The Rise of Emotion-aware Conversational Agents: Threats in Digital Emotions

A future where the conversation with machines can potentially involve mutual emotions between the parties may be not so far in time. Inspired by the episode of Black Mirror "Be Right Back'' and Replika, a futuristic app that promises to be "your best friend'', in this work we are considering the positive and negative points of including an automated learning conversational agent inside the personal world of feelings and emotions. These systems can impact both single individuals and society, worsening an already critical situation. Our conclusion is that a regulation on the artificial emotional content should be considered before actually going beyond some one-way-only limits.

[1]  Sara H. Konrath,et al.  Changes in Dispositional Empathy in American College Students Over Time: A Meta-Analysis , 2011, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[2]  Xiaoyan Zhu,et al.  Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory , 2017, AAAI.

[3]  J. Moor,et al.  Four Kinds of Ethical Robots , 2009 .

[4]  Joelle Pineau,et al.  Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models , 2015, AAAI.

[5]  Vidyasagar Potdar,et al.  Computational approaches for emotion detection in text , 2010, 4th IEEE International Conference on Digital Ecosystems and Technologies.

[6]  Fakhri Karray,et al.  Survey on speech emotion recognition: Features, classification schemes, and databases , 2011, Pattern Recognit..

[7]  土居 健郎,et al.  The Anatomy of Dependence , 1971 .

[8]  Heiga Zen,et al.  WaveNet: A Generative Model for Raw Audio , 2016, SSW.

[9]  Eli Pariser FILTER BUBBLE: Wie wir im Internet entmündigt werden , 2012 .

[10]  L. R. Goldberg The structure of phenotypic personality traits. , 1993, The American psychologist.

[11]  Eli Pariser,et al.  The Filter Bubble: What the Internet Is Hiding from You , 2011 .

[12]  Quoc V. Le,et al.  A Neural Conversational Model , 2015, ArXiv.

[13]  Roger Clarke,et al.  Asimov's Laws of Robotics: Implications for Information Technology - Part 2 , 1993, Computer.

[14]  Marc Schröder,et al.  A comparison of voice conversion methods for transforming voice quality in emotional speech synthesis , 2008, INTERSPEECH.

[15]  Aleix M. Martínez,et al.  A Model of the Perception of Facial Expressions of Emotion by Humans: Research Overview and Perspectives , 2012, J. Mach. Learn. Res..

[16]  Michael Zielenziger,et al.  Shutting Out the Sun: How Japan Created Its Own Lost Generation , 2006 .

[17]  Christine L. Lisetti Affective computing , 1998, Pattern Analysis and Applications.

[18]  Jianfeng Gao,et al.  A Persona-Based Neural Conversation Model , 2016, ACL.

[19]  Wei-Ying Ma,et al.  Topic Aware Neural Response Generation , 2016, AAAI.

[20]  R. Blake,et al.  Perception of human motion. , 2007, Annual review of psychology.

[21]  Navneet Kaur,et al.  Opinion mining and sentiment analysis , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[22]  P. Ekman Facial expression and emotion. , 1993, The American psychologist.

[23]  Jeffrey P. Harman,et al.  Liar, Liar: Internet Faking but Not Frequency of Use Affects Social Skills, Self-Esteem, Social Anxiety, and Aggression , 2005, Cyberpsychology Behav. Soc. Netw..

[24]  Andy Furlong,et al.  The Japanese Hikikomori Phenomenon: Acute Social Withdrawal among Young People , 2008 .

[25]  Louis-Philippe Morency,et al.  It's only a computer: Virtual humans increase willingness to disclose , 2014, Comput. Hum. Behav..

[26]  Bill Hibbard,et al.  Ethical Artificial Intelligence , 2014, Mar/Apr 2020.

[27]  Jakob Grue Simonsen,et al.  A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion , 2015, CIKM.