Unintended Side Effects of Digital Transition: Perspectives of Japanese Experts
1. Introduction and Motivations for the Roundtable
- What are the major present or future unintended side effects that call for specific attention and understanding?
- How might interdisciplinary collaborations across different disciplines contribute to solving the problems caused by unintended side effects?
- What partnerships of industry, business, government, non-governmental organizations (NGOs), or the public at large would be interested in co-designing transdisciplinary processes in which science and practice work together to learn about the sustainable use of digital technologies?
3. Phenomena: Toward an Understanding of the Relationship between Digital Technologies and Social Systems
4. Unintended Side Effects and Concerns Related to Sustainability
5.1. Japanese Perspectives in the Global Debate
5.2. Broadening Domestic Conversations
5.3. Future Work
Conflicts of Interest
Appendix A. Note on Terminology
Appendix B. Propositions on the Future Perspectives on Digital Transition
Appendix B.1. Hiroshi Deguchi
Appendix B.1.1. Proposition 1: Platform Lock-In on the B2C Market
Appendix B.1.2. Proposition 2: Top-Down Optimization and Low-Capability Business Components
Appendix B.1.3. Proposition 3: IoT-Based Second Internet Revolution & Reality Shift
Appendix B.1.4. Proposition 4: Reality Reconstruction and Reality Shift
Appendix B.2. Arisa Ema
Appendix B.2.1. Proposition 1
Appendix B.2.2. Proposition 2
Appendix B.3. Atsuo Kishimoto (Propositions on the Perspective: Risk Management)
Appendix B.3.1. Risk Based Approach (Proposition 1)
Appendix B.3.2. Specifying the Endpoints (Proposition 2)
Appendix B.3.3. Quantifying Likelihood and Severity (Proposition 3)
Appendix B.4. Junichi Mori
Appendix B.4.1. Proposition 1
Appendix B.4.2. Proposition 2
Appendix B.5. Roland W. Scholz (Propositions on the Perspective: ‘Biophysical, Genetic, and Epigenetic Level of the Digital Transformation’)
Appendix B.5.1. Proposition 1
Appendix B.5.2. Proposition 2
Appendix B.5.3. Proposition 3
- The limits of a digital conception of DNA and the potential role of analog models (e.g., in the folding of DNA)
- The understanding of the “nature” of biocomputers
- Vulnerabilities of (agro-)ecosystems and other systems with respect to the digital manipulation (e.g., directed evolution) of DNA
- Individual exposure to digital information systems (e.g., Internet addiction, massive virtual information, etc.)
- The power of knowledge about an individual’s DNA and biotechnological engineering by owners of digital knowledge.
Appendix B.6. Hideaki Shiroyama (Propositions on the Perspective: Risk and Resilience Management)
Appendix B.6.1. Proposition 1
Appendix B.6.2. Proposition 2
Appendix B.6.3. Proposition 3
Appendix B.7. Masahiro Sugiyama (Propositions on the Perspective: Job Market and Biotech Risks)
Appendix B.7.1. Proposition 1
Appendix B.7.2. Proposition 2
Appendix B.7.3. Proposition 3
- Government of Japan. The 5th Science and Technology Basic Plan; Government of Japan: Tokyo, Japan, 2016.
- Committee on Technology. Preparing for the Future of Artificial Intelligence; Executive Office of the President: Washington, DC, USA, 2016.
- Executive Office of the President. Artificial Intelligence, Automation, and the Economy; Executive Office of the President: Washington, DC, USA, 2016.
