1. Adaptive Support using Cognitive Models of Trust Robbert-Jan Beun (UU), Jurriaan van Diggelen (TNO), Mark Hoogendoorn (VU), Syed Waqar Jaffry (VU), Peter-Paul van Maanen (TNO), Francien Wisse (UU)

2. AI Seminar October 2010 Overview of talk Introduction and motivation Adaptive support based on cognitive models of trust General methodology Part I: Validation and verification of trust models Independent vs. relative trust model Method Results Conclusions Part II: Evaluation of adaptive support based on trust models Reliance support by advising vs. adaptive autonomy Method Results Conclusions General discussion

3. AI Seminar October 2010 Introduction and motivation Trends in military / homeland security / incident management / … : More complex situations More different situations More information Reduced manning / less human assistance Less experience Less specific training possible Increased computer intelligence … Challenge: Human error in the appropriate reliance on information from humans and computers is evident Possible solution: Let support systems take into account human limitations in reliance decision making: Trust-aware adaptive systems

4. AI Seminar October 2010 Adaptive support based on cognitive models of trust How can one do that? Design a support system that: Supports human-computer teams Estimates current trust (cogn. mod.) Estimates optimal trust (cogn. mod.) When sub-optimal, intervenes: By providing advise (other) By adapting autonomy (self)

5. AI Seminar October 2010 General methodology Part I: Validation and verification of trust models Part II: Evaluation of adaptive support based on trust models

6. AI Seminar October 2010 Part I: Validation and verification of trust models

7. AI Seminar October 2010 Independent vs. relative trust model Independent trust model (Van Maanen, Klos, Van Dongen, 2007) : Trust in agent A independent of trust in agents other than A Relative trust model (Hoogendoorn, Jaffry, Treur, 2008) :

8. AI Seminar October 2010 Method Optimization and validation of 2 models done by: Implementation of human-computer team task Gathering input data for models (performance data) Gathering validation data (actual reliance data) Generate model output (estimated reliance data) Use actual and estimated reliance data to cross-validate models: train models (half the data) and test (other half) Input: performance data Output: estimated reliance data Output: actual reliance data

9. AI Seminar October 2010 Method Simulated through a server

10. AI Seminar October 2010 Method

11. AI Seminar October 2010

12. Method Training of models by parameter estimation (exhaustive search):

13. AI Seminar October 2010 Results Significant: relative trust model has higher accuracy than independent trust model

14. AI Seminar October 2010 Conclusions Trust models were optimized and an attempt was made to see what model structure is best for the specific task The relative trust model improves reliance decision estimation over the independent trust model Future research could focus on: improved models and model verification and validation techniques and for other domains/tasks

15. AI Seminar October 2010 Part II: Evaluation of adaptive support based on trust models

16. AI Seminar October 2010 Reliance support by advising vs. adaptive autonomy Two types of interventions: Advising by visualization of discrepancies between agents Adaptive autonomy by taking over reliance decisions

17. AI Seminar October 2010 Method Evaluation of 2 adaptive support types done by: Usage of same task as previously explained Calculate appropriateness (alpha) of trust in self, system and other: t^d(t) = estimated trust, t^p(t) = desired trust Per agent, when above or below a certain (-)threshold, advise: In total, when above or below a certain (-)threshold, adapt autonomy: Calculate performances: For no support (NS), advising (GS), adaptive autonomy (AA)

18. AI Seminar October 2010 Results Not significant

19. AI Seminar October 2010 Results Significant: Support effectiveness decreases relative to human competence

20. AI Seminar October 2010 Results Significant: Support effectiveness decreases relative to human competence

21. AI Seminar October 2010 Results Not significant: Support effectiveness does not in-/decrease relative to human competence

22. AI Seminar October 2010 Results Not significant: Higher task difficulty did not lead to higher support effectiveness

23. AI Seminar October 2010 Results Finally: GS was more satisfactory than AA (significant)

24. AI Seminar October 2010 Conclusions Proof of concept: It is indeed possible to implement adaptive support using cognitive optimized and validated models of trust Results show no significant effect of the support types for the current task Future work: Effect of validity on the effectiveness of support Effect of intrusiveness of support Improvements of satisfaction and acceptance of support Improvement of reliance decisions of system (in case of adaptive autonomy) Other domains, tasks, support types

25. AI Seminar October 2010 General discussion Questions that can be raised: Can the proposed methodology be used for the development of adaptive support using cognitive models? Are there other cognitive models that can be used? How would machines that take over tasks or manipulate the human mind be perceived by humans? Are they accepted? What would future human-aware machines be like? Would they augment the human mind, cooperating with humans, or would they be better of without humans?