Human-centred artificial intelligence: a contextual morality perspective

References

• Abdul, Ashraf, Jo Vermeulen, Danding Wang, Brian Y. Lim, and Mohan Kankanhalli. 2018. “Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). 18. New York, NY, USA: ACM. Article 582. doi:https://doi.org/10.1145/3173574.3174156.
   Google Scholar
• Albarghouthi, Aws, and Samuel Vinitsky. 2019. “Fairness-Aware Programming.” In Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). 211–219. New York, NY, USA:ACM. doi:https://doi.org/10.1145/3287560.3287588.
   Google Scholar
• Appel, Markus, Timo Gnambs, Tobias Richter, and Melanie C. Green. 2015. “The Transportation Scale–Short Form (TS–SF).” Media Psychology 18 (2): 243–266. doi:https://doi.org/10.1080/15213269.2014.987400.
   Web of Science ®Google Scholar
• Aristotle. 2000. Aristotle: Nicomachean Ethics. Oxford: Cambridge University Press.
   Google Scholar
• Arnold, Matthew, Rachel K. E. Bellamy, Michael Hind, Stephanie Houde, Sameep Mehta, Aleksandra Mojsilovic, Ravi Nair, Karthikeyan Natesan Ramamurthy, Darrell Reimer, Alexandra Olteanu, David Piorkowski, Jason Tsay, and Kush R. Varshney. 2018. FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformity. CoRR abs/1808.0.
   Google Scholar
• Arnold, Kenneth C., Kai–Wei Chang, and Adam Tauman Kalai. 2017. Counterfactual Language Model Adaptation for Suggesting Phrases. CoRR abs/1710.01799.
   Google Scholar
• Awad, Edmond, Sohan Dsouza, Richard Kim, Jonathan Schulz, Joseph Henrich, Azim Shariff, Jean-François Bonnefon, and Iyad Rahwan. 2018. “The Moral Machine Experiment.” Nature 563 (7729): 59. doi:https://doi.org/10.1038/s41586-018-0637-6.
   PubMed Web of Science ®Google Scholar
• Barocas, Solon, and Andrew D Selbst. 2016. “Big Data's Disparate Impact.” California Law Review 104: 671.
   Web of Science ®Google Scholar
• Berinsky, Adam J., Gregory A. Huber, and Gabriel S. Lenz. 2012. “Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk.” Political Analysis 20 (3): 351–368. doi:https://doi.org/10.1093/pan/mpr057.
   Web of Science ®Google Scholar
• van Berkel, Niels, Simo Hosio, Benjamin Tag, and Jorge Goncalves. 2019. “Capturing Contextual Morality: Applying Game Theory on Smartphones.” In Adjunct Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing. doi:https://doi.org/10.1145/3341162.3344846.
   Google Scholar
• Black, Jessica E., and William M. Reynolds. 2016. “Development, Reliability, and Validity of the Moral Identity Questionnaire.” Personality and Individual Differences 97: 120–129. doi:https://doi.org/10.1016/j.paid.2016.03.041.
   Web of Science ®Google Scholar
• Bonnefon, Jean-François, Azim Shariff, and Iyad Rahwan. 2016. “The Social Dilemma of Autonomous Vehicles.” Science (New York, N.Y.) 352 (6293): 1573–1576. doi:https://doi.org/10.1126/science.aaf2654.
   PubMed Web of Science ®Google Scholar
• Brodhead, Matthew T., David J. Cox, and Shawn P. Quigley. 2018. “Chapter 1 – Introduction to ABA, Ethics, and Core Ethical Principles.” In Practical Ethics for Effective Treatment of Autism Spectrum Disorder, Matthew T. Brodhead, David J. Cox, and Shawn P. Quigley eds. 1–16. London: Academic Press. doi:https://doi.org/10.1016/B978-0-12-814098-7.00001-8.
   Google Scholar
• Cai, Carrie J., Emily Reif, Narayan Hegde, Jason Hipp, Been Kim, Daniel Smilkov, Martin Wattenberg, Fernanda Viegas, Greg S. Corrado, Martin C. Stumpe, and Michael Terry. 2019. “Human-Centered Tools for Coping with Imperfect Algorithms During Medical Decision-Making.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). 14. New York, NY, USA:ACM. Article 4. doi:https://doi.org/10.1145/3290605.3300234.