- World Economic Forum. The Global Risks Report 2017; World Economic Forum: Geneva, Switzerland, 2017. [Google Scholar]
- Harriss, L.; Ennis, J. Automation and the Workforce; Parliamentary Office of Science and Technology: London, UK, 2016. [Google Scholar]
- European Parliamentary Technology Assessment (EPTA). The Future of Labour in the Digital Era: Ubiquitous Computing, Virtual Platforms, and Real-Time Production; European Parliamentary Technology Assessment: Vienna, Austria, 2016. [Google Scholar]
- Stone, P.; Brooks, R.; Brynjolfsson, E.; Calo, R.; Etzioni, O.; Hager, G.; Hirschberg, J.; Kalyanakrishnan, S.; Kamar, E.; Kraus, S.; et al. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015–2016 Study Panel; Stanford University: Stanford, CA, USA, 2016. [Google Scholar]
- Tenets|Partnership on Artificial Intelligence to Benefit People and Society. Available online: https://www.partnershiponai.org/tenets/ (accessed on 23 September 2017).
- The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems. Ethically Aligned Design: A Vision for Prioritizing Human Wellbeing with Artificial Intelligence and Autonomous Systems; IEEE: New York, NY, USA, 2016. [Google Scholar]
- AI Principles—Future of Life Institute. Available online: https://futureoflife.org/ai-principles/ (accessed on 23 September 2017).
- The Conference toward AI Network Society. Draft AI R&D Guidelines for International Discussions; The Conference toward AI Network Society; Ministry of Internal Affairs and Communications: Tokyo, Japan, 2017.
- Japanese Society for Artificial Intelligence. The Japanese Society for Artificial Intelligence Ethical Guidelines; Japanese Society for Artificial Intelligence: Tokyo, Japan, 2017. [Google Scholar]
- Matsuo, Y. About the Japanese Society for Artificial Intelligence Ethical Guidelines. Available online: http://ai-elsi.org/archives/514 (accessed on 23 September 2017).
- Japanese Society for Artificial Intelligence Ethics Committee Summary Report—Open Discussion: The Japanese Society for Artificial Intelligence (2017/5/24). Available online: http://ai-elsi.org/archives/615 (accessed on 23 September 2017).
- Ema, A. Ethically Aligned Design Dialogue: A Case Practice of Responsible Research and Innovation. Jinko Chino (Artif. Intell.) 2017, 32, 694–700. (In Japanese) [Google Scholar]
- Advisory Board on Artificial Intelligence and Human Society. Report on Artificial Intelligence and Human Society; Advisory Board on Artificial Intelligence and Human Society: Tokyo, Japan, 2017. [Google Scholar]
- Acceptable Intelligence with Responsibility. Available online: http://sig-air.org/ (accessed on 23 September 2017).
- Future of Life Institute Benefits and Risks of Artificial Intelligence. Available online: https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/ (accessed on 7 October 2017).
- Chang, J.-H.; Rynhart, G.; Huynh, P. ASEAN in Transformation: How Technology Is Changing Jobs and Enterprises; International Labor Organization: Genève, Switzerland, 2016. [Google Scholar]
- Owen, R.; Macnaghten, P.; Stilgoe, J. Responsible research and innovation: From science in society to science for society, with society. Sci. Public Policy 2012, 39, 751–760. [Google Scholar] [CrossRef]
- Stilgoe, J.; Owen, R.; Macnaghten, P. Developing a framework for responsible innovation. Res. Policy 2013, 42, 1568–1580. [Google Scholar] [CrossRef][Green Version]
- European Commission Directorate-General for Research and Innovation. Options for Strengthening Responsible Research and Innovation: Report of the Expert Group on the State of Art in Europe on Responsible Research and Innovation; Publications Office of the European Union: Luxemborg, 2013. [Google Scholar]
