1. Explanation Infrastructure Supporting Transparency and Accountability Deborah L. McGuinness Co-Director and Senior Research Scientist Knowledge Systems, AI Laboratory, Stanford University Joint work with Li Ding, Cynthia Chang, Vasco Furtado, Paulo Pinheiro da Silva Inference Web is joint work with Richard Fikes, Alyssa Glass, Honglei Zeng, Mayukh Bhaowal, Bill Millar, Dhyanesh Narayan, Priyendra Deshwal, … TAMI/Portia Privacy and Accountability Workshop 28-29 June 2006, Cambridge, MA USA

2. Deborah McGuinness, June 2006 General Motivation Interoperability – as more systems are use varied sources and multiple information manipulation engines, they benefit more from encodings that are shareable and interoperable Provenance - if users (humans and agents) are to use and integrate data from unknown, unreliable, or multiple sources, they need provenance metadata for evaluation Explanation/Justification – if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust –if some sources are more trustworthy than others, representations should be available to encode, propagate, combine, and (appropriately) display trust values Provide interoperable knowledge provenance infrastructure that supports explanations of sources, assumptions, learned information, and answers as an enabler for trust.

3. Deborah McGuinness, June 2006 TAMI Background Overall TAMI Ambition: Explore privacy implications of semantic web technologies and determine viability. Goal: Assess applicability of a usage limitation model (as opposed to or in addition to a data collection model) to data mining/profiling applications. Explore technical challenges of provable accountability with explicit justifications in large scale, heterogeneous information systems (i.e., the Web). Develop public policy models to encourage transparent, accountable data mining

4. Deborah McGuinness, June 2006 Privacy and Explanation As more online data becomes available and as inference and interoperability increases, privacy protection will have to rely more on usage limitation rules and less on collection limitation rules Usage Limits depend upon: Transparency: knowledge provenance history of sources, data manipulations, and inferences is maintained in an interoperable form. Explanation technology used to allow examination of knowledge provenance by authorized parties (who may be the general public). Accountability: ability to check whether the policies that govern data manipulations and inferences were in fact adhered to. Explanation technology used to examine inference usage.

5. Deborah McGuinness, June 2006 WWW Toolkit Proof Markup Language (PML) CWM (TAMI) JTP (DAML/NIMD) SPARK (CALO) UIMA (NIMD/Exp Agg) IW Explainer/ Abstractor IWBase IWBrowser IWSearch Trust Justification Provenance N3 KIF SPARK-L Text Analytics IWTrust provenance registration search engine based publishing Expert friendly Visualization End-user friendly visualization Trust computation SDS (DAML/SNRC) OWL-S/BPEL [Inference Web] Framework for explaining question answering tasks by abstracting, storing, exchanging, combining, annotating, filtering, segmenting, comparing, and rendering proofs and proof fragments provided by question answerers. Inference Web Infrastructure

6. Deborah McGuinness, June 2006 PML Ontology

7. Deborah McGuinness, June 2006 How PML Works Justification Trace IWBase NodeSet foo:ns1 (hasConclusion …) Query foo:query1 (type arrest1 ?x) Question foo:question1 (how is arrest1 classified?) Mapping NodeSet foo:ns2 (hasConclusion …) SourceUsage hasAnswer hasAntecendent fromQuery fromAnswer … isQueryFor InferenceEngine InferenceRule hasVariableMapping hasInferencEngine hasRule InferenceStep Language hasLanguage InferenceStep Source isConsequentOf hasSourceUsage hasSource isConsequentOf usageTime …

8. Deborah McGuinness, June 2006 TAMI Architecture Data Sources Inference Engine(s) & Truth Maintenance System Justification Generator (why action does/doesn’t comply with policy) Proof Generation Services (Inference Web) Assertions with provenance Usage Rules (Laws/Policy) Action

9. Privacy Act background

10. Deborah McGuinness, June 2006 Privacy Act

11. Deborah McGuinness, June 2006 Sharing Restrictions (b) Conditions of Disclosure.— –No agency shall disclose any record which is contained in a system of records –by any means of communication to any person or agency … –except... with the prior written consent of, the individual to whom the record pertains, –unless disclosure of the record would be— …. (3) for a routine use [5 USC § 552a(b)(3)]

