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Chris Hazard - Measuring and Manipulating Player Biases and Trust Through Choice and Game Mechanics

Chris Hazard, CEO/Founder, Hazardous Software This presentation was given at the 2016 Serious Play Conference, hosted by the UNC Kenan-Flagler Business School. Information theory offers a mathematical measure of expected surprisal and a measure of ambiguity. When coupled with decision science, psychology, and a little game theory, human biases and trust can be formalized, measured and, ultimately, manipulated. This talk will provide an overview of how such techniques can be employed in the mechanics of serious games to create more believable experiences, more challenging and effective AI, and to help players understand their own biases and weaknesses in their own disciplines. Audiences will become familiar with types of biases, limitations of human abilities to asses risk probability, and how nuanced real-world interactions can be recreated in serious game environments. This is useful for those interested in employing serious games for training and evaluation, as well as for practitioners to implement in their own games.

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Chris Hazard - Measuring and Manipulating Player Biases and Trust Through Choice and Game Mechanics

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  1. Measuring and Manipulating Player Trust through Choice and Game Mechanics Christopher J. Hazard, PhD CEO Hazardous Software Inc.

  2. ●having reason or understanding ●relating to, based on, or agreeable to reason: reasonable

  3. Rational ●having reason or understanding ●relating to, based on, or agreeable to reason: reasonable -Merriam Webster

  4. Humans are rational* *given limited computational bounds, unfounded beliefs of others, inaccurate capability assessments, inexplicable valuations, and some level of [im]patience

  5. Machines are rational* *given limited computational bounds, unfounded beliefs of world, wrong models, inexplicable valuations, and some level of implicit [im]patience

  6. from zap2it.com from Seattle Weekly from trutv.com by tinyfroglet, cc from supermanhomepage.com from penny-arcade.com

  7. Reputation ● Belief about attribute ● Hindsight, capabilities, statistics ● Concern: adverse selection Trust ● Belief will not exploit ● Foresight, strategy, game theory ● Concern: moral hazard

  8. +

  9. Trustworthiness ~ Patience

  10. Trustworthiness Isomorphic to Discount Factor ● Compare two agents interacting with third in pure moral hazard situation ● Assumptions – Consistent valuations – Quasilinearity – Trustworthiness sufficiently consistent – Individually rational ● All else equal, given definitions & assumptions, only factor that affects trustworthiness is discount factor

  11. Discounting Everywhere Stochastic search Amortization Bellman Equation Reinforcement Learning Markov Decision Processes & POMDPs      Normalize discount rate wrt time 

  12. Creeping Sniper's Dilemma ● Single sniper optimal strategy; slow creep out = low risk ● Multiple sniper optimal strategy ● Match quickest visible discount strategy unless too risky

  13. Negotiating Rubenstein Negotiation v1 = (1-γ2)/(1-γ1γ2) Inequalities if rationality not guaranteed Player & NPC interaction inequalities Impatience NPC disagreements with player over choices      

  14. Measuring discount factor by choice

  15. Combining Observations: Bayesian Inference

  16. Optimal Level of Patience for Given Scenario

  17. Trust Exploration ● Measure valuations, discount factor, beliefs, maxent regions ● NPCs of different trustworthiness ● Reputations Trust Exploitation ● Push player's ethics buttons: “what is your price?” ● Stability & comfort vs conflict ● Trickery

  18. Psychological Heuristics of Trust Homophily Image from WoW Cataclysm Embedding Mass Effect 3 Corroboration Image from Heavenly Sword

  19. Homophily Embedding Corroboration

  20. Acceptance and Affirmation Antitheses (Alliterated) - Algorithm aversion Dietvorst et al., J Exp Psych 2013 + Anthropomorphization - Abeyance of absorbtion + Acceptance acquiered after asking assistance Flynn, Org Behav & Hum Dec Proc, 2003

  21. Selling Trust With Nuance 1: Don't [unintentionally] Scare Players Nevermind (forthcoming) – Monitor fright Balloon Brigade IQ, Depression, Behavior, Health, Preferences, Diet, Injuries, Friends, etc. -Newman, Jerome, & Hazard, AIPLA, 2014 Psychometrics for Predicting Behavior – Poore et al., J Cognitive Engineering, 2014. NBA 2K14 - Swearing

  22. Selling Trust With Nuance 2: Physiology ●More permissive on right ear than left - Marzoli & Tommasi, Sci of Nat, 2009 ●Two-streams hypothesis for vision processing ●Foveal & spatial detail vs perifoveal & temporal detail ●Mutual exclusion between physical & social reasoning – Jack et al., Neuroimage, 2012 ●Push players to practice self-control – Denson, DeWall, Finkel, Cur Dir in Psych Sci., 2012

  23. Selling Trust With Nuance 3: Hypnosis & Trance ●Relaxation ●Memory ●Creativity ●Suggestability ●Awe & comfort ●Biases ●Placebo effect

  24. Trust & Society ● Enforcing/sanctioning to combat lies ● Incentive compatibility & revelation principle wrt information asymmetry ● Level of trust req'd for system & efficiency ● Too trusting with homophily, embedding, corroboration? ● Common inability to play “red player”

  25. Direct Applications (Conclusions) NPC decisions: favors, purchases, alliances Measuring player patience Adversary willingness to look ahead related to organizational trust (e.g., big bad) NPC subordinates following player commands based on trustworthiness (explicit or implicit)    

  26. Questions? info@hazardoussoftware.com

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