the various points that the plaintiff must establish in order to win a claim.
CMNA’23: Workshop on Computational Models of Natural Argument, December 1st, 2023, online
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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1
Whether the courts are obliged to to follow the decisions varies from jurisdiction to jurisdiction. Inferior courts are
generally obliged to follow the decisions of superior courts (vertical stare decisis), but whether decisions of courts of
equal status (horizontal stare decisis) must be followed varies. In the US, federal appeal courts obey horizontal stare
decisis, whereas the appeal courts of New York state do not. Courts may be able to show good reason not to follow
a precedent: this usually involves distinguishing the case by showing a significant difference with the precedent.
Of course, superior courts are not bound by the decisions of inferior courts. Even if not bound by a precedent,
however, the court may find the precedent persuasive and follow it, thus conferring its own status on the decision.
2
Teaching law students how to make good distinctions was the guiding purpose of CATO system.
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CATO was concerned only to generate arguments, not commit to an outcome. Issue Based
Prediction (IBP) [5], was designed to predict case outcomes, and so the issues were organised
into an and/or tree, tying the separate hierarchies of CATO into a single structure with the
outcome as root. Factor based reasoning is used to resolve the issues, standard logical reasoning
to deduce the outcome from the and/or tree of issues. The Value Judgement and Argumentation
Prediction (VJAP) of [6], used the same hierarchy but extended IBP by using value judgements
to justify preferences between factors. Factors are by far the most common way to represent
cases when modelling reasoning with precedents. As well CATO, IBP and VJAP, all of which,
like HYPO, addressed US Trade Secrets Misappropriation, factors are used in [7], [8], [9], [10]
and many others.
The principle of stare decisis means that the set of precedents can constrain the decision in a
new case. So the question arise for a new case: is the case constrained by the precedents, so
that the decision is straightforward, or is the new case sufficiently different that the judges must
choose the decision which they believe is justified on the facts of the new case (thus setting
a new precedent). To answer this question, in [11] John Horty introduced a formal account
of precedential constraint for reasoning with legal cases described as sets of factors. Horty’s
original conference paper was expanded into a journal paper [12], and some improvements
were suggested in [13]. A key element of Horty’s approach is that it used the reason model of
precedential constraint [14], as opposed to the results model [15]. Given a case 𝐶 = 𝑃 ∪ 𝐷 where
𝑃 are the pro-plaintiff factors and 𝐷 are the pro-defendant factors the results model, as used
in [7] and [16], states that the set 𝑃 is preferred to the set 𝐷 if the plaintiff wins and that 𝐷 is
preferred to 𝑃 if the defendant wins. The reason model recognises that a subset of its factors
may be enough for the winning side to be preferred to the complete set of opposing factors,
and so the preference is, if the plaintiff won, the reason 𝑅 is preferred to 𝐷 where 𝑅 ⊂ 𝑃, and, if
the defendant won, 𝑅 is preferred to 𝑃 where 𝑅 ⊂ 𝐷. The advantage of the reason model is that
it constrains more cases than the results model. Later developments include modelling both
factors and dimensions ([17], [18]), but here we will consider only factors3 .
There are three main types of factor hierarchy in the literature. In CATO [4], there is a
separate hierarchy for each issue. Each hierarchy has one or more layers of intermediate factors,
and a bottom layer of base level factors. In IBP [5] and VBJP [6], the root is the outcome, followed
by one or more layers of issues, followed by a layer of base level factors. Here there are no
intermediate factors. In the ANGELIC methodology [20] we have a combination where the
root is the outcome, followed by one or more layers of issues, followed by one or more layers of
intermediate factors, followed by a layer of base level factors. Horty’s model of precedential
constraint in [12], however, does not use a hierarchy: it moves straight from outcome to base
level factors, giving a one step explanation, base level factors → 𝑜𝑢𝑡𝑐𝑜𝑚𝑒.