- Von Schomberg, R. (Ed.) Towards Responsible Research and Innovation in the Information and Communication Technologies and Security Technologies Fields; Publications Office of the European Union: Luxemborg, 2011. [Google Scholar]
- Osawa, H.; Ema, A.; Hattori, H.; Akiya, N.; Kanzaki, N.; Kubo, A.; Koyama, T.; Ichise, R. What is Real Risk and Benefit on Work with Robots? In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’17, Vienna, Austria, 6–9 March 2017; ACM Press: New York, NY, USA, 2017; pp. 241–242. [Google Scholar]
- Kajikawa, Y. Research core and framework of sustainability science. Sustain. Sci. 2008, 3, 215–239. [Google Scholar] [CrossRef]
- Laws, D.; Scholz, R.W.; Shiroyama, H.; Susskind, L.; Suzuki, T.; Weber, O. Expert views on sustainability and technology implementation. Int. J. Sustain. Dev. World Ecol. 2004, 11, 247–261. [Google Scholar] [CrossRef]
- Scholz, R. The Normative Dimension in Transdisciplinarity, Transition Management, and Transformation Sciences: New Roles of Science and Universities in Sustainable Transitioning. Sustainability 2017, 9, 991. [Google Scholar] [CrossRef]
- The United Nations General Assembly. Resolution Adopted by the General Assembly on 25 September 2015--Transforming Our World: The 2030 Agenda for Sustainable Development; The United Nations General Assembly: New York, NY, USA, 2015. [Google Scholar]
- Scholz, R. Transdisciplinary transition processes for adaptation to climate change. In From Climate Change to Social Change: Perspectives on Science-Policy Interactions; Driessen, P.P.J., Leroy, P., Van Vierssen, W., Eds.; International Books: Utrecht, The Netherlands, 2010; pp. 69–94. [Google Scholar]
- Scholz, R.W.; Steiner, G. The real type and ideal type of transdisciplinary processes: Part I—Theoretical foundations. Sustain. Sci. 2015, 10, 527–544. [Google Scholar] [CrossRef]
- Silver, D.; Huang, A.; Maddison, C.J.; Guez, A.; Sifre, L.; van den Driessche, G.; Schrittwieser, J.; Antonoglou, I.; Panneershelvam, V.; Lanctot, M.; et al. Mastering the game of Go with deep neural networks and tree search. Nature 2016, 529, 484–489. [Google Scholar] [CrossRef] [PubMed]
- Huang, X.; Baker, J.; Reddy, R. A historical perspective of speech recognition. Commun. ACM 2014, 57, 94–103. [Google Scholar] [CrossRef]
- Markoff, J. A Learning Advance in Artificial Intelligence Rivals Human Abilities. The New York Times, 10 December 2015; B3. [Google Scholar]
- LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436–444. [Google Scholar] [CrossRef] [PubMed]
- Moore, G.E. Cramming more components onto integrated circuits. Electronics 1965, 38, 114. [Google Scholar] [CrossRef]
- Mayer-Schönberger, V.; Cukier, K. Big Data: A Revolution that Will Transform How We Live, Work, and Think; Houghton Mifflin Harcourt: Boston, MA, USA, 2013; ISBN 0544227751. [Google Scholar]
- Crane, D. Theoretical models and emerging trends. In Global Culture: Media, Arts, Policy, and Globalization; Crane, D., Kawashima, N., Kawasaki, K., Eds.; Routledge: London, UK, 2002; pp. 1–28. [Google Scholar]
- Zolfagharifard, E. Would you Take Orders from a ROBOT? An Artificial Intelligence Becomes the World’s First Company Director. Available online: http://www.dailymail.co.uk/sciencetech/article-2632920/Would-orders-ROBOT-Artificial-intelligence-world-s-company-director-Japan.html#ixzz (accessed on 7 October 2017).
- Rahman, K. “We Don’t Hurt Anybody, We Are Just Happy”: Woman Reveals She Has Fallen in Love with a ROBOT and Wants to Marry it. Available online: http://www.dailymail.co.uk/femail/article-4060440/Woman-reveals-love-ROBOT-wants-marry-it.html (accessed on 7 October 2017).
