Models of Legal Argumentation

1. Models of Legal Argumentation Trevor Bench-Capon Department of Computer Science The University of Liverpool Liverpool UK

2. Overview • Argument and Proof • Arguments Based on Cases • HYPO • CATO • Arguments Based on Rules • Bodies of Arguments – Dung • Argument Schemes – Toulmin • Persuasion Using Purpose and Value

3. Argument John is old because he is aged 82 Arguments persuade, not compel Arguments leave things implicit. The hearer fills in the gaps and may be convinced Proof John is aged 82 John is a man All men aged greater than 70 are old 82 > 70 Therefore, John is old Argument and Proof

4. Arguments may contain open textured concepts The proof requires a threshold for old The hearer needs only to accept that 82 is above the threshold Proof John is aged 82 John is a man All men aged greater than 70 are old 82 > 70 Therefore, John is old Argument and Proof • Argument • John is old because • he is aged 82

5. Arguments may introduce new information Speaker may assume John is man, but hearer knows he is a tortoise Proof John is aged 82 John is a man All men aged greater than 70 are old 82 > 70 Therefore, John is old Argument and Proof • Argument • John is old because • he is aged 82

6. Legal Argument • Legal Argument displays these typical characteristics of argument: • Unstated background and uncontested facts • Open texture and context dependent interpretation • New information and considerations

7. Arguments are Defeasible • A sound proof has to be accepted • But arguments are inherently and inescapably defeasible • They may be accepted, or challenged • Different audiences may respond differently, accepting for different reasons, or offering different challenges • The challenge can be accepted and the argument withdrawn, or it can be rebutted • Thus arguments are embedded in a dialectic context – and the audience is important

8. Arguments Based on Cases Wyoming Rutgers Amherst GREBE Branting Industrial Injuries Semantic Net Based Pittsburgh SMILE IBP Ashley and Bruninghaus Trade Secrets Law Outcome Prediction

9. Arguments Based on Cases • This was a focus of AI and Law from the beginning • I will focus on • HYPO (Rissland and Ashley) • CATO (Ashley and Aleven) • Both systems operate in US Trade Secrets Law

10. HYPO • Main Features • Three-Ply Argument Structure • Use of Dimensions to Represent and Compare Cases

11. Three Ply Argument • First Ply: • A case is cited by proponent • Second Ply: • The citation is attacked by opponent • By distinguishing the case • With a counter example • Third Ply: • The attack is rebutted by proponent • Distinguishing the counter examples

12. Three Ply Argument • Provides a simple but effective way of organising the argument • Is clearly adversarial in nature • Allows for both distinguishing and counter examples • Can be considered as an argument scheme

13. Dimensions • A dimension is a feature of the case which may need to be considered • In Trade Secret Law e.g. • Security Measures Adopted • Disclosures Subject to Restrictions • Competitive Advantage Gained

14. Dimensions • Are associated with • Preconditions • A range • Facts which determine the position within the range • A direction

15. Security Measures Adopted • Precondition • The plaintiff adopted some security measures • Range • From Minimal measures through some physical measures to nondisclosure agreements • Facts • List of security measures adopted • Direction • Stronger measures favour the plaintiff

16. Disclosures Subject to Restriction • Precondition • Some disclosures were restricted • Range • 0-100% of disclosures restricted • Facts • Percentage of disclosures restricted • Direction • Plaintiff favoured by more restricted disclosures

17. Competitive Advantage Gained • Precondition • Defendant saved development cost • Range • $10,000 - $10,000,000 • Facts • Plaintiff development time and cost • Defendant development time and cost • Direction • Greater savings favour plaintiff

18. π = plaintiff ∆ = defendant HYPO Trade Secret Example CASE16 Yokana (∆) F7 Brought-Tools (π) F10 Secrets-Disclosed-Outsiders (∆) F16 Info-Reverse-Engineerable (∆) CASE30 American Precision (π) F7 Brought-Tools (π) F16 Info-Reverse-Engineerable (∆) F21 Knew-Info-Confidential (π) CASE Mason (?) F1 Disclosure-in-Negotiations (∆) F6 Security-Measures (π) F15 Unique-Product (π) F16 Info-Reverse-Engineerable (∆) F21 Knew-Info-Confidential (π) F10 (∆) F9 (π) Yokana(∆) F7 (π) F16 (∆) American Precision (π) Mason (?) F1 (∆) F21 (π) F6 (π) F15 (π) CFS F19 (∆) F18 (π)

