reading agendas between the lines, an exercise
TRANSCRIPT
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Reading Agendas between the lines an exercise
Giovanni Sileno ([email protected]),Alexander Boer, Tom van EngersLeibniz Center for LawUniversity of Amsterdam
30 August 2016 - AI4J Workshop / ECAI 2016 @ Den Haag
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Problem context
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socialsystem
How people behave..
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sourcesof law
socialsystem
What the law states..
How people behave..
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sourcesof law
socialsystem
services
What the law states..
How people behave..
How public administrations implements the law..
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sourcesof law
socialsystem
services
What the law states..
How people behave..
How public administrations implements the law..
are three matters only loosely coupled
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sourcesof law
socialsystem
services
Focus on services/social system
What the law states..
How people behave..
How public administrations implements the law..
● non-compliance
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sourcesof law
socialsystem
services
Focus on services/social system
What the law states..
How people behave..
How public administrations implements the law..
● non-compliance
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sourcesof law
socialsystem
services
Focus on services/social system
What the law states..
How people behave..
How public administrations implements the law..
● non-compliance● new user requirements
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Diagnosis of social systems
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Diagnosis
● Diagnosis starts from the presumption that a failure occurred in the system.
● But what counts as a failure?
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Diagnosis of a designed artifact
● In case of a designed artifact, we know the function of the system, so if does not behave how it was supposed to, this is a failure.
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Diagnosis of a designed artifact
● In case of a designed artifact, we know the function of the system, so if does not behave how it was supposed to, this is a failure.
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Diagnosis of a designed artifact
● In case of a designed artifact, we know the function of the system, so if does not behave how it was supposed to, this is a failure.
● Two types of failure:
– operational failure – bad design
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Consistency-based diagnosis
● In case of electronic components, for instance, manufacturers furnish the normal behaviour of the item.
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Consistency-based diagnosis
● In case of electronic components, for instance, manufacturers furnish the normal behaviour of the item.
failure = inconsistency with nominal specifications
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Consistency-based diagnosis
● In case of electronic components, for instance, manufacturers furnish the normal behaviour of the item.
failure = inconsistency with nominal specifications
● Usual diagnostic problem: recognize the minimal set of components that produces the inconsistency
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Consistency-based diagnosis
● In case of electronic components, for instance, manufacturers furnish the normal behaviour of the item.
failure = inconsistency with nominal specifications
-a :- not a.
In AI terms ~ default negation implies strong negation
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Abductive diagnosis
● In other domains, we naturally create models of faulty behaviour, because there may be non-pathological cases in which things do not go as expected. i.e. not all misalignments to the norm are failures.
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Abductive diagnosis
● In other domains, we naturally create models of faulty behaviour, because there may be non-pathological cases in which things do not go as expected. i.e. not all misalignments to the norm are failures.
failure = consistency with explicitly faulty model
In AI terms ~ default negation is different from strong negation
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Diagnosis of a social system
● What counts as a failure in a social system?
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Diagnosis of a social system
● What counts as a failure in a social system? ● A wrong supposedly occurs when there are unmet
social expectations (for at least one of the participants)
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Diagnosis of a social system
● What counts as a failure in a social system? ● A wrong supposedly occurs when there are unmet
social expectations (for at least one of the participants)
● These are specified via normative directives: prohibitions, obligations, etc.
– In principle, a wrong is detectable from the violation of normative directives.
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Diagnosis of a social system
● What counts as a failure in a social system? ● A wrong supposedly occurs when there are unmet
social expectations (for at least one of the participants)
● These are specified via normative directives: prohibitions, obligations, etc.
– In principle, a wrong is detectable from the violation of normative directives..
but proceeding “literally” is not sufficient.