In [10] it was argued that ignoring issues resulted in some cases which should be constrained
being unconstrained, since the cases could be distinguished using factors belonging to a different
issue, and so not relevant to the main point of the case. Instead the method should be applied
at the issue level rather than the outcome level, and use the hierarchy of IBP. This enables
reasoning with portions of precedents as recommended by Branting [21]. The use of issues
gives rise to a two step explanation: base level factors → 𝑖𝑠𝑠𝑢𝑒𝑠 → 𝑜𝑢𝑡𝑐𝑜𝑚𝑒.
3
Our view is that dimensions should be used at the factor ascription stage, not the constraint stage [19].
At ICAIL 2023 two papers, [22] and [23], attempted to go further, by reintroducing interme-
diate factors. Neither placed any particular stress on issues: it appears that the root may be
an issue or an outcome in [22], but always an outcome in [23]. In this paper we will discuss
mainly [22], which contained some interesting results regarding the constraints imposed by
hierarchies with intermediate factors (H-constrained) and flat hierarchies, those with only base
level factors (F-constrained). In [22] it was demonstrated that there were significant differences
between using a single step argument from factors to outcome and the hierarchical approach:
cases H-constrained might not be F-constrained without the intermediate factors, and cases
F-constrained might not be H-constrained. This gives rise to two types of problem case (A and
D cases are constrained or unconstrained with either hierarchy and so unproblematic):
B: Cases F-constrained but not H-constrained
C: Cases not F-constrained but H-constrained.
These results are clearly undesirable, unless one of the two constraints always gives the
correct outcome. We argue that the F-constraint is the correct notion. We will consider type B
cases and type C cases in turn.
2. Type B cases: F-constrained but not H-constrained.
Our example type-B case will use the example from [22], shown in Figure 1. In this domain
there are six factors. There are three pro-plaintiff factors, 𝐹 1𝑝 , 𝐹 2𝑝 and 𝐹 4𝑝 , and three defendant
factors, 𝐹 3𝑑 , 𝐹 5𝑑 and 𝐹 6𝑑 4 . In the type B example we have:
• A precedent case with pro plaintiff factors 𝐹 1𝑝 and 𝐹 4𝑝 and pro defendant factor 𝐹 5𝑑 .
• A current case with pro plaintiff factor 𝐹 1𝑝 and pro defendant factor 𝐹 5𝑑 .
Given the account of hierarchical constraint in [22], the current case is apparently F-constrained
because the reason for deciding for the plaintiff is 𝐹 1𝑝 , the reason for deciding for the defendant
is 𝐹 5𝑑 , and the decision for 𝜋 in 𝑐3 gives the preference 𝐹 1𝑝 ≻ 𝐹 5𝑑 . Thus, when flattened in
accordance with [22], we have the preference 𝐹 1𝑝 ≻ 𝐹 5𝑑 relative to the concern 𝜋/𝛿, so that the
current case is F-constrained. However, in the hierarchical setting, when 𝐹 4𝑝 is absent, as in the
current case, 𝑅𝑑 is present, and since 𝑅𝑑 was absent from the precedent, there is no preference
for 𝑄𝑝 over 𝑅𝑑 , and so the current case is not H-constrained.
My view, however, is that the case should not be F-constrained. If we apply the reason model
as set out in [12] directly to the flatted hierarchy we have three possible reasons;
• (a) 𝐹 1𝑝 and 𝐹 4𝑝 ≻ 𝐹 5𝑑 : (b) 𝐹 1𝑝 ≻ 𝐹 5𝑑 : (c) 𝐹 4𝑝 ≻ 𝐹 5𝑑
But now suppose we use the layered hierarchy to explain the reasoning which led to a
decision for the plaintiff in 𝑐3 . We can see that it is 𝐹 4𝑝 that is preferred to, and so neutralises,
𝐹 5𝑑 . 𝐹 4𝑝 , however, does not provide a reason to find for the plaintiff, and so 𝐹 1𝑝 is required
for the decision, and so 𝐹 4𝑝 ≻ 𝐹 5𝑑 cannot be the reason. There is, however, no comparison in
𝑐3 between 𝐹 1𝑝 and 𝐹 5𝑑 and so it would be unsafe to give 𝐹 1𝑝 ≻ 𝐹 5𝑑 as the reason, because
4
For extra clarity I subscript factors with the party favoured.