- Extance, A. How DNA could store all the world’s data. Nature 2016, 537, 22–24. [Google Scholar] [CrossRef] [PubMed]
- Scholz, R.W.; Steiner, G. Transdisciplinarity at the crossroads. Sustain. Sci. 2015, 10, 521–526. [Google Scholar] [CrossRef]
- Ema, A.; Akiya, N.; Osawa, H.; Hattori, H.; Oie, S.; Ichise, R.; Kanzaki, N.; Kukita, M.; Saijo, R.; Takushi, O.; et al. Future Relations between Humans and Artificial Intelligence: A Stakeholder Opinion Survey in Japan. IEEE Technol. Soc. Mag. 2016, 35, 68–75. [Google Scholar] [CrossRef]
- Meinrath, S.D.; Losey, J.W.; Pickard, V.W. Digital feudalism: Enclosures and erasures from digital rights management to the digital divide. CommLaw Conspec. 2011, 19, 423–479. [Google Scholar]
- Sornette, D.; Ouillon, G. Dragon-kings: Mechanisms, statistical methods and empirical evidence. Eur. Phys. J. Spec. Top. 2012, 205, 1–26. [Google Scholar] [CrossRef]
- Taleb, N.N. The Black Swan: The Impact of the Highly Improbable; Random House: New York, NY, USA, 2007. [Google Scholar]
- Frey, C.B.; Osborne, M.A. The Future of Employment: How Susceptible Are Jobs to Computerization? Oxford Martin Programme on Technology and Employment: Oxford, UK, 2013. [Google Scholar]
- Finucane, M.L.; Holup, J.L. Psychosocial and cultural factors affecting the perceived risk of genetically modified food: An overview of the literature. Soc. Sci. Med. 2005, 60, 1603–1612. [Google Scholar] [CrossRef] [PubMed]
- Liang, X.; Ho, S.S.; Brossard, D.; Xenos, M.A.; Scheufele, D.A.; Anderson, A.A.; Hao, X.; He, X. Value predispositions as perceptual filters: Comparing of public attitudes toward nanotechnology in the United States and Singapore. Public Underst. Sci. 2015, 24, 582–600. [Google Scholar] [CrossRef] [PubMed]
- Visschers, V.H.M.; Shi, J.; Siegrist, M.; Arvai, J. Beliefs and values explain international differences in perception of solar radiation management: insights from a cross-country survey. Clim. Chang. 2017, 142, 531–544. [Google Scholar] [CrossRef]
- Fraune, M.; Kawakami, S.; Sabanovic, S.; de Silva, R.; Okada, M. Three’s company, or a crowd: The effects of robot number and behavior on HRI in Japan and the USA. In Robotics: Science and Systems XI; Robotics Science and Systems Foundation: Rome, Italy, 2015. [Google Scholar]
- Lee, H.R.; Sabanović, S. Culturally variable preferences for robot design and use in South Korea, Turkey, and the United States. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’14, Bielefeld, Germany, 3–6 March 2014; ACM Press: New York, NY, USA, 2014; pp. 17–24. [Google Scholar]
- Geraci, R.M. Spiritual robots: Religion and our scientific view of the natural world. Theol. Sci. 2006, 4, 229–246. [Google Scholar] [CrossRef]
- Ema, A. Artificial Intelligence and Future Society: Projects and Prospect. In Proceedings of the 29th Annual Conference of the Japanese Society for Artificial Intelligence, Hakodate, Japan, 30 May–2 June 2015. (In Japanese). [Google Scholar]
- Report: Open Discussion: The Japanese Society for Artificial Intelligence (2017/5/24). Available online: http://ai-elsi.org/archives/628 (accessed on 7 October 2017).
- Civic Debate. Available online: http://ai-initiative.org/ai-consultation/ (accessed on 7 October 2017).
