Henry Prakken JURIX tutorial Krakow 10 December, 2014 Formal Models of Balancing in Legal Cases (1)

General setting Inference by constructing and comparing arguments and counterarguments Usually legal arguments apply rules Conflicting rules, exceptions But some legal domains only have factors pro and con How to build and compare arguments in such domains?

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Attack on conclusion

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Saving DNA of all citizens but crime does not reduce crime The UK saved DNA of many citizens but crime did not reduce Attack on premise …

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Saving DNA of all citizens but crime does not reduce crime Prof. P says that … The UK saved DNA of many citizens but crime did not reduce … often becomes attack on intermediate conclusion

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Prof. P says that … Prof. P has political ambitions People with political ambitions are not objective Prof. P is not objective Attack on inference

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Prof. P says that … Saving DNA of all citizens does not endanger privacy People who don’t do wrong have nothing to hide Indirect defence

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Saving DNA of all citizens but crime does not reduce crime Prof. P says that … Prof. P has political ambitions People with political ambitions are not objective Prof. P is not objective Saving DNA of all citizens does not endanger privacy People who don’t do wrong have nothing to hide The UK saved DNA of many citizens but crime did not reduce

AB C D E Dung

AB C D E 1. An argument is In iff all arguments that defeat it are Out. 2. An argument is Out iff some argument that defeats it is In. Dung P.M. Dung, On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming, and n–person games. Artificial Intelligence, 77:321–357, Grounded semantics minimises In labelling Preferred semantics maximises In labelling

11 Justification status of arguments A is justified if A is In in all labellings A is overruled if A is Out in all labellings A is defensible otherwise

AB C D E Example (grounded labelling) Justified: C and D Overruled: A Defensible: B and E

We should save DNA of all citizens Saving DNA of all citizens reduces crime Reducing crime is good We should not save DNA of all citizens Saving DNA of all citizens endangers privacy Endangering privacy is bad Saving DNA of all citizens but crime does not reduce crime Prof. P says that … Prof. P has political ambitions People with political ambitions are not objective Prof. P is not objective Saving DNA of all citizens does not endanger privacy People who don’t do wrong have nothing to hide The UK saved DNA of many citizens but crime did not reduce C AB E D

Logics for Defeasible Argumentation Chain inferences into arguments Deductive inferences Premises guarantee conclusion Defeasible inferences Premises create presumption for conclusion Attack arguments with counterarguments See which attacks result as defeats with preferences Apply Dung (1995) to arguments + defeat Modgil & me Pollock S. Modgil & H. Prakken, The ASPIC+ framework for structured argumentation: a tutorial. Argument & Computation 5 (2014): 31-62

Evaluating arguments Internal justification: Does each step instantiate an acceptable inference scheme? Deductive or defeasible External justification: have all its counterarguments been refuted? Are its premises acceptable? For defeasible inferences in the argument: what about attacks on the inference or its conclusion?

Contents Factor-based reasoning Two-valued factors Preferences from precedents More or less abstract factors Many-valued factors Precedential constraint Preferences from values

Running example factors: misuse of trade secrets Some factors pro misuse of trade secrets: F2 Bribe-Employee F4 Agreed-Not-To-Disclose F6 Security-Measures F15 Unique-Product F18 Identical-Products F21 Knew-Info-Confidential Some factors con misuse of trade secrets: F1 Disclosure-In-Negotiations F16 Info-Reverse-Engineerable F23 Waiver-of-Confidentiality F25 Info-Reverse-Engineered HYPO Rissland & Ashley CATO Aleven & Ashley

Citing precedent Mason v Jack Daniels Distillery (Mason) – undecided. F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F15 Unique-Product (p) F16 Info-Reverse-Engineerable (d) F21 Knew-Info-Confidential (p) Bryce and Associates v Gladstone (Bryce) – plaintiff F1 Disclosure-In-Negotiations (d) F4 Agreed-Not-To-Disclose (p) F6 Security-Measures (p) F18 Identical-Products (p) F21 Knew-Info-Confidential (p) Plaintiff cites Bryce because of F6,F21

