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Moral Coppélia: Affective moral reasoning with twofold autonomy and a touch of personality Matthijs Pontier [email protected]

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We present a moral reasoner, Moral Coppélia, which combines connectionism, utilitarianism, and ethical theory about the moral duties autonomy, non-maleficence, beneficence, and justice with affective states and personality traits. We, moreover, treat human autonomy in the sense of self-determination as well as making a meaningful choice. Our system combines bottom-up with top-down approaches, calculating the effect of an act on the total moral utility in the world. Moral Coppélia can reproduce the verdicts of medical ethicists and health judges in real-life cases and can handle the emotional differences between logically identical problems such as the Trolley and Footbridge dilemma. It also deals with properties of character and personality such as honesty and humility to explain why logic reasoning is not always descriptive of actual human moral behavior. Apart from simulating known cases, we performed a split-half experiment with the responses of 153 participants in a criminal justice experiment. While fine-tuning the parameters to the first half of the data, the encompassing version of Moral Coppélia was capable of forecasting criminal decisions, leading to a better fit with the second half of the data than either of the loose component parts did. In other words, we found empirical support for the integral contribution of ratio, affect, and personality to moral decision making, which, additionally, could be acceptably simulated by our extended version of the Moral Coppélia system.

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Page 1: Moral Coppélia: Affective moral reasoning with twofold autonomy and a touch of personality - Presentation at MEMCA14 Symposium at AISB50

Moral Coppélia: Affective moral reasoning with twofold autonomy and a touch of personality

Matthijs Pontier

[email protected]

Page 2: Moral Coppélia: Affective moral reasoning with twofold autonomy and a touch of personality - Presentation at MEMCA14 Symposium at AISB50

Overview of this presentation

• SELEMCA• Moral Reasoning• Silicon Coppelia: Model of Emotional Intelligence• Moral Reasoning + Silicon Coppelia = Moral Coppelia• Predicting Crime with Moral Coppelia• Conclusion• Future Work

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SELEMCA• Develop ‘Caredroids’: Robots or Computer Agents

that assist Patients and Care-deliverers• Focus on patients who stay in long-term care facilities

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Possible functionalities

• Care-broker: Find care that matches need patient

• Companion: Become friends with the patient to prevent loneliness and activate the patient

• Coach: Assist the patient in making healthy choices: Exercising, Eating healthy, Taking medicine, etc.

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Applications: Care Agents

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Applications: Care Robots

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Background Machine Ethics

• Machines are becoming more autonomous

Rosalind Picard (1997): ‘‘The greater the freedom of a machine, the more it will need moral standards.’’

• Machines interact more with peopleWe should manage that machines do not harm us or

threaten our autonomy

• Machine ethics is important to establish perceived trust in users

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Domain: Medical Ethics

• Within SELEMCA, we develop caredroids• Patients are in a vulnerable position.

Moral behavior of robot is extremely important.We focus on Medical Ethics

• Conflicts between:

1. Beneficence

2. Non-maleficence

3. Autonomy

4. Justice

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Moral reasoning system

We developed a rational moral reasoning system that is capable of balancing between conflicting moral goals.

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Positive vs Negative Autonomy

• Negative Autonomy = Self-determination• Freedom of others

• Autonomy is more than self-determination• Being able to make a meaningful choice• Act in line with well-considered preferences

• Positive Autonomy =

Freedom to make a meaningful choice

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Typical moral dilemmas Caredroids will encounter• Positive vs Negative Autonomy:

• Accept unhealthy choice vs Persuade reconsider• Binding to previous agreement vs Giving up

Expand moral principle of Autonomy

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Model autonomy

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New Moral Reasoning System

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Results

London, 03-04-2014 MEMCA-14 Symposium at AISB50

• New moral reasoning system matches decisions previous moral reasoning system

• Simulation of 2008-2012 NL law cases:• Case 1: Assertive outreach to prevent judicial coercion

• Patient in demise. Aggression Assertive Outreach• Case 2: Inform care deliverers, not parents of adult

• Patient in alarming situation. No good contact with parents.• Case 3: Neg. autonomy constrained to enhance pos. autonomy

• Self-binding declaration addict due to relapses in alcohol use

• Conditions were met Judicial Coercion

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Conclusions Autonomy Model

• We created moral reasoning system including twofold approach of autonomy

• System matches decisions medical ethical experts• System matches decisions law cases

• By using theories of (medical) ethics, we can build robots that stimulate autonomy

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Limitations rational moral reasoning

• Only moral reasoning results in very cold decision-making, only in terms of rights and duties

• Wallack, Franklin & Allen (2010): “Ethical agents require emotional intelligence as well as other ‘supra-rational’ faculties, such as a sense of self and a ‘Theory of Mind”

• Tronto (1993): “Care is only thought of as good care when it is personalized”

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Problem: Not Able to SimulateTrolley Dilemma vs Footbridge Dilemma

• Greene et al. (2001) find that moral dilemmas vary systematically in the extent to which they engage emotional processing and that these variations in emotional engagement influence moral judgment.