- Mikami, N. Public Participation in Decision-Making on Energy Policy: The Case of the “National Discussion” after the Fukushima Accident. In Lessons from Fukushima; Springer International Publishing: Cham, Switzerland, 2015; pp. 87–122. [Google Scholar]
- Brundage, M. Artificial Intelligence and Responsible Innovation. In Fundamental Issues of Artificial Intelligence; Müller, V., Ed.; Springer International Publishing: Cham, Switzerland, 2016; pp. 543–554. [Google Scholar]
- Scheufele, D.A.; Xenos, M.A.; Howell, E.L.; Rose, K.M.; Brossard, D.; Hardy, B.W. U.S. attitudes on human genome editing. Science 2017, 357, 553–554. [Google Scholar] [CrossRef] [PubMed]
- Carr, W.; Preston, C.J.; Yung, L.; Szerszynski, B.; Keith, D.W.; Mercer, A.M. Public engagement on solar radiation management and why it needs to happen now. Clim. Chang. 2013, 121, 567–577. [Google Scholar] [CrossRef]
- Sugiyama, M.; Kosugi, T.; Ishii, A.; Asayama, S. Public Attitudes to Climate Engineering Research and Field Experiments: Preliminary Results of a Web Survey on Students’ Perception in Six Asia-Pacific Countries. Available online: http://pari.u-tokyo.ac.jp/eng/publications/WP16_24.html (accessed on 7 October 2017).
- Rowe, G.; Frewer, L.J. A Typology of Public Engagement Mechanisms. Sci. Technol. Hum. Values 2005, 30, 251–290. [Google Scholar] [CrossRef]
- Nishizawa, M. Citizen deliberations on science and technology and their social environments: case study on the Japanese consensus conference on GM crops. Sci. Public Policy 2005, 32, 479–489. [Google Scholar] [CrossRef]
- Sugiyama, M.; Asayama, S.; Ishii, A.; Kosugi, T.; Moore, J.C.; Lin, J.; Lefale, P.F.; Burns, W.; Fujiwara, M.; Ghosh, A.; et al. The Asia-Pacific’s role in the emerging solar geoengineering debate. Clim. Chang. 2017, 143, 1–12. [Google Scholar] [CrossRef]
- Sugiyama, M.; Asayama, S.; Kosugi, T.; Ishii, A.; Emori, S.; Adachi, J.; Akimoto, K.; Fujiwara, M.; Hasegawa, T.; Hibi, Y.; et al. Transdisciplinary co-design of scientific research agendas: 40 research questions for socially relevant climate engineering research. Sustain. Sci. 2017, 12, 31–44. [Google Scholar] [CrossRef]
- Kelly, K. The Inevitable: Understanding the 12 Technological Forces that Will Shape Our Future; Penguin: New York, NY, USA, 2016; ISBN 9780525428084. [Google Scholar]
- Hilbert, M.; Lopez, P. The World’s Technological Capacity to Store, Communicate, and Compute Information. Science 2011, 332, 60–65. [Google Scholar] [CrossRef] [PubMed]
- Schumpeter, J. Business Cycles: A Theoretical, Historical, and Statistical Analysis of the Capitalist Process; McGraw-Hill: New York, NY, USA, 1939. [Google Scholar]
- Latour, B.; Woolgar, S. Laboratory Life: The Construction of Scientific Facts; Princeton University Press: Princeton, NJ, USA, 1979. [Google Scholar]
- Ensmenger, N. The Digital Construction of Technology: Rethinking the History of Computers in Society. Technol. Cult. 2012, 53, 753–776. [Google Scholar] [CrossRef]
- Deguchi, H. Learning Dynamics in Platform Externality. In Economics as an Agent-Based Complex System; Springer: Tokyo, Japan, 2004; pp. 219–244. [Google Scholar]
- Smith, A. The Wealth of Nations: Books 1-3; Penguin Classics: London, UK, 1982. [Google Scholar]
- Babbage, C. On the Economy of Machinery and Manufactures; Nabu Press: Charleston, SC, USA, 2011. [Google Scholar]
- Gratton, L. The Shift: The Future of Work is Already Here; HarperCollins Business: London, UK, 2011. [Google Scholar]
- Rifkin, J. The Zero Marginal Cost Society: The Internet of Things, the Collaborative Commons, and the Eclipse of Capitalism; Griffin: New York, NY, USA, 2015. [Google Scholar]