   Google Scholar
• Calders, Toon, and Sicco Verwer. Sept. 1, 2010. “Three Naive Bayes Approaches for Discrimination-free Classification.” Data Mining and Knowledge Discovery 21 (2): 277–292. doi:https://doi.org/10.1007/s10618-010-0190-x.
   Web of Science ®Google Scholar
• Caruana, Rich, Yin Lou, Johannes Gehrke, Paul Koch, Marc Sturm, and Noemie Elhadad. 2015. “Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission.” In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ‘15). 1721–1730. New York, NY, USA: ACM. doi:https://doi.org/10.1145/2783258.2788613.
   Google Scholar
• Chang, Ruth. 2015. “Transformative Choices.” Res Philosophica 92 (2): 237–282. doi:https://doi.org/10.11612/resphil.2015.92.2.14.
   Web of Science ®Google Scholar
• Chopra, Amit K, and Munindar P SIngh. 2018. “Sociotechnical Systems and Ethics in the Large.” In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society (AIES ’18). 48–53. New York, NY, USA: ACM. doi:https://doi.org/10.1145/3278721.3278740.
   Google Scholar
• Choudhury, Munmun De, and Emre Kiciman. 2018. “Integrating Artificial and Human Intelligence in Complex, Sensitive Problem Domains: Experiences From Mental Health.” AI Magazine 39 (3): 69–80. doi: https://doi.org/10.1609/aimag.v39i3.2815
   Web of Science ®Google Scholar
• Crawford, Kate. 2016. Artificial intelligence's white guy problem.
   Google Scholar
• Crawford, Kate, and Ryan Calo. 2016. “There is a Blind Spot in AI Research.” Nature News 538 (7625): 311. doi:https://doi.org/10.1038/538311a.
   PubMed Web of Science ®Google Scholar
• Croxall, Samuel. 1775. Fables of Æsop and Others. London: W. Strahan.
   Google Scholar
• Davidson, James, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He Mike Lambert, Blake Livingston, and Dasarathi Sampath. 2010. “The YouTube Video Recommendation System.” In Proceedings of the Fourth ACM Conference on Recommender Systems (RecSys '10). 293–296. New York, NY, USA: ACM. doi:https://doi.org/10.1145/1864708.1864770.
   Google Scholar
• Dey, Anind K. Jan. 2001. “Understanding and Using Context.” Personal Ubiquitous Comput. 5 (1): 4–7. doi:https://doi.org/10.1007/s007790170019.
   Web of Science ®Google Scholar
• Diakopoulos, Nicholas. 2016. “Accountability in Algorithmic Decision Making.” Communications of the ACM 59 (2): 56–62. doi: https://doi.org/10.1145/2844110
   Web of Science ®Google Scholar
• Dressel, Julia, and Hany Farid. 2018. “The Accuracy, Fairness, and Limits of Predicting Recidivism.” Science Advances 4 (1). doi:https://doi.org/10.1126/sciadv.aao5580.
   Web of Science ®Google Scholar
• Dwork, Cynthia, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012. “Fairness Through Awareness.” In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (ITCS '12). 214–226. New York, NY, USA: ACM. doi:https://doi.org/10.1145/2090236.2090255.
   Google Scholar
• Ellora Thadaney Israni. 2017. When an Algorithm Helps Send You to Prison.
   Google Scholar
• Ellul, Jacques. 1964. The Technological Society. New York: Knopf.
   Google Scholar
• Eslami, Motahhare, Aimee Rickman, Kristen Vaccaro, Amirhossein Aleyasen, Andy Vuong, Karrie Karahalios, Kevin Hamilton, and Christian Sandvig. 2015. “‘I Always Assumed That I Wasn't Really That Close to [Her]’: Reasoning About Invisible Algorithms in News Feeds.” In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). 153–162. New York, NY, USA: ACM. doi:https://doi.org/10.1145/2702123.2702556.
   Google Scholar
• Eslami, Motahhare, Kristen Vaccaro, Min Kyung Lee, Amit Elazari Bar On, Eric Gilbert, and Karrie Karahalios. 2019. “User Attitudes Towards Algorithmic Opacity and Transparency in Online Reviewing Platforms.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). 14. New York, NY, USA: ACM. Article 494. doi:https://doi.org/10.1145/3290605.3300724.
   Google Scholar
• Europost. June 2019. G20 ministers agree on human-centric AI principles.
   Google Scholar
• Garrigan, Beverley, Anna L. R. Adlam, and Peter E. Langdon. June 2018. “Moral Decision-making and Moral Development: Toward An Integrative Framework.” Developmental Review 49: 80–100. doi:https://doi.org/10.1016/j.dr.2018.06.001.