• Their study was inspired by the difference between two variants of an ethical dilemma:

Trolley dilemma (moral impersonal)

Footbridge dilemma (moral personal)

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Solution: Add Emotional Processing

• Previously, we developed Silicon Coppelia,

a model of emotional intelligence. • This can be projected in others for Theory of Mind• Learns from experience Personalization

Connect Moral Reasoning to Silicon Coppelia• More human-like moral reasoning• Personalize moral decisions and communication

about moral reasoning

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Silicon Coppelia

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Silicon Coppelia

• We developed Silicon Coppelia, with the goal to create emotionally human-like robots

• Simulation experiments:

System behaves consistent with Theory and Intuition

• Compare performance model with

performance real human in speeddating experiment

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Turing Test

• Turing Test was originally text-based• We enriched test with affect-laden communication

• Facial expressions showing emotions• Capable of vocal speech

• Afterwards questionnaire:

How do you think Tom perceived you?

Measure made continuous and more elaborated than simply yes/no

• Analysis: Bayesian structural equation modeling

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Speed-dating Experiment

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Results

• Participants did not detect differences on single variables

• Participants did not recognize significant differences on cognitive-affective structure

• Model in which conditions (1: human, 2: robot) were assumed equal explained data better than model in which conditions were assumed different

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Conclusions Speed-Date

• We created simulation of affect so natural that young women could not discern dating a robot from a man

• Important for:• Understanding human affective communication• Developing communication technologies • Developing emotionally human-like robots

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Silicon Coppelia + Moral Reasoning:

Decisions based on:

1. Rational influences• Does action help me to reach my goals?

2. Affective influences• Does action lead to desired emotions?• Does action reflect Involvement I feel towards user?• Does action reflect Distance I feel towards user?

3. Moral reasoning• Is this action morally good?

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Results Trolley & Footbridge

Kill 1 to Save 5 Do Nothing

Moral system

Trolley X

Footbridge X

Moral Coppelia

Trolley X

Footbridge X

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Background Criminology Study• Substantial evidence emotions are fundamental in

criminal decision making• But emotions rarely in criminal choice models

Study relation Ratio+Emotions+Moral

Apply Moral Coppelia to criminology data

Predict criminal decisions participants

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Matching data to model

Match:

• Honesty/Humility to Weightmorality

• Perceived Risk to Expected Utility• Negative State Affect to EESA

Parameter Tuning:

1. Find optimal fits for initial sample

2. Predict decisions for holdout sample

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Predicting Criminal Choices

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Ratio Emo R+E Moral M+R M+E M+R+E

morcc 0 0 0 0.68 0.42 0.453 0.435

wmor 0 0 0 1.00 0.96 0.97 0.87

partrat 1 0 0.34 0 1 0 0.64

partemo 0 1 0.66 0 0 1 0.36

R2 initial

0.7553 0.8792 0.9222 0.9336 0.9871 0.9798 0.9881

R2 holdout

0.7192 0.9060 0.9323 0.9281 0.9803 0.9778 0.9821

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Conclusions

• We created an affective moral reasoning system • System matches decisions medical ethical experts• System matches decisions law cases• By using theories of (medical) ethics,

we can build robots that stimulate autonomy• System can simulate trolley and footbridge dilemma• System can predict human criminal choices

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Discussion

• The introduction of affect in rational ethics is important when robots communicate with humans

• Combination Ratio + Affect + Morals useful for applications that simulate human decision making

for example, when agent systems or robots provide healthcare support, or in entertainment settings

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Future Work: Apply in politics

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• Personal freedom• Privacy• Human rights• Transparency• Citizen participation• Evidence-based policy• Science & Education• Freedom of information• Open access / Open data / Open source

• Elections European Parliament: 22.05.2014

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Thank you!

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Matthijs Pontier

[email protected]

http://camera-vu.nl/matthijs

http://www.linkedin.com/in/matthijspontier• @Matthijs85

http://www.piratenpartij.nl/ • @Piratenpartij

London, 03-04-2014MEMCA-14 Symposium at AISB50