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Types of failure
e.g. duty to pay taxes
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Types of failure
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)
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Types of failure
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)● pay a wrong amount in respect to the declared
income (syntaxic, quantitative failure)
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Types of failure
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)● pay a wrong amount in respect to the declared
income (syntaxic, quantitative failure)● pay the correct but not the right amount, by using
tax evasion schemes (semantic failure)
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Types of failure
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)● pay a wrong amount in respect to the declared
income (syntaxic, quantitative failure)● pay the correct but not the right amount, by using
tax evasion schemes (semantic failure)
The “semantic” failure is the most difficult to be catched!
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sourcesof law
legal norms
Sources of knowledge
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sourcesof law
services
legal norms
businessprocess models
Sources of knowledge
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sourcesof law
services
legal norms
businessprocess models
Sources of knowledge
Usual focus of compliance-
checking methods
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sourcesof law
services
legal norms
businessprocess models
Sources of knowledge
Usual focus of compliance-
checking methods
..but not adequate to capture the social semantics
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sourcesof law
socialsystem
services
stories,experiences
legal norms,cases
businessprocess models
Sources of knowledge
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sourcesof law
socialsystem
services
stories,experiences
legal norms,cases
businessprocess models
Sources of knowledge
Which representational ground should we
consider?
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sourcesof law
socialsystem
services
agent-rolesstories,
experienceslegal norms,
cases
agent-rolemodels
businessprocess models
Integrating model: agent-role
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sourcesof law
socialsystem
services
agent-rolesstories,
experienceslegal norms,
cases
agent-rolemodels
businessprocess models
Integrating model: agent-role
agent-role =coordination of roles (script + topology)
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sourcesof law
socialsystem
services
agent-rolesstories,
experienceslegal norms,
cases
agent-rolemodels
businessprocess models
Integrating model: agent-role
agent-role =coordination of roles (script + topology)
NB: the model abstracts the individuals
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An exercise of application
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Domain: Real-estate transactions
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Normal sale
Real estate A, worth 500.000 €
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Normal sale
Real estate A, worth 500.000 €With 6% transfer tax, if sold 30.000 € taxes
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Hidden payment scenario
X wants to give to Y 300.000 €.X sells Real estate A (worth 500.000 €) for 200.000 € to Y
with 6% transfer tax, 10.000 €.(taxes for a direct transfer would be higher)
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Swap-scheme scenario
Owner: X. Real estate A, worth 10.000.000 €
Owner: Y. Real estate B, worth 10.000.000 €
X wants B, Y wants A.
6% transfer tax: if sold, 1.200.000 € (total)
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Swap-scheme scenario
Owner: X. Real estate A, worth 10.000.000 €
Owner: Y. Real estate B, worth 10.000.000 €
X wants B, Y wants A.
“Why don't we decrease the nominal price?“
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Swap-scheme scenario
Owner: X. Real estate A, sold for 5.000.000 €
Owner: Y. Real estate B, sold for 5.000.000 €
X wants B, Y wants A.
6% transfer tax: 600.000 € (total)
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Swap-scheme topology
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Swap-scheme topology
internal topologies – intentional coordination
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Swap-scheme topology
internal topologies – intentional coordination
base for concentration of interests (company, family, etc.)
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Swap-scheme topology
external topology – scenario coordination
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Swap-scheme topology
external topology – scenario coordination
This may be contingent...
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Monitoring and diagnosis
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Taking the diagnoser view
bounded perception
● Sale declarations● Sale payments
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Monitoring and diagnosis● The observation abilities of the diagnoser are
necessarily limited. ● Cognitive resources for reasoning are also limited.
It does not make sense to interpret all the data.
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Monitoring and diagnosis● We consider an architecture affine to the Dual
Process theory of reasoning:
– monitoring (fast, reactive) for selecting suspicious cases
– diagnosis (slow, reflective) for investigating them.
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Monitoring
Monitoring filters can be constructed by constrast of normal cases with abnormal ones.