   Web of Science ®Google Scholar
• Gebru, Timnit, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumeé, and Kate Crawford. 2018. Datasheets for Datasets. CoRR 1–27.
   Google Scholar
• Gert, Bernard. 2017. “The Definition of Morality.” In The Stanford Encyclopedia of Philosophy (fall 2017 ed.), Edward N. Zalta (Ed.). New York: Metaphysics Research Lab, Stanford University.
   Google Scholar
• Glaser, Jack, and Mahzarin R Banaji. 1999. “When Fair is Foul and Foul is Fair: Reverse Priming in Automatic Evaluation.” Journal of Personality and Social Psychology 77 (4): 669. doi:https://doi.org/10.1037/0022-3514.77.4.669.
   PubMed Web of Science ®Google Scholar
• Govindarajulu, Naveen Sundar, and Selmer Bringsjord. 2017. “On Automating the Doctrine of Double Effect.” In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17). 4722–4730. AAAI Press.
   Google Scholar
• Green, Melanie C., and Timothy C. Brock. 2002. Lawrence Erlbaum Associates Publishers, Mahwah, NJ, US, Chapter In the mind's eye: Transportation-imagery model of narrative persuasion, 315–341.
   Google Scholar
• Green, Melanie C., and Jenna L. Clark. 2013. “Transportation Into Narrative Worlds: Implications for Entertainment Media Influences on Tobacco Use.” Addiction (Abingdon, England) 108 (3): 477–484. doi:https://doi.org/10.1111/j.1360-0443.2012.04088.x.
   PubMed Web of Science ®Google Scholar
• Greenwald, A. G., D. E. McGhee, and J. L. Schwartz. 1998. “Measuring Individual Differences in Implicit Cognition: the Implicit Association Test.” Journal of Personality and Social Psychology 74 (6): 1464–1480. doi: https://doi.org/10.1037/0022-3514.74.6.1464
   PubMed Web of Science ®Google Scholar
• Grizzard, Matthew, Ron Tamborini, Robert J. Lewis, Lu Wang, and Sujay Prabhu. 2014. “Being Bad in a Video Game Can Make Us Morally Sensitive.” Cyberpsychology, Behavior, and Social Networking 17 (8): 499–504. doi:https://doi.org/10.1089/cyber.2013.0658.
   PubMed Web of Science ®Google Scholar
• Hardt, Moritz, Eric Price, and Nathan Srebro. 2016. “Equality of Opportunity in Supervised Learning.” In Proceedings of the 30th International Conference on Neural Information Processing Systems (NIPS'16). 3323–3331. USA: Curran Associates Inc.
   Google Scholar
• Harman, Gilbert. 1999. “Moral Philosophy Meets Social Psychology: Virtue Ethics and the Fundamental Attribution Error.” Proceedings of the Aristotelian Society 99: 315–331. doi: https://doi.org/10.1111/1467-9264.00062
   Google Scholar
• Henrich, Joseph, Steven J Heine, and Ara Norenzayan. 2010. “Most People are Not WEIRD.” Nature 466 (7302): 29. doi: https://doi.org/10.1038/466029a
   PubMed Web of Science ®Google Scholar
• Hitron, Tom, Yoav Orlev, Iddo Wald, Ariel Shamir, Hadas Erel, and Oren Zuckerman. 2019. “Can Children Understand Machine Learning Concepts?: The Effect of Uncovering Black Boxes.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). 11. New York, NY, USA: ACM. Article 415. doi:https://doi.org/10.1145/3290605.3300645.
   Google Scholar
• Hofstede, Geert. 2011. “Dimensionalizing Cultures: The Hofstede Model in Context.” Online Readings in Psychology and Culture 2 (1): 8. doi:https://doi.org/10.9707/2307-0919.1014.
   Google Scholar
• Holstein, Kenneth, Jennifer Wortman Vaughan, Hal Daumé, Miro Dudik, and Hanna Wallach. 2019. “Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI'19). 16. New York, NY, USA: Association for Computing Machinery, Article Paper 600, doi:https://doi.org/10.1145/3290605.3300830.