- Deguchi, H. Toward Next Generation Social Systems Sciences—From Cross Cultural and Science of Artificial Points of View. In Proceedings of the XVIII ISA World Congress of Sociology, Yokohama, Japan, 13–19 July 2014; Tokyo Institute of Technology: Yokohama, Japan, 2014. [Google Scholar]
- Giddens, A. The Consequences of Modernity; Polity: Cambridge, UK, 1991. [Google Scholar]
- Bauman, Z. Liquid Modernity; Polity: Cambridge, UK, 2000. [Google Scholar]
- Wyatt, S. Non-Users Also Matter: The Construction of Users and Non-Users of the Internet. In How Users Matter: The Co-Construction of Users and Technologies; Oudshoorn, N., Pinch, T.J., Eds.; MIT Press: Cambridge, UK, 2003; pp. 67–79. [Google Scholar]
- Wagner, I.; Boiten, E. Privacy Risk Assessment: From Art to Science, By Metrics. arXiv, 2017; arXiv:1709.03776. [Google Scholar]
- Weinberg, A.M. Science and trans-science. Minerva 1972, 10, 209–222. [Google Scholar] [CrossRef]
- Helbing, D.; Frey, B.S.; Gigerenzer, G.; Hafen, E.; Hagner, M.; Hofstetter, Y.; van den Hoven, J.; Zicari, R.V.; Zwitter, A. Will Democracy Survive Big Data and Artificial Intelligence? Available online: https://www.scientificamerican.com/article/will-democracy-survive-big-data-and-artificial-intelligence/ (accessed on 7 October 2017).
- Esau, M.; Rozema, M.; Zhang, T.H.; Zeng, D.; Chiu, S.; Kwan, R.; Moorhouse, C.; Murray, C.; Tseng, N.-T.; Ridgway, D.; et al. Solving a Four-Destination Traveling Salesman Problem Using Escherichia coli Cells As Biocomputers. ACS Synth. Biol. 2014, 3, 972–975. [Google Scholar] [CrossRef] [PubMed]
- Zhirnov, V.V.; Cavin, R.K. Future Microsystems for Information Processing: Limits and Lessons From the Living Systems. IEEE J. Electr. Devices Soc. 2013, 1, 29–47. [Google Scholar] [CrossRef]
- Montag, C.; Sindermann, C.; Becker, B.; Panksepp, J. An Affective Neuroscience Framework for the Molecular Study of Internet Addiction. Front. Psychol. 2016, 7, 1906. [Google Scholar] [CrossRef] [PubMed]
- Woollett, K.; Maguire, E.A. Exploring anterograde associative memory in London taxi drivers. NeuroReport 2012, 23, 885–888. [Google Scholar] [CrossRef] [PubMed]
- Bollati, V.; Baccarelli, A. Environmental epigenetics. Heredity 2010, 105, 105–112. [Google Scholar] [CrossRef] [PubMed]
- Jirtle, R.L.; Tyson, F.L. (Eds.) Environmental Epigenomics in Health and Disease: Epigenetics and Disease Origins; Springer: Berlin/Heidelberg, Germany, 2013. [Google Scholar]
|Reports and Activities||Description|
|Report by an expert committee under the Cabinet Office (2017) ||Reported on benefits and risks of existing and near-term technologies, based on stakeholder dialogues|
|Report by an expert committee under the Ministry of Internal Affairs and Communication (2017) ||Discussed issues on a network of AI systems and developed guidelines for AI research|
|Japanese Society for Artificial Intelligence, Ethics Committee||Adopted ethical guidelines for AI research  in February 2017, developed after extensive public discussions|
|Acceptable Intelligence with Responsibility ||A voluntary group of scientists from various disciplines who discuss the institutional and ethical issues related to the AI age|
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Sugiyama, M.; Deguchi, H.; Ema, A.; Kishimoto, A.; Mori, J.; Shiroyama, H.; Scholz, R.W. Unintended Side Effects of Digital Transition: Perspectives of Japanese Experts. Sustainability 2017, 9, 2193. https://doi.org/10.3390/su9122193
Sugiyama M, Deguchi H, Ema A, Kishimoto A, Mori J, Shiroyama H, Scholz RW. Unintended Side Effects of Digital Transition: Perspectives of Japanese Experts. Sustainability. 2017