12. Deborah McGuinness, June 2006 Routine Use as defined in subsection (a)(7) –“the use of such record for a purpose which is compatible with the purpose for which it was collected;” [5 USC § 552a(a)(7)] described under subsection (e)(4)(D) –“publish in the Federal Register upon establishment or revision a notice of the existence and character of the system of records, which notice shall include—” [5 USC § 552a(e)(4)] –“each routine use of the records contained in the system, including the categories of users and the purpose of such use” [5 USC § 552a(e)(4)(d)]

13. Deborah McGuinness, June 2006 a ROUTINE USE a SHARING_PERMISSION Recipient : [1,∞] Organization HasDataCategory :DataCategory HasPurpose :AuthorizedPurpose … General Categories Structured Components One Simple Description

14. Deborah McGuinness, June 2006 Sample Code RU1 a RoutineUse ; recipient FBI ; category DataCategory3 ; purpose CounterTerrorism ; dc:description "May share where TSA becomes aware of information that may be related to an individual identified in the TSDB.“ DataCategory3 a DataCategory ; dc:description "Information about people who are known or reasonably suspected to be or have been engaged in conduct constituting, in preparation for, in aid of, or related to terrorism.". Can share with FBI Data about possible terrorists So they can investigate whether a criminal law has been violated

15. Deborah McGuinness, June 2006 Explanation Why was data sharing xyz acceptable? –Using RoutineUse459 We shared with the FBI Data belonging to DataCategory3 For the purpose of CounterterrorismCriminalLawEnforcement Provenance: RoutineUse459 is derived from –SORN (statement of records notice) for “Secure Flight” –Published at 70 FR 36319 –Encoded by DHS Office of the Privacy Officer

16. Deborah McGuinness, June 2006 Explanation Why was data sharing xyz unacceptable? –We checked all of the RoutineUses We shared with the IRS Data belonging to DataCategory3 –IRS is not authorized to receive DataCategory3 For the purpose of CounterterrorismCriminalLawEnforcement Provenance: all RoutineUses are derived from –SORN for “Secure Flight” –Published at 70 FR 3620 –Encoded by DHS Office of the Privacy Officer

17. Scenario 3 Examples (nerd level)

18. Deborah McGuinness, June 2006 IWBrowser - Browse & Debug

19. Deborah McGuinness, June 2006 IWBrowser - Provenance

20. Deborah McGuinness, June 2006 IWBrowser - Explanation

21. Deborah McGuinness, June 2006 A fragment of PML data 1. 2. @prefix : <http://dig.csail.mit.edu/TAMI/lkagal/scenario3/rules#>. 3. @prefix data: <http://dig.csail.mit.edu/TAMI/cph/v2/data.ttl#>. 4. data:arrest-1 a :NotJustifiedArrest; :charge <http://dig.csail.mit.edu/TAMI/law/USC-18-228>. 5. 6. data:arrest-1 [is-a] :NotJustifiedArrest;[and has] :charge <http://dig.csail.mit.edu/TAMI/law/USC-18-228>. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. http://dig.csail.mit.edu/TAMI/lkagal/scenario3/rules#A 21. http://dig.csail.mit.edu/TAMI/cph/v2/data.ttl#arrest-1 22. 23. 24. 25. http://dig.csail.mit.edu/TAMI/lkagal/scenario3/rules#P 26. http://dig.csail.mit.edu/TAMI/background#ct-criminal-law-enforcement 27. 28. 29. 30. http://dig.csail.mit.edu/TAMI/lkagal/scenario3/rules#C 31. http://dig.csail.mit.edu/TAMI/law/USC-18-228 32. 33.

22. Deborah McGuinness, June 2006 Next Generation Browser

23. Deborah McGuinness, June 2006 Discussion Exploring an explainable usage limitation model supported by semantic technologies Status: –Use case written up and (very recently) encoded –Early prototype in place – JUST integrated with CWM with use case 3 … refinement in process –Exploiting domain independent explanation tools –Exploring options that leverage knowledge of N3 and CWM supporting more useful tools/APIs/interfaces –Exploring options that leverage knowledge of law supporting context-sensitive and appropriate presentations