   Google Scholar
• Hosio, Simo, Andy Alorwu, Niels van Berkel, Miguel Bordallo López, Mahalakshmy Seetharaman, Jonas Oppenlaender, and Jorge Goncalves. 2019. “Fueling AI with Public Displays?: A Feasibility Study of Collecting Biometrically Tagged Consensual Data on a University Campus.” In Proceedings of the 8th ACM International Symposium on Pervasive Displays (PerDis '19). 7. New York, NY, USA: ACM. Article 14, doi:https://doi.org/10.1145/3321335.3324943.
   Google Scholar
• Howard, Don, and Ioan Muntean. 2017. Artificial Moral Cognition: Moral Functionalism and Autonomous Moral Agency. Cham: Springer International Publishing. 121–159. doi: doi:https://doi.org/10.1007/978-3-319-61043-6_7.
   Google Scholar
• Iyer, Rahul, Yuezhang Li Huao Li, Michael Lewis, Ramitha Sundar, and Katia Sycara. 2018. “Transparency and Explanation in Deep Reinforcement Learning Neural Networks.” In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society (AIES '18). 144–150. New York, NY, USA: ACM. doi:https://doi.org/10.1145/3278721.3278776.
   Google Scholar
• Jhaver, Shagun, Yoni Karpfen, and Judd Antin. 2018. “Algorithmic Anxiety and Coping Strategies of Airbnb Hosts.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI'18). 12. New York, NY, USA: Association for Computing Machinery. Article Paper 421. doi:https://doi.org/10.1145/3173574.3173995.
   Google Scholar
• Jobin, Anna, Marcello Ienca, and Effy Vayena. 2019. “The Global Landscape of AI Ethics Guidelines.” Nature Machine Intelligence 1 (9): 389–399. doi:https://doi.org/10.1038/s42256-019-0088-2.
   Google Scholar
• Johnson, Dan R., Brandie L. Huffman, and Danny M. Jasper. 2014. “Changing Race Boundary Perception by Reading Narrative Fiction.” Basic and Applied Social Psychology 36 (1): 83–90. doi:https://doi.org/10.1080/01973533.2013.856791.
   Web of Science ®Google Scholar
• Johnson, Dan R, Daniel M Jasper, Sallie Griffin, and Brandie L Huffman. 2013. “Reading Narrative Fiction Reduces Arab-Muslim Prejudice and Offers a Safe Haven From Intergroup Anxiety.” Social Cognition 31 (5): 578–598. doi: https://doi.org/10.1521/soco.2013.31.5.578
   Web of Science ®Google Scholar
• Kamtekar, Rachana. 2004. “Situationism and Virtue Ethics on the Content of Our Character.” Ethics 114 (3): 458–491. doi:https://doi.org/10.1086/381696.
   Web of Science ®Google Scholar
• Kroll, Joshua A, Solon Barocas, Edward W Felten, Joel R Reidenberg, David G Robinson, and Harlan Yu. 2016. “Accountable Algorithms.” University of Pennsylvania Law Review 165: 633.
   Web of Science ®Google Scholar
• Kudina, Olya, and Peter-Paul Verbeek. 2019. “Ethics from Within: Google Glass, the Collingridge Dilemma, and the Mediated Value of Privacy.” Science, Technology, & Human Values 44 (2): 291–314. doi:https://doi.org/10.1177/0162243918793711.
   Web of Science ®Google Scholar
• van Laer, Tom, Ko de Ruyter, Luca M. Visconti, and Martin Wetzels. Aug. 2013. “The Extended Transportation-Imagery Model: A Meta-Analysis of the Antecedents and Consequences of Consumers' Narrative Transportation.” Journal of Consumer Research 40 (5): 797–817. doi:https://doi.org/10.1086/673383.
   Web of Science ®Google Scholar
• Latour, Bruno, and Couze Venn. 2002. “Morality and Technology.” Theory, Culture & Society 19 (5–6): 247–260. doi:https://doi.org/10.1177/026327602761899246.
   Web of Science ®Google Scholar
• Leavitt, Keith, Scott J. Reynolds, Christopher M. Barnes, Pauline Schilpzand, and Sean T. Hannah. 2012. “Different Hats, Different Obligations: Plural Occupational Identities and Situated Moral Judgments.” Academy of Management Journal 55 (6): 1316–1333. doi:https://doi.org/10.5465/amj.2010.1023.
   Web of Science ®Google Scholar
• Leavy, Susan. 2018. “Gender Bias in Artificial Intelligence: The Need for Diversity and Gender Theory in Machine Learning.” In Proceedings of the 1st International Workshop on Gender Equality in Software Engineering (GE '18). 14–16. New York, NY, USA: ACM. doi:https://doi.org/10.1145/3195570.3195580.