Distinguishing precedent Mason v Jack Daniels Distillery (Mason) – undecided. F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F15 Unique-Product (p) F16 Info-Reverse-Engineerable (d) F21 Knew-Info-Confidential (p) Bryce and Associates v Gladstone (Bryce) – plaintiff F1 Disclosure-In-Negotiations (d) F4 Agreed-Not-To-Disclose (p) F6 Security-Measures (p) F18 Identical-Products (p) F21 Knew-Info-Confidential (p) Plaintiff cites Bryce because of F6,F21 Defendant distinguishes Bryce because of F4,F18 and F16

Counterexample Mason v Jack Daniels Distillery – undecided. F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F15 Unique-Product (p) F16 Info-Reverse-Engineerable (d) F21 Knew-Info-Confidential (p) Robinson v State of New Jersey – defendant. F1 Disclosure-In-Negotiations (d) F10 Secrets-Disclosed-Outsiders (d) F18 Identical-Products (p) F19 No-Security Measures (d) F26 Deception (p) Defendant cites Robinson because of F1

Distinguishing counterexample Mason v Jack Daniels Distillery – undecided. F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F15 Unique-Product (p) F16 Info-Reverse-Engineerable (d) F21 Knew-Info-Confidential (p) Robinson v State of New Jersey – defendant. F1 Disclosure-In-Negotiations (d) F10 Secrets-Disclosed-Outsiders (d) F18 Identical-Products (p) F19 No-Security Measures (d) F26 Deception (p) Defendant cites Robinson because of F1 Plaintiff distinguishes Robinson because of F6,F15,F21 and F10,F19

Plaintiff: I should win because My case shares pro factors F6 and F21 with Bryce, which was won by plaintiff Defendant: Unlike the present case, Bryce had pro factors F4 and F18 Defendant: I should win because my case shares con factor F1 with Robinson, which was won by defendant Defendant: Unlike Bryce, the present case has con factor F16 Plaintiff: Unlike Robinson, the present case has pro factors F6, F15 and F21 Plaintiff: Unlike the present case, Robinson had con factors F10 and F19

Basic scheme for reasoning with two-valued factors AS2: The Pro-factors of current are P The Con-factors of current are C P are preferred over C Current should be decided Pro The Pro-factors of current are P The Con-factors of current are C C are preferred over P Current should be decided Con

Preferences from precedents (1) AS2: The Pro-factors of precedent are P The Con-factors of precedent are C precedent was decided Pro P are preferred over C Limitation 1: the current case will often not exactly match a precedent

A fortiori reasoning with two-valued factors AS3: P are preferred over C P+ are preferred over C- P+ = P plus zero or more additional pro-factors C- = C minus zero or more con factors Limitation 2: not all differences with a precedent will make a current case stronger

(snapshot of) CATO Factor Hierarchy F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d) Vincent Aleven

Distinguishing F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Emphasising distinctions F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Downplaying distinctions F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Exploiting factor hierarchies (1): current misses pro factor AS4: P1 are preferred over C P2 substitutes P1 P2 are preferred over C Def1: Factor set P2 substitutes factor set P1 iff For all factors p1 in P1 that are not in P2 there exists a factor p2 in P2 that substitutes p1 Def2: Factor p2 substitutes factor p1 iff p1 instantiates abstract factor p3 and p2 instantiates abstract factor p3

Example of substitution Precedent – plaintiff F1 Disclosure-In-Negotiations (d) F4 Agreed-Not-To-Disclose (p) F21 Knew-Info-Confidential (p) New case – undecided F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F21 Knew-Info-Confidential (p) {F4,F21} > {F1} because of precedent Plaintiff wants to argue that {F6,F21} > {F1}

Example of substitution (2) AS2: The Pro-factors of Precedent are {F4,F21} The Con-factors of Precedent are {F1} precedent was decided Pro {F4,F21} are preferred over {F1} AS4: {F4,F21} are preferred over {F1} {F6,F21} substitutes {F4,F21} {F6,F21} are preferred over {F1}

Example of substitution (3) AS1: The Pro-factors of Current are {F6,F21} The Con-factors of Current are {F1} {F6,F21} are preferred over {F1} Current should be decided Pro