24. Deborah McGuinness, June 2006 Summary Leverage points include: –PML: justification, provenance, and trust interlingua –IW tools for interactive browsing, summarizing, searching, validation, abstraction, trust representation, propagation, presentation… (domain independent) –Experience explaining a wide variety of reasoners (JTP, SNARK, …), task processing engines (SPARK), learners (TAILOR), text analytics (UIMA), web services (SDS/BPEL), … Continuing work –Identify explanation (representation and presentation) requirements –Refining registration and presentation –Designing special purpose filters and abstractions Impact –Interoperable justifications supporting transparency and accountability –Has the potential to change publishing law (with markup) as well as presenting judgments (with interactive justifications) –Audit trace

25. Deborah McGuinness, June 2006 More Information Links –http://iw.stanford.edu/: Inference Web home –http://iw.stanford.edu/doc/project/tami/: TAMI@Stanford –http://dig.csail.mit.edu/TAMI: TAMI home Papers –(Inference Web) Deborah L. McGuinness and Paulo Pinheiro da Silva. Explaining Answers from the Semantic Web: The Inference Web Approach. Journal of Web Semantics. Vol.1 No.4., pages 397-413, 2004(Inference Web) –(PML) Paulo Pinheiro da Silva, Deborah L. McGuinness and Richard Fikes. A Proof Markup Language for Semantic Web Services. Information Systems. Volume 31, Issues 4-5, pages 381-395, 2006(PML) –(TAMI) Daniel J. Weitzner, Hal Abelson, Tim Berners-Lee, Chris P. Hanson, Jim Hendler, Lalana Kagal, Deborah L. McGuinness, Gerald J. Sussman, K. Krasnow Waterman. Transparent Accountable Inferencing for Privacy Risk Management. Proceedings of AAAI Spring Symposium on The Semantic Web meets eGovernment. AAAI Press, Stanford University, USA 2006. Also available as MIT CSAIL Technical Report-2006-007 and Stanford KSL Technical Report KSL-06-03.TAMI The Semantic Web meets eGovernment

26. Deborah McGuinness, June 2006 Extras

27. Deborah McGuinness, June 2006 IWBrowser - Browse & Debug

28. Deborah McGuinness, June 2006 IWBrowser - Provenance

29. Deborah McGuinness, June 2006 IWBrowser - Explanation

30. Deborah McGuinness, June 2006 A fragment of PML data 1. 2. @prefix : <http://dig.csail.mit.edu/TAMI/cdk/scenario3/data.n3#>. 3. @prefix tr: <http://dig.csail.mit.edu/TAMI/cdk/scenario3/rules.n3#>. 4. :Arrest05NY2343CRJFC a tr:JustifiedArrest. 5. :Arrest05NY2343CRJFC [is-a] tr:JustifiedArrest. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. http://people.csail.mit.edu/lkagal/tami/tami-scenario3-filter.n3#A 20. http://dig.csail.mit.edu/TAMI/cdk/scenario3/data.n3#Arrest05NY2343CRJFC 21. 22. 23. 24. http://people.csail.mit.edu/lkagal/tami/tami-scenario3-filter.n3#B 25. http://dig.csail.mit.edu/TAMI/cdk/scenario3/data.n3#open-source-search-2-result-1 26. 27.

31. Deborah McGuinness, June 2006 Next Generation Browser

32. PML based Explanation: Adding trust-tab to Wikipedia

33. Deborah McGuinness, June 2006 The Original Wikipedia Article

34. Deborah McGuinness, June 2006 Trust Tab Multiple Trust Tab citation based revision history based Fragments colored according trust value Explanation about a fragment (author, trust value)

35. Deborah McGuinness, June 2006 fragment PML Tab http://inferenceweb.stanford.edu/2006/02/example1-iw-wiki.owl fragment trust author trust 0.1766 0.1766

36. PML based Explanation: Explaining Cognitive Assistants – DARPA PAL Program’s CALO system

37. Deborah McGuinness, June 2006 Explanation Process Initial request and answer strategy : Why are you doing ? : I am trying to do and is one subgoal in the process. Follow-up questions for mixed initiative dialogue : Why are you doing ? : How did you learn to do in this way? : Why haven’t you completed yet? : Why is a subgoal of ? : When will you finish ? : What sources did you use to do ? McGuinness, D.L.; Pinheiro da Silva, P.; Glass, A.; Wolverton, M. Explaining Task Processing in Cognitive Assistants. 2006. Technical Report, KSL-06-06, Knowledge Systems Lab., Stanford.

38. Deborah McGuinness, June 2006 CALO TM Explainer UI Initial explanation, with links indicating follow-up queries and alternate strategies.