Figure 1: Example Type B case [22]. 𝜋 is a decision for plaintiff, 𝛿 a decision for the defendant. Lower
case letters are intermediate factor names: without a prime they favour the plaintiff, with a prime they
favour the defendant. Highlighted nodes are accepted. Arrows indicate reasons for the parent node:
bold arrows are the effective reasons.
that would ignore the importance of 𝐹 4𝑝 in counteracting 𝐹 5𝑑 . This would leave as 𝐹 1𝑝 and
𝐹 4𝑝 ≻ 𝐹 5𝑑 the most plausible reason, given the knowledge represented in the hierarchy.
Now, however, 𝑐4 is not constrained by this reason, since 𝐹 4𝑝 is missing, so that the preference
does not apply to 𝑐4 . If, however, 𝑐4 is in fact decided in favour of the plaintiff, we will have
our comparison between 𝐹 1𝑝 and 𝐹 5𝑑 , and then we can revise our reason to 𝐹 1𝑝 ≻ 𝐹 5𝑑 . The
precedent justifying this reason would be 𝑐4 , however, not the original precedent, 𝑐3 .
So, although the hierarchy helps us explain the decision, it is the flattened hierarchy that
should be used to constrain future cases.
3. Type C cases: H-constrained but not F-constrained.
The same domain is used as for the type B case. The example is illustrated in Figure 2.
• The precedent contains 𝐹 1𝑝 , 𝐹 4𝑝 , 𝐹 3𝑑 and 𝐹 5𝑑 and was found for plaintiff.
• The current case contains 𝐹 2𝑝 and 𝐹 6𝑑 .
Since there are no factors in common, the precedent does not F-constrain the current case.
However, in the layered case, both cases contain 𝑄𝑝 and 𝑅𝑑 and the decision for 𝜋 turned on the
preference 𝑄𝑝 ≻ 𝑅𝑑 expressed in 𝑐1 , and so the case is H-constrained.
Our view is that the case should not be constrained. The problem causing different behaviour
is that factors should only be grouped under the same intermediate factor if they are of the
same strength5 , if preferences are going to be expressed between the intermediate factors.
The preference may well depend on the strength of the reasons why the intermediate factors
5
Factors with different strengths are recognised in both CATO [4] (which distinguishes weak and strong factors) and
IBP [5], which has ordinary and “knock out” factors. This is needed since not all downplaying arguments succeed.
These qualitative strengths should not be confused with the quantitative strengths represented by dimensions a
factors with magnitude [17]. Strengths of factors is also ignored in [23]: “what matters is that both [fact situations]
𝐺 and 𝐹 satisfy the [intermediate] pro-𝜋 factor F101, and not why it is satisfied.”
Figure 2: Example Type C cases [22]. Notation is as for Figure 1
are present. If factors of differing strengths are grouped under the same intermediate factor
problems arise, as discussed in [24] (Section 4.1), since a weak factor may be treated as if it
were a strong factor, and so be used to distinguish the case even though the difference is not
significant.
Consider the example hierarchy in Figure 3. This is taken from the US Trade Secrets domain
and uses base level factors from CATO [4]. It shows a fragment from the hierarchy for the issue
InfoValuable. The intermediate factors differ from CATO, but choice of intermediate factors is
always with the analyst, to best suit the task, so we have chosen intermediate factors to best
illustrate the problem.
