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

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)

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. 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)

4. 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

5. 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

6. 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

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

8. 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

9. 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

10. 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

11. 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

12. Testimony principle is not a causal but an evidential rule • Testimony principle not represented from cause to effect: • but from effect to cause: • 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

13. 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

14. 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