   Google Scholar
• Lepri, Bruno, Nuria Oliver, Emmanuel Letouzé, Alex Pentland, and Patrick Vinck. Dec. 1, 2018. “Fair, Transparent, and Accountable Algorithmic Decision-making Processes.” Philosophy & Technology 31 (4): 611–627. doi:https://doi.org/10.1007/s13347-017-0279-x.
   Google Scholar
• Lindquist, Kristen A, Lisa Feldman Barrett, Eliza Bliss-Moreau, and James A Russell. 2006. “Language and the Perception of Emotion.” Emotion (Washington, D.C.) 6 (1): 125. doi: https://doi.org/10.1037/1528-3542.6.1.125
   PubMed Web of Science ®Google Scholar
• Liu, Lydia T, Sarah Dean, Esther Rolf, Max Simchowitz, and Moritz Hardt. 2018. “Delayed Impact of Fair Machine Learning.” In Proceedings of the 35th International Conference on Machine Learning (Proceedings of Machine Learning Research), Jennifer Dy and Andreas Krause, eds., Vol. 80. PMLR, 3150–3158. Stockholm Sweden: Stockholmsmässan.
   Google Scholar
• Lobel, Adam, Marientina Gotsis, Erin Reynolds, Michael Annetta, Rutger C. M. E. Engels, and Isabela Granic. 2016. “Designing and Utilizing Biofeedback Games for Emotion Regulation: The Case of Nevermind.” In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '16). 1945–1951. New York, NY, USA: ACM. doi:https://doi.org/10.1145/2851581.2892521.
   Google Scholar
• Mill, J. S. 1863. Utilitarianism. London: Parker.
   Google Scholar
• Morgan, Susan E., Lauren Movius, and Michael J. Cody. 2009. “The Power of Narratives: The Effect of Entertainment Television Organ Donation Storylines on the Attitudes, Knowledge, and Behaviors of Donors and Nondonors.” Journal of Communication 59 (1): 135–151. doi:https://doi.org/10.1111/j.1460-2466.2008.01408.x.
   Web of Science ®Google Scholar
• Morgenstern, M., E. A. Poelen, R. Scholte, S. Karlsdottir, S. H. Jonsson, F. Mathis, F. Faggiano, E. Florek, H. Sweeting, K. Hunt, J. D. Sargent, and R. Hanewinkel. Oct. 2011. “Smoking in Movies and Adolescent Smoking: Cross-cultural Study in Six European Countries.” Thorax 66 (10): 875–883. doi: https://doi.org/10.1136/thoraxjnl-2011-200489
   PubMed Web of Science ®Google Scholar
• Paolacci, Gabriele, Jesse Chandler, and Panagiotis G Ipeirotis. 2010. “Running Experiments on Amazon Mechanical Turk.” Judgment and Decision Making 5 (5): 411–419.
   Web of Science ®Google Scholar
• Parsons, Thomas D.. 2015. “Virtual Reality for Enhanced Ecological Validity and Experimental Control in the Clinical, Affective and Social Neurosciences.” Frontiers in Human Neuroscience 9: 660. doi:https://doi.org/10.3389/fnhum.2015.00660.
   PubMed Web of Science ®Google Scholar
• Pasquale, Frank. 2015. The Black Box Society: the Secret Algorithms that Control Money and Information. Cambridge: Harvard University Press.
   Google Scholar
• Patil, Indrajeet, Carlotta Cogoni, Nicola Zangrando, Luca Chittaro, and Giorgia Silani. 2014. “Affective Basis of Judgment-behavior Discrepancy in Virtual Experiences of Moral Dilemmas.” Social Neuroscience 9 (1): 94–107. doi:https://doi.org/10.1080/17470919.2013.870091.
   PubMed Web of Science ®Google Scholar
• Picard, Rosalind W. 1997. Affective Computing. Cambridge: MIT Press.
   Google Scholar
• Reynolds, Scott J, Keith Leavitt, and Katherine A DeCelles. July 2010. “Automatic Ethics: the Effects of Implicit Assumptions and Contextual Cues on Moral Behavior.” The Journal of Applied Psychology95 (4): 752–760. doi:https://doi.org/10.1037/a0019411.
   PubMed Web of Science ®Google Scholar
• Roberts, Sarah. 2016. Commercial Content Moderation: Digital Laborers' Dirty Work. New York.