We will use two cases, Mason v. Jack Daniel Distillery and MBL (USA) Corp. v. Diekman . The
factors in Mason relevant to InfoValuable were F6p, SecurityMeasures and F16d, InfoReverseEngi-
neerable. The relevant factors in MBL were SecurityMeasures and F20d, InfoKnownToCompetitors.
Mason was found for the plaintiff and MBL for the defendant.
Suppose the first case to appear was Mason. Both IF1 and IF2 are present, and since the
case was found for the plaintiff, we must, using H-constraint, accept that IF1 ≻ IF2. Now if
MBL comes before the court, it would appear to be H-constrained. But MBL was found for
the defendant, showing that the preference IF1 ≻ IF2 does not hold. How can this be? What
the judges have to decide is not the absolute question of whether protection is preferred to
availability in all cases, but whether the protection is sufficient in the case under consideration.
This requires them to examine the reason why the intermediate factors hold, namely the base
level factors. In Mason it is reasonable to think that the measures taken by Mason were sufficient
to outweigh the mere possibility of reverse engineering, given the time trouble and expense
that that might take. So we do have the preference 𝐹 6𝑝 ≻ 𝐹 16𝑑 . But in MBL, the defendant has
the stronger reason, that the information is already known to competitors. Thus the security
measures taken by MLB seem to have been a case of bolting the stable door after the horse has
gone, and it is quite reasonable to have the preference 𝐹 20𝑑 ≻ 𝐹 6𝑝 . Thus the H-constraint does
not hold: instead both Mason and MBL give rise to F-constraints, for different sides.
Turning now to the example from [22], shown in Figure 2, it might well be that 𝐹 1𝑝 establishes
𝑄𝑝 with sufficient strength to defeat 𝑅𝑑 , when 𝑅𝑑 is established by 𝐹 5𝑑 , but that 𝐹 2𝑝 does not
Figure 3: Fragment of the factor hierarchy for the issue InfoValuable.
when 𝑅𝑑 is established by 𝐹 6𝑑 . If it turned out that the current case in Figure 2 was decided for
the plaintiff, that might be held to justify the hierarchy used there. But this requires the decision
from the court, effectively establishing that 𝐹 2𝑝 is stronger than 𝐹 6𝑑 , so that the current case
itself becomes the precedent. The decision could equally have been made for the defendant,
establishing that 𝐹 6𝑝 was stronger than 𝐹 2𝑝 . Without the decision the assumption of equal
strength of the reasons for the intermediate factors cannot be made, and so the H-constraint
should be considered valid only if the F-constraint also holds with appropriate precedents. In all
cases where the decision legitimates the hierarchy, the legitimating case can be used to justify a
preference between base level factors.
To apply H-constraints conceals that a judgement is being made as to whether the plaintiff in-
termediate factor is sufficient to outweigh the defendant intermediate factor, and this judgement
is a, perhaps the, crucial step in the decision.
4. Explanation
.
We have so far argued that F-constraint is the correct notion when determining the outcome
of a case. Does this mean that we can ignore intermediate factors and return to the two step
explanations of [5] and [10]? Let us consider why intermediate factors were introduced in
CATO [4]. The purpose of CATO was to teach law students to distinguish cases and to defend
against distinctions. One way of defending against a distinction is to downplay it, by finding a
different factor which could be used to substitute for or cancel the distinguishing factor. Thus
where Mason is the precedent and MBL the defence can distinguish Mason:
Def : In MBL, the information was known to competitors. This was not so in Mason.
Plain : In Mason, the information was also obtainable, through reverse engineering, and the
security measures taken by Mason were sufficient to counter this availability.
Judge : That the information is known to competitors is far stronger than the mere possibility
of reverse engineering. I find for the defendant.
In CATO the difference in strength is not important, since its role is only to find arguments,
not to determine outcomes. It is up to the user, acting as judge, to decide on which argument
wins. And the plaintiff’s argument is a valid downplaying argument, albeit not a strong one. Had
Mason contained the stronger 𝐹 24𝑝 , InfoObtainableElsewhere, instead of 𝐹 6𝑝 , the downplaying
argument would probably have succeeded 6 . Thus the judgement between intermediate factors
is an important part of the reason for the decision, and so should be reflected in the explanation.