19. Comparing Cases • On the basis of similarities between past cases and the current fact situation, HYPO forms a case lattice

20. Case Lattice

21. Typically • The first level will contain both plaintiff and defendant cases • These are available to be cited • KFC, American Precision or Digital Development for plaintiff • Speciner, Carver or Speedry for defendant • If no case is available at the first level, we would need to descend a level until we found a case supporting our side • If F1 absent, Midland Ross or Yokana for defendant

22. First Ply (for Plaintiff) • Where disclosure in negotiations, security measures, knew information confidential and unique product, plaintiff should win. Digital Development • Note that pro-defendant factors are included here

23. Distinguishing • Either additional pro-defendant factor in current case • Or additional pro-plaintiff factor in cited case • Thus we may distinguish Mason from Digital Development since the product was reverse engineerable in Mason but not Digital Development. • Note that Unique Product does not distinguish Mason from KFC – it makes Mason better

24. Counter Example • A case at the same level of the case lattice held for the other side • E.g. Carver is CE to Digital Development • Better a case with all the shared factors and more (“trumping CE”) • E.g. American Precision if Midland Ross cited for the defendant

25. Third Ply - Rebuttal • Distinguishes the counter examples • E.g. Carver is distinguishable because security measures, knew information confidential and unique product in Mason, but not Carver

26. Argument, not a Decision • Except for the trumping, more on point, counter example, we may choose which side should win • We may reject the distinctions as unimportant • We may follow the cited case or the counter example

27. CATO • Also in US Trade Secrets Law • Also uses 3 ply argument • But • Uses factors not dimensions • Organises factors into a hierarchy, allowing additional argument moves • Some additional rebutting moves

28. Factors • No degree – factors either apply or do not apply • The presence of a factor always favours either the plaintiff or the defendant • Security measures – plaintiff • No security measures – defendant • Outsider disclosures restricted – plaintiff • Competitive advantage - plaintiff

29. Factor Hierarchy Info Trade Secret -p Info valuable -p Efforts to maintain Secrecy -p Security Measures p No Security Measures - d Competitive Advantage -p Waiver of Confidentiality - d

30. Emphasising and Downplaying Distinctions • Precedent: No security measures • Case 1: Waiver of Confidentiality • Case 2: Security Measures • Case1 and Case 2 can both be distinguished because no security measures is absent • Case 1 can downplay the distinction because there is an alternative argument against efforts to maintain secrecy • Case 2 can emphasise the distinction, because there is now no argument against efforts to maintain secrecy Confidentiality

31. Argument Moves in CATO • Analogising a case to a past case with a favourable outcome • Distinguishing a case with an unfavourable outcome;. • Downplaying the significance of a decision; • Emphasising the significance of a distinction; • Citing a favourable case to emphasise strengths; • Citing a favourable case to argue that weaknesses • are not fatal; • Citing a more on point counterexample to a case cited • by an opponent; • Citing an as on point counter example to a case cited • by an opponent.

32. Arguments Based on Cases • Cases are compared according to common features • Features tend to be at a level of abstraction above facts (issues) • Arguments mainly based of differences between cases • And the significance of these differences

33. Arguments Based on Rules • In Law, rules often conflict • The person named in a will should inherit • A murderer should not inherit • Conflicting rules provide an argument for and an argument against • How do we resolve such arguments?