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)
– Use a timeout rule, asynchronous check
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Monitoring
Monitoring filters can be constructed by constrast of normal cases with abnormal ones.
e.g. duty to pay taxes● not to pay taxes (syntaxic, qualitative failure)
– Use a timeout rule, asynchronous check● pay a wrong amount in respect to the declared
income (syntaxic, quantitative failure)
– Use an operational rule, synchronous check
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Monitoring
Monitoring filters can be constructed by constrast of normal cases with abnormal ones.
e.g. duty to pay taxes● pay the correct but not the right amount, by using
tax evasion schemes (semantic failure)
– contrast determines threshold conditions
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Monitoring
Monitoring filters can be constructed by constrast of normal cases with abnormal ones.
e.g. duty to pay taxes● pay the correct but not the right amount, by using
tax evasion schemes (semantic failure)
– contrast determines threshold conditions
In our case, adequate thresholds are decided upon
average market price.
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Selection rule in Prolog
suspiciousPrice(Price, Estate, Time) :-marketPrice(MarketPrice, Estate, Time),Price =< (MarketPrice * 60)/100.
suspiciousSale(Seller, Buyer, Estate, Price, Time) :-declaration(sale(Seller, Buyer, Estate, Price, Time)),suspiciousPrice(Price, Estate, Time).
Suppose the threshold is placed at -40% of market price (e.g. after statistical analysis):
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Diagnosis (main action)
ActionEvidenceOfSwap(sale(Seller1, Buyer1, EstateA, PriceA, T1),sale(Seller2, Buyer2, EstateB, PriceB, T2)
) :-suspiciousSale(Seller1, Buyer1, EstateA, PriceA, T1),suspiciousSale(Seller2, Buyer2, EstateB, PriceB, T2),not(EstateA = EstateB),not(Seller1 = Seller2), not(Buyer1 = Buyer2).
At this point, we check if suspicious sales are consistent with a swap-scheme agent-role:
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Diagnosis (additional evidence)
actionAndCircumstantialEvidenceOfSwap(sale(Seller1, Buyer1, EstateA, PriceA, T1),sale(Seller2, Buyer2, EstateB, PriceB, T2)
) :-actionEvidenceOfSwap(sale(Seller1, Buyer1, EstateA, PriceA, T1),sale(Seller2, Buyer2, EstateB, PriceB, T2)),relatedTo(Seller1, SharedStructure1),relatedTo(Buyer2, SharedStructure1),relatedTo(Seller2, SharedStructure2),relatedTo(Buyer1, SharedStructure2).
..and when suspicious coordinated behaviour is found, we look for circumstantial evidence about structures of concentration of interests:
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Swap-scheme generalization● Through computational means, we can
easily generalize the investigation ton-steps swaps (obfuscasting traces of coordination).
…this includes the “hidden payment” scenario!
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Conclusion
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Conclusion● This exercise showed a simplified application of a
more general framework
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Conclusion● This exercise showed a simplified application of a
more general framework
– The most important message is that...
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Conclusion● This exercise showed a simplified application of a
more general framework
– The most important message is that...
agency trascends individuals.
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Conclusion● This exercise showed a simplified application of a
more general framework
– The most important message is that...
agency trascends individuals...and we require abstractions like agent-roles to pass to higher-level interpretation.
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Further developments● This exercise showed a simplified application of a
more general framework
– Prolog conflates strong negation with default negation. What if some information is simply unavailable? Other approaches (EBA) would be more appropriate.
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Further developments● This exercise showed a simplified application of a
more general framework
– Prolog conflates strong negation with default negation. What if some information is simply unavailable? Other approaches (EBA) would be more appropriate.
– Scenarios should be collected in an adequate representation for the modeler taking causation into account. We suggested an extension to Petri nets, with normative and agentive positions.
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Further developments● This exercise showed a simplified application of a
more general framework
– For the acquisition, in previous work we proposed an intecremental method, starting from UML-diagrams (similarly to requirement engineering practices)
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Further developments● This exercise showed a simplified application of a
more general framework
– For the acquisition, in previous work we proposed an intecremental method, starting from UML-diagrams (similarly to requirement engineering practices)
– About computational complexity, existing decomposition techniques could be used in principle to compile the database of scenarios offline, and for realtime exploitation.