The Pro-factors of Current are {F6,F21} The Con-factors of Current are {F1} {F6,F21} > {F1} {F4,F21} > {F1} {F6,F21} substitutes {F4,F21} F4 instantiates F102 F6 instantiates F102 F6 substitutes F4 The Pro- factors of Precedent are {F4,F21} The Con- factors of Precedent are {F1} Precedent was decided Pro

Current should be decided Pro The Pro-factors of Current are {F6,F21} The Con-factors of Current are {F1} {F6,F21} > {F1} {F4,F21} > {F1} {F6,F21} substitutes {F4,F21} F4 instantiates F102 F6 instantiates F102 F6 substitutes F4 The Pro- factors of Precedent are {F4,F21} The Con- factors of Precedent are {F1} Precedent was decided Pro

Distinguishing F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Emphasising distinctions F101: Info Trade Secret (p) F102: Efforts to maintain secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Downplaying distinctions F101: Info Trade Secret (p) F102: Efforts to maintain Secrecy (p) F104: Info valuable (p) F4: Agreed not to disclose (p) F1: Disclosures in negotiations (d) F6: Security measures (p) F15: Unique product (p) Misuse of Trade Secret (p) F120: Info legitimately obtained elsewhere (d)

Exploiting factor hierarchies (2): current has additional con factor AS5: P are preferred over C P cancels C+ P are preferred over C+ Def3: Factor set P cancels factor set C iff For all factors c1 in C+ that are not in C there exists a factor p1 in P such that p1 cancels c1 Def4: Factor p1 cancels factor c1 iff p1 instantiates abstract factor p2 and c1 is con abstract factor p2 and p1 is preferred over c1

Example of cancellation Precedent – plaintiff F15 Unique-Product (p) F21 Knew-Info-Confidential (p) F120 Info-Legitimately obtained elsewhere (d) New case – undecided F1 Disclosure-In-Negotiations (d) F4 Agreed-Not-To-Disclose (p) F15 Unique-Product (p) F21 Knew-Info-Confidential (p) F120 Info-Legitimately obtained elsewhere (d) {F15,F21} > {F120} because of precedent Plaintiff wants to argue that {F4,F15,F21} > {F1,F120}

Example of cancellation (2) AS2: The Pro-factors of Precedent are {F15,F21} The Con-factors of Precedent are {F120} Precedent was decided Pro {F15,F21} are preferred over {F120} AS3: {F15,F21} are preferred over {F120} {F4,F15,F21} are preferred over {F120}

Example of cancellation (3) AS5: {F4,F15,F21} are preferred over {F120} {F4,F15,F21} cancels {F1,F120} {F4,F15,F21} is preferred over {F1,F120} Def3: {F4,F15,F21} cancels factor set {F1,F120} since F4 cancels F1 Def4: F4 cancels F1 since F4 instantiates abstract factor F102 and F1 is con abstract factor F102 and F4 is preferred over F1

Current should be decided Pro The Pro-factors of Current are {F4,F15,F21} The Con-factors of Current are {F1,F120} {F4,F15, F21} > {F1,F120} {F15,F21} > {F120} {F4,F15,F21} cancels {F1,F120} F4 instantiates F102 F1 is con F102 F4 cancels F1The Pro- factors of Precedent are {F15,F21} The Con- factors of Precedent are {F120} Precedent was decided Pro {F4,F15,F21} > {F120} F4 > F1

From two-valued to many-valued factors (dimensions) Dimensions can have a value from an ordered range of values Numbers Anything else that can be ordered Notation: (dimension,value) or (d,v) Dimensions have polarities: conpro 0,1,2,…..…, 500, ….... Primary school, secondary school, Bsc, Msc, Dr <

Example dimensions in HYPO Number of disclosees (0,1,….) Competetive advantage (none, weak, moderate, strong) procon , ….... <

Example dimensions in HYPO Number of disclosees (0,1,….) Competetive advantage (none, weak, moderate, strong) conpro none weak moderate strong <