34. Types of Conflict • Rules may conflict in several ways: • Contradictory conclusions • If P then Q, If R then not Q • Denial of premises • If P then Q, if R then not P • Rule inapplicable • If P then Q, if R then not (if P then Q)

35. Resolution Through General Principles • Prefer most specific rule • Statutes are often written as general rule and exceptions • Prefer most recent rule • A recent case is preferred to an old one • Prefer most authoritative rule • Supreme court better than lower courts • These principles can conflict • No general ordering seems possible

36. Weighing Reasons • We can see the antecedents as reasons for the conclusion • Some reasons may be stronger than others • We should prefer the stronger reasons to the weaker reasons

37. Explicit Rule Priorities • We can simply state which of a pair of conflicting rules has priority over the other • Note: such priorities may themselves be the subject of debate

38. Dialogical Justification P Q Proponent wins R  ¬ Q Opponent wins S  ¬ R Proponent wins T  ¬ (S  ¬ R) Opponent wins Proponent wins U  ¬ T

39. Reconstruction of HYPOPrakken and Sartor • Cases are represented as 3 implications: • (i) if pro-plaintiff factors then plaintiff • (ii) if pro-defendant factors then defendant • (iii) (i) < (ii) if defendant won, else (ii) < (i) • May be broadened by omitting factors • May be distinguished • Are deployed in a dialogue game

40. π = plaintiff ∆ = defendant HYPO Trade Secret Example CASE16 Yokana (∆) F7 Brought-Tools (π) F10 Secrets-Disclosed-Outsiders (∆) F16 Info-Reverse-Engineerable (∆) CASE30 American Precision (π) F7 Brought-Tools (π) F16 Info-Reverse-Engineerable (∆) F21 Knew-Info-Confidential (π) CASE Mason (?) F1 Disclosure-in-Negotiations (∆) F6 Security-Measures (π) F15 Unique-Product (π) F16 Info-Reverse-Engineerable (∆) F21 Knew-Info-Confidential (π) F10 (∆) F9 (π) Yokana(∆) F7 (π) F16 (∆) American Precision (π) Mason (?) F1 (∆) F21 (π) F6 (π) F15 (π) CFS F19 (∆) F18 (π)

41. Example • Yokana gives 3 rules • R1: F7  P • R2: F16 & F10  D • R3: R2 > R1 • American Precision gives 3 rules • R4: F7 & F21  P • R5: F16  D • R6: R4 > R5

42. Rationales – Loui and Norman • This records the progress of the dispute which may be important. • Consider a precedent which has F1 and F2 favouring plaintiff and F3 favouring the defendant and was won by plaintiff • Given a new case with only F1 it is unclear that the plaintiff should win • But suppose F2 was used to defeat F3: Now it can be seen that F1 can stand alone

43. R4: F1  P R2: F3  D R5: F2  not (F3  D) R6: R5 > R2 Now we can confidently apply R4 R1: F1 & F2  P R2: F3  D R3: R1 > R2 Not clear that R4: F1  P Compare We need a record of the dispute to decide which description is the right one

44. Argumentation Frameworks • We can often view a legal dispute as a set of conflicting arguments • P.M. Dung has developed an elegant way of looking at and reasoning about sets of conflicting arguments

45. Dung’s Argument Framework • Introduced in AIJ 1995 • Arguments at their most abstract • Only: which other arguments does an argument attack? • Attacks always succeed • We cannot accept an argument and its attacker

46. Definitions An argumentation framework is a pair AF = <AR, attacks> • Where AR is a set of arguments and attacks is a binary relation on AR, i.e. attacksAR  AR. An argument AAR is acceptable with respect to set of arguments S if: (x)((xAR) &(attacks(x,A))  (y)(y S) & attacks(y,x). A set S of arguments isconflict-freeif (x) (y)( xS) & (y S) & attacks(x,y). A conflict-free set of arguments S is admissible if (x)((xS)  acceptable(x,S).

47. Preferred Extension • A set of arguments S in an argumentation framework AF is a preferred extension if it isa maximal (with respect to set inclusion) admissible set of AR. • Preferred Extensions are interesting because they represent maximal coherent positions, able to defend themselves against all attackers • BUT: there may be multiple preferred extensions, and no way to choose between them

48. Odd Cycle Preferred Extension is the empty set We can’t accept Anything here a Akin to Paradoxes b c

49. Even Cycle We can accept Either a and c Or b and d Two Preferred Extensions {a,c} and {b,d} a d b Akin to Dilemmas c

50. In general • Every AF has a preferred extension • Which may be the empty set • AFs do not have a unique preferred extension • Even cycles give rise to choices • An argument may be in every preferred extension (sceptically acceptable) • An argument may be in some preferred extensions (credulously acceptable) • An argument may be in no preferred extension (indefensible)