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Toward machines that behave ethically better than humans do
 Matthijs           Pontier 1, 2
                1                                                          Moral Goals      Belief strengths   Actions   Output
 Johan F, Hoorn




                                                         Moral reasoner
 1 VU                                                                                                             F
        University, Amsterdam                                                Autonomy
 2 http://camera-vu.nl/matthijs/
                                                                                                               Action1
   matthijspon@gmail.com

                                                                            Beneficence


                                                                                                               Action2
Abstract
Increasing dependence on autonomous                                       Non-maleficence
operating systems calls for ethical machine
behavior. Our moral reasoner combines
connectionism, utilitarianism, and ethical
theory about moral duties. The moral
decision-making matches the analysis of
expert ethicists in the health domain. This is
particularly useful when machines interact
with humans in a medical context. Connected
to a model of emotional intelligence and
affective decision making, we can explore
how moral decision making impacts affective
behavior and vice versa.



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

Wallach, Franklin, and Allen (2010) argue
that agents that adhere to a deontological
ethic or that are utilitarians also require
emotional intelligence, a sense of self, and a
theory of mind.

We connected the moral system to Silicon
Coppélia (Hoorn, Pontier, & Siddiqui, 2011), a
model of emotional intelligence and affective
decision making. Silicon Coppélia contains a
feedback loop that learns the preferences of
an individual patient so to personalize its
behavior.



Results
                                                 Discussion
                                                 Sample Exp. 5: A patient with incurable cancer refuses chemotherapy to
                                                 live a few months longer, almost without pain, because he is convinced
                                                 of being cancer-free. According to Buchanan and Brock (1989), the
                                                 ethically preferable answer is to “try again.” The patient seems less than
                                                 fully autonomous and his decision leads to harm, denying the chance to
                                                 a longer life (a violation of the duty of beneficence). This he might regret
                                                 later. Our moral reasoner comes to the same conclusion as the ethical
                                                 experts. However, even among doctors, there is no consensus about the
                                                 interpretation of values, their ranking and meaning. Van Wynsberghe
                                                 (2012) found this depends on: the type of care (i.e., social vs. physical
                                                 care), the task (e.g., bathing vs. lifting vs. socializing), the care-givers
                                                 and their style, as well as the care-receivers and their specific needs.

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Toward machines that behave ethically better than humans do - Poster

  • 1. Toward machines that behave ethically better than humans do Matthijs Pontier 1, 2 1 Moral Goals Belief strengths Actions Output Johan F, Hoorn Moral reasoner 1 VU F University, Amsterdam Autonomy 2 http://camera-vu.nl/matthijs/ Action1 matthijspon@gmail.com Beneficence Action2 Abstract Increasing dependence on autonomous Non-maleficence operating systems calls for ethical machine behavior. Our moral reasoner combines connectionism, utilitarianism, and ethical theory about moral duties. The moral decision-making matches the analysis of expert ethicists in the health domain. This is particularly useful when machines interact with humans in a medical context. Connected to a model of emotional intelligence and affective decision making, we can explore how moral decision making impacts affective behavior and vice versa. Background Rosalind Picard (1997): ‘‘The greater the freedom of a machine, the more it will need moral standards.’’ Wallach, Franklin, and Allen (2010) argue that agents that adhere to a deontological ethic or that are utilitarians also require emotional intelligence, a sense of self, and a theory of mind. We connected the moral system to Silicon Coppélia (Hoorn, Pontier, & Siddiqui, 2011), a model of emotional intelligence and affective decision making. Silicon Coppélia contains a feedback loop that learns the preferences of an individual patient so to personalize its behavior. Results Discussion Sample Exp. 5: A patient with incurable cancer refuses chemotherapy to live a few months longer, almost without pain, because he is convinced of being cancer-free. According to Buchanan and Brock (1989), the ethically preferable answer is to “try again.” The patient seems less than fully autonomous and his decision leads to harm, denying the chance to a longer life (a violation of the duty of beneficence). This he might regret later. Our moral reasoner comes to the same conclusion as the ethical experts. However, even among doctors, there is no consensus about the interpretation of values, their ranking and meaning. Van Wynsberghe (2012) found this depends on: the type of care (i.e., social vs. physical care), the task (e.g., bathing vs. lifting vs. socializing), the care-givers and their style, as well as the care-receivers and their specific needs.