A fortiori reasoning with dimensions AS6: P1 are preferred over C1 P2 are at least as strong as P1 C1 are at least as strong as C2 P2 are preferred over C2 Def5: Set P2 of dimension-value pairs pro is at least as strong as set P1 of dimension-value pairs pro iff For all pairs (d,v1) in P1 there exists a pair (d,v2) in P2 such that v1 ≤ v2 Set C1 of dimension-value pairs con is at least as strong as set C2 of dimension-value pairs con iff For all pairs (d,v2) in C2 there exists a pair (d,v1) in C1 such that v1 ≤ v2

Example with dimensions (1) Precedent – defendant F1 Disclosure-In-Negotiations (d) F21 Knew-Info-Confidential (p) Fx Competetive-advantage = strong (p) Fy Number of disclosees = 10 (d) New case – undecided F1 Disclosure-In-Negotiations (d) F21 Knew-Info-Confidential (p) Fx’ Competetive-advantage = moderate (p) Fy Number of disclosees = 10 (d) {F21, Fx} < {F1,Fy} because of precedent Defendant wants to argue that {F21, Fx’} < {F1,Fy}

Example with dimensions (2) Precedent – defendant F1 Disclosure-In-Negotiations (d) F21 Knew-Info-Confidential (p) Fx Competetive-advantage = strong (p) Fy Number of disclosees = 10 (d) New case – undecided F1 Disclosure-In-Negotiations (d) F21 Knew-Info-Confidential (p) Fx’ Competetive-advantage = moderate (p) Fy’ Number of disclosees = 6 (d) {F21, Fx} < {F1,Fy} because of precedent Defendant wants to argue that {F21, Fx’} < {F1,Fy’}

What if the previous schemes do not apply? Which decisions are allowed by a body of precedents? Precedential constraint Where do preferences then come from?

Precedential constraint: consistency of preferences A preference relation < on factor sets is consistent if and only if there are no factor sets X and Y such that both X < Y and Y < X.

Precedential constraint: allowed and forced decisions Let < be determined by: A set S of precedents The preferences derivable from it by AS2 (preferences from precedent) AS3 (a fortiori for two-valued factors) Assume < is consistent Then a decision pro in a new case C is: allowed by S iff adding C with decision pro to S leaves < consistent. forced iff allowed and adding C with decision con to S makes < inconsistent

Following, distinguishing and overruling precedents Let Prec have pro factors P and con factors C and decision pro. Let Curr have pro factors Pcurr such that P is included in Pcurr. Following Prec = deciding Curr pro Distinguishing Prec = deciding Curr con where deciding Curr either pro or con is allowed Overruling Prec = deciding Curr con where deciding Curr pro is forced

Example (1) Precedent – plaintiff F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F21 Knew-Info-Confidential (p) F23 Waiver-of-Confidentiality (d) New Case – undecided F21 Knew-Info-Confidential (p) F23 Waiver-of-Confidentiality (d) F25 Info-Reverse-Engineered (d) {F6,F21} > {F1,F23} Pro = {F21} > {F23,F25} Con = {F21} < {F23,F25} Both pro and con allowed Deciding pro follows precedent Deciding con distinguishes precedent

Example (2) Precedent 1 – plaintiff F1 Disclosure-In-Negotiations (d) F6 Security-Measures (p) F21 Knew-Info-Confidential (p) F23 Waiver-of-Confidentiality (d) Precedent 2 – defendant F6 Security-Measures (p) F21 Knew-Info-Confidential (p) F25 Info-Reverse-Engineered (d) New Case – undecided F21 Knew-Info-Confidential (p) F23 Waiver-of-Confidentiality (d) F25 Info-Reverse-Engineered (d) {F6,F21} > {F1,F23} {F6,F21} < {F25} Pro = {F21} > {F23,F25} Con = {F21} < {F23,F25} Only con allowed Deciding pro overrules precedent 2 Deciding con follows precedent 2

What if the previous schemes do not apply? Which decisions are allowed by a body of precedents? Precedential constraint Where do preferences then come from?

