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Sense-making software for crime investigation: how to combine stories and arguments?

Sense-making software for crime investigation: how to combine stories and arguments?. Henry Prakken (& Floris Bex, Susan van den Braak, Herre van Oostendorp, Bart Verheij, Gerard Vreeswijk) New York, January 29th, 2007. Contents. A research project:

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Sense-making software for crime investigation: how to combine stories and arguments?

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  1. Sense-making software for crime investigation: how to combine stories and arguments? Henry Prakken (& Floris Bex, Susan van den Braak, Herre van Oostendorp, Bart Verheij, Gerard Vreeswijk) New York, January 29th, 2007

  2. Contents • A research project: • Building software that supports crime investigators • Investigate theoretical basis • Stories and causality in evidential reasoning • Abduction • Reasoning with testimonies: • Argumentation • Combining stories and testimonies: • abduction + argumentation

  3. Practical motivation • Crime investigation often one-sided, aiming to confirm a certain hypothesis • Dutch criminal procedure is inquisitory: • Judges rely on police case files • Very little investigation in court • ... • So a lot can go wrong

  4. The intended software: a sense-making system • No knowledge inside, but • Supports human users in structuring and visualising their thinking • Can calculate with these structures • Can link them with case files • Should be based on an account of evidentiary reasoning that is: • Prescriptive (supporting rational thinking) • Natural (close to the way crime investigators think)

  5. Anchored Narratives Theory(Crombag, van Koppen & Wagenaar) • A rational and natural theory of evidentiary reasoning? • Recognises importance of • stories (timelines!) • Generalisations • Find plausible causal links within story • Anchor stories in evidence • But theoretically underdeveloped • Our aim: investigate theoretical foundations of ANT • Causation • Testimonies

  6. Stories involve causation • Stories are (at least) a sequence of events on a timeline • Events are supposedly caused by earlier events • Physical causation • Mental causation • Reasoning with causal information: • Prediction: assume or observe event, predict what will happen next • Explanation: observe event, explain what could have caused it

  7. Example: the King case (1) • Fact: King was beaten up by mr. Zomerdijk in backyard of Zomerdijk’s house • Prosecution’s story • King (a convicted thief) was up to no good • King climbs into backyard of Zomerdijk family • King enters bedroom • King steps on toy • Mr. Zomerdijk hears sound • Mr. Zomerdijk goes to bedroom • King closes door and runs away

  8. Example: the King case (2) • Fact: King was beaten up by mr. Zomerdijk in backyard of Zomerdijk’s house • Defence’s story • King climbs into backyard of Zomerdijk family • Wind opens bedroom door • Wind hits toy • Mr. Zomerdijk hears sound • Mr. Zomerdijk goes to bedroom • Mr. Zomerdijk sees King in backyard

  9. Representing causal knowledge • Explanation with evidential rules: Deduction: • Explanation with causal rules: Abduction: Smoke means Fire Smoke Fire Effect  Cause Effect Cause Cause  Effect Effect Cause Fire causes Smoke Smoke Fire

  10. Abductive-logical models • Simulate abduction with deduction: • Given: • causal rules T • ‘explanandum’ F • Hypothesise a cause C such that T with C logically implies F (“C explains F”) • Compare all alternative explanations • How much additional evidence is explained? • How much additional evidence is contradicted? • …

  11. Toy makes a sound The door is closed Observations Explanations as causal networks of events

  12. King closes door King enters house King steps on toy Toy makes a sound The door is closed Observations Explanations as causal networks of events

  13. King closes door King enters house King steps on toy Toy makes a sound The door is closed Observations Explanations as causal networks of events The wind opens the door The wind hits the toy The wind closes the door Loud bang

  14. King closes door King enters house King steps on toy Toy makes a sound The door is closed Observations No loud bang was heard Explanations as causal networks of events The wind opens the door The wind hits the toy The wind closes the door Loud bang

  15. Witness wants to protect himself Witness Z says “I heard a sound” Witness Z says “the door was closed” Witness Z often imagines sounds A problem(?): testimonies must also be explained King closes door King enters house King steps on toy Toy makes a sound The door is closed Observations

  16. Testimony principle is not a causal but an evidential rule • Testimony principle not represented from-cause-to-effect: • but from-cause-to-effect: • Truth of P is the usual cause of “P”. Other causes of are exceptions. • Reasoning is then modelled as constructing and comparing (defeasible) arguments P => Witness says “P” Witness says “P” => P

  17. King closes door King enters house King steps on toy Toy makes a sound The door is closed ‘Observations’ Witness Z is not sincere Witness Z says “I heard a sound” Witness wants to protect himself Further evidence needed! Combining abduction and argumentation

  18. No loud bang was heard The full picture King closes door King enters house King steps on toy Toy makes a sound The door is closed Observations The wind opens the door The wind hits the toy The wind closes the door Loud bang

  19. Conclusion • Combining abduction for representing stories and argumentation for reasoning about sources of evidence • arguably is natural • can arguably be given a sound rational basis • But all this should be further investigated

  20. Arguments Assault hitting intent p e1 e3 e2

  21. Counterarguments Assault Selfdefence attacked hitting intent p q e1 e3 e5 e2 e4

  22. Reinstatement Assault Selfdefence attacked Not attacked hitting intent p q e1 e3 e5 e6 e7 e2 e4

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