And this requires the intermediate factors.
A popular method for explaining legal cases, widely used in US Law Schools, is the Issue-
Rule-Application-Conclusion (IRAC) method [25]. An IRAC “issue” is not limited to what are
termed “issues” in the hierarchies, but rather refers to the main point under dispute which
may equally be a conflict between intermediate factors such as we found in Mason and MBL.
Note therefore that a flat hierarchy would be insufficient to identify such issues: the issue (in
the IRAC sense) in Mason and MBL is not so much whether 𝐹 6𝑝 outweighs 𝐹 16𝑑 or 𝐹 20𝑑 , as
whether the protection was sufficient to keep the value of the information given the extent of
the availability. Thus the explanation offered by [10], that the security measures were preferred
to the reverse engineerability is not really enough.
The IRAC issue in these cases is whether the protection was sufficient to keep the value of the
information given the extent of the availability. The rule is that if the protection is considered
sufficient given the availability, the information is valuable and not otherwise. The application
concerns the relative strength of the reasons supporting the conflicting intermediate factors.
The conclusion then follows from the rule. Thus the IRAC explanation in Mason is:
I : Was the protection sufficient given the availability of the information?
R : If the protection was sufficient, find the information valuable.
A : The security measures taken by Mason were sufficient to outweigh the bare possibility
of the information being reverse engineered.
C The information was valuable.
And in MBL, with Mason as precedent:
I : Was the protection sufficient given the availability of the information?
R : If the protection was sufficient, find the information valuable (Mason).
A : The security measures taken by MBL were not sufficient to protect the information
since it is known to competitors.
C : The information was not valuable.
This greatly improves the explanation, because it identifies the real issue, and explains why
the base level factors are in conflict, and the import of their relative strengths.
4.1. Nested IRAC
In deeper hierarchies, we may need to apply explain several judgements and so need to nest
the explanations. Consider the fragment of the factor hierarchy for US Trade Secrets shown
in Figure 4. Here we have an additional layer of intermediate factors. Consider first National
Instrument Labs, Inc. v. Hycel which contained only factors 𝐹 1𝑑 , DisclosureInNegotiations, and
𝐹 21𝑝 , KnewInfoConfidential relating to the issue of confidentiality. National Instrument Labs
was found for the plaintiff, so 𝐹 21𝑝 ≻ 𝐹 1𝑑 . The explanation would be:
6
In IBP [5], the problem is resolved by making some factors “knock out” factors, resistant to downplaying.
Figure 4: Fragment of the factor hierarchy for the issue ConfidentialRelationship.
I1 : Was there a confidential Relationship?
R1 : A confidential Relationship exists if there was notice of confidentiality, which is not
invalid.
I2 : Was there notice of confidentiality?
R2 : There was notice of confidentiality if there is a verbal agreement or a written
agreement.
I3 : Was there a verbal agreement?
R3 : There is a verbal agreement if the defendant knew the information to be
confidential.
A3 : The defendant knew the information to be confidential.
C3 : There was a verbal agreement.
A2 : There was a verbal agreement.
C2 : There was notice of confidentiality.
A1 : There was notice of confidentiality and no evidence that it was invalid.
C1 : There was a confidential relationship.
Now consider a case with factors F4p, NonDisclosureAgreement, and F5d, AgreementNotSpecific.
I1 : Was there a confidential Relationship?
R1 : A confidential Arrangement exists if there was notice of confidentiality, which is not
invalid.
I2 : Was there notice of confidentiality?
R2 : There is an explicit agreement if there is a verbal agreement or a written agreement.
I3 : Was there a written agreement?
R3 : There is a written agreement if there is a non-disclosure or a non-competition
agreement
A3 : The defendant signed a non-disclosure agreement.