Scheme for reasoning with promoted values Deciding current pro promotes set of values V1 Deciding current con promotes set of values V2 V1 is preferred over V2 Therefore, current should be decided pro

Scheme for inferring value orderings from cases Deciding precedent pro promotes set of values V1 Deciding precedent con promotes set of values V2 precedent was decided pro Therefore, V1 is preferred over V2

From factors to values case contains factor P Deciding case pro when it contains P promotes value V Therefore, deciding case pro promotes value V

Wild animals example Pierson v Post: Plaintiff is hunting a fox on open land. Defendant kills the fox. Keeble v Hickersgill: Plaintiff is a professional hunter. Lures ducks to his pond. Defendant scares the ducks away Young v Hitchens: Plaintiff is a professional fisherman. Spreads his nets. Defendant gets inside the nets and catches the fish. Slide by Trevor Bench-Capon

Pierson – defendant NotDefLiv: Defendant not pursuing livelihood (p) NotPlLiv: Plaintiff not pursuing livelihood (d) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Keeble – plaintiff NotDefLiv: Defendant not pursuing livelihood (p) PlLiv: Plaintiff pursuing livelihood (p) OwnLand: Plaintiff on own land (p) NotCaught: Plaintiff had not caught animal (d) Young – (defendant) DefLiv: Defendant pursuing livelihood (d) PlLiv: Plaintiff pursuing livelihood (p) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Factors in the wild animals cases Con = {PlLiv} < {NotOwnLand,NotCaught,DefLiv} Pro = {PlLiv} > {NotOwnLand,NotCaught,DefLiv} {NotDefLiv} < {NotPlLiv,NotOwnLand, NotCaught} {NotDefLiv,PlLiv, OwnLand} > {NotCaught}

Pierson – defendant NotDefLiv: Defendant not pursuing livelihood (p) NotPlLiv: Plaintiff not pursuing livelihood (d) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Keeble – plaintiff NotDefLiv: Defendant not pursuing livelihood (p) PlLiv: Plaintiff pursuing livelihood (p) OwnLand: Plaintiff on own land (p) NotCaught: Plaintiff had not caught animal (d) Young – (defendant) DefLiv: Defendant pursuing livelihood (d) PlLiv: Plaintiff pursuing livelihood (p) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Factors in the wild animals cases

Pierson – defendant NotDefLiv: Defendant not pursuing livelihood (p) NotPlLiv: Plaintiff not pursuing livelihood (d) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Keeble – plaintiff NotDefLiv: Defendant not pursuing livelihood (p) PlLiv: Plaintiff pursuing livelihood (p) OwnLand: Plaintiff on own land (p) NotCaught: Plaintiff had not caught animal (d) Young – (defendant) DefLiv: Defendant pursuing livelihood (d) PlLiv: Plaintiff pursuing livelihood (p) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d) Factors in the wild animals cases

Values Cval: Certainty and avoidance of litigation Eval: Economic benefit for society Pval: respecting Property From factors to values: Deciding pro when case contains PlLiv promotes Eval Deciding pro when case contains OwnLand promotes Pval Deciding pro when case contains Caught promotes Pval Deciding con when case contains NotCaught promotes Cval Deciding con when case contains DefLiv promotes Eval Values in the wild animals cases

Pierson – defendant NotDefLiv: Defendant not pursuing livelihood (p) NotPlLiv: Plaintiff not pursuing livelihood (d) NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d)Cval Keeble – plaintiff NotDefLiv: Defendant not pursuing livelihood (p) PlLiv: Plaintiff pursuing livelihood (p)Eval OwnLand: Plaintiff on own land (p)Pval NotCaught: Plaintiff had not caught animal (d)Cval Young – (defendant) DefLiv: Defendant pursuing livelihood (d)Eval PlLiv: Plaintiff pursuing livelihood (p)Eval NotOwnLand: Plaintiff not on own land (d) NotCaught: Plaintiff had not caught animal (d)Cval Values in the wild animals cases {} < {Cval} {Eval,Pval} > {Cval} Pro = {Eval} > {Eval,Cval} Con = {Eval} < {Eval,Cval}

Further refinements Promotion and demotion of values Degrees of promotion or demotion Absolute or marginal Probability of promotion or demotion