   Google Scholar
• Russell, James A. 1994. “Is There Universal Recognition of Emotion From Facial Expression? A Review of the Cross-Cultural Studies.” Psychological Bulletin 115 (1): 102. doi: https://doi.org/10.1037/0033-2909.115.1.102
   PubMed Web of Science ®Google Scholar
• Savulescu, Julian, and Hannah Maslen. 2015. Moral Enhancement and Artificial Intelligence: Moral AI. Cham: Springer International Publishing.79–95. doi: doi:https://doi.org/10.1007/978-3-319-09668-1_6.
   Google Scholar
• Scherr, S. A., F. Elberzhager, and K. Holl. 2018. “Acceptance Testing of Mobile Applications – Automated Emotion Tracking for Large User Groups.” In 2018 IEEE/ACM 5th International Conference on Mobile Software Engineering and Systems (MOBILESoft). 247–251.
   Google Scholar
• Shankar, Shreya, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, and D. Sculley. 2017. “No classification without representation: assessing geodiversity issues in open data sets for the developing world.” In nips 2017 workshop: machine learning for the developing world.
   Google Scholar
• Sundar Govindarajulu, Naveen, Selmer Bringsjord, Rikhiya Ghosh, and Vasanth Sarathy. 2019. “Toward the Engineering of Virtuous Machines.” In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (AIES'19). 29–35. New York, NY, USA: Association for Computing Machinery. doi:https://doi.org/10.1145/3306618.3314256.
   Google Scholar
• Tag, Benjamin, Andrew W. Vargo, Aman Gupta, George Chernyshov, Kai Kunze, and Tilman Dingler. 2019. “Continuous Alertness Assessments: Using EOG Glasses to Unobtrusively Monitor Fatigue Levels In-The-Wild.” In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI'19). 12. New York, NY: Association for Computing Machinery. Article Paper 464. doi:https://doi.org/10.1145/3290605.3300694.
   Google Scholar
• Trystan, Upstill. May 2018. The new Google News: AI meets human intelligence.
   Google Scholar
• van Berkel, Niels, Denzil Ferreira, and Vassilis Kostakos. Dec. 2017. “The Experience Sampling Method on Mobile Devices.” Comput. Surveys 50 (6): 40. Article 93, doi:https://doi.org/10.1145/3123988.
   Web of Science ®Google Scholar
• Veale, Michael, Max Van Kleek, and Reuben Binns. 2018. “Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). 14. New York, NY, USA: ACM. Article 440. doi:https://doi.org/10.1145/3173574.3174014.
   Google Scholar
• Vitell, Scott J., Saviour L. Nwachukwu, and James H. Barnes. 1993. “The Effects of Culture on Ethical Decision-making: An Application of Hofstede's Typology.” Journal of Business Ethics 12 (10): 753–760. doi:https://doi.org/10.1007/BF00881307.
   Web of Science ®Google Scholar
• Woodruff, Allison, Sarah E. Fox, Steven Rousso-Schindler, and Jeffrey Warshaw. 2018. “A Qualitative Exploration of Perceptions of Algorithmic Fairness.” In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ‘18). 14. New York, NY: ACM. Article 656. doi:https://doi.org/10.1145/3173574.3174230.
   Google Scholar
• Wyld, David C, and Coy A Jones. March 1997. “The Importance of Context: The Ethical Work Climate Construct and Models of Ethical Decision Making – An Agenda for Research.” Journal of Business Ethics 16 (4): 465–472. doi:https://doi.org/10.1023/A:1017980515603.
   Web of Science ®Google Scholar
• Yudkin, Daniel, Ana Gantman, Wilhelm Hofmann, and Jordi Quoidbach. 2019. Moral Values Gain Importance in the Presence of Others. doi:https://doi.org/10.31234/osf.io/tcq65.
   Google Scholar
• Zheng, Vincent W., Yu Zheng, Xing Xie, and Qiang Yang. 2012. “Towards Mobile Intelligence: Learning From GPS History Data for Collaborative Recommendation.” Artificial Intelligence 184–185: 17–37. doi:https://doi.org/10.1016/j.artint.2012.02.002.
   Web of Science ®Google Scholar
• Zou, James, and Londa Schiebinger. 2018. “AI Can Be Sexist and Racist–it's Time to Make it Fair.” Nature 559: 324–326. doi:https://doi.org/10.1038/d41586-018-05707-8.
   PubMed Web of Science ®Google Scholar