C3 : There was a written agreement.
A2 : There was a written agreement.
C2 : There was notice of confidentiality.
I4 : Was the agreement valid?
R4 : An agreement is valid unless confidentiality has been waived, or the agreement
was not specific.
A4 : The agreement was not specific.
C4 : The agreement was not valid.
A1 : There was notice of confidentiality but the agreement was not specific.
C1 : There was no confidential relationship.
Note that the outcomes depend solely on the preference 𝐹 21𝑝 ≻ 𝐹 1𝑑 in the first case and
𝐹 5𝑑 ≻ 𝐹 4𝑝 in the second. This does, however, show how the IRAC explanation uses intermediate
factors to contextualise the preference and shows why it matters.
4.2. Improving the presentation
Currently the explanation is a bit stilted, and resembles the how? of early rule based programs
such as MYCIN [26]. It could be greatly improved by representing the case not as a set of
factors, but as a set of factor-fact pairs where fact is a textual description of the facts which
led to the ascription of the factor. In the National Instrument Labs case we could associate 𝐹 1𝑑
with “The plaintiff revealed the information during negotiations of 3rd September 1978”, and
𝐹 21𝑝 with “but the defendant concedes that the information was given under terms of strict
confidentiality”7 . Now the central part of the National Instrument Labs explanation can become:
I3 : Was there a verbal agreement?
R3 : There is a verbal agreement if the defendant knew the information to be confidential.
A3 : The plaintiff revealed the information during negotiations of 3rd September 1978, but the
defendant concedes that the information was given under terms of strict confidentiality.
C3 : There was a verbal agreement.
Similarly in the second case, we can associate 𝐹 4𝑝 with “The defendant signed a non-disclosure
agreement on 6th August 1977” and associate 𝐹 5𝑑 with ”The agreement made no mention of
future discoveries, and cannot be held to cover the information in question, which was not
discovered until September 1980.” Now the relevant parts of the explanation can become:
I3 : Was there a written agreement?
R3 : There is a written agreement if there is a non-disclosure or a non-competition agreement
A3 : The defendant signed a non-disclosure agreement on 6th August 1977.
C3 : There was a written agreement.
and
7
The defendant in fact argued that the information was available on the grounds of reverse engineerability, and
that it was known to competitors. Both these claims failed. The case was thus lost at the factor ascription stage,
showing the need for a stage before applying precedential constraints over preferences.
I4 : Was the agreement valid?
R4 : An agreement is valid unless confidentiality has been waived, or the agreement was not
specific.
A4 : The agreement made no mention of future discoveries, and cannot be held to cover the
information in question, which was not discovered until September 1980.
C4 : The agreement was not valid.
We believe that this connection to the facts of the case greatly improves the naturalness of
the explanation.
5. Concluding Remarks
Providing a formal account of precedential constraint is an active topic in Artificial Intelligence
and Law. The original account was in terms of factors and outcomes only. In [10] it was argued
that issues also required consideration, to avoid irrelevant distinctions. More recently it has been
argued in [22] and [23] that a still finer grained notion, including layers of intermediate factors
should be used. This, however, raises some problems. In was shown in [22] that H-constraints
and F-constraints do not always align, and H-constrained cases may not be F-constrained and
vice versa. In sections 2 and 3 we argued that the correct outcome was always given by the
F-constraint, and explained why this is so. Therefore, for determining the outcome of the case,
only base level factors should be considered.
The explanation resulting from F-constraint is, however, rather terse and assumes that the
explainee will be aware of how and why the base level factors relate and their consequences.
This information is what is contained in the intermediate factors. In consequence, better
explanations can be given using the finer grained hierarchy. We illustrated this in Section 4
by showing how it can yield IRAC style explanations. These can be made more natural by
associating the base level factors with the facts that led to their ascription.
Thus we believe that the intermediate factors play an important cognitive role in aiding
understanding of the domain, but play no role in the logic of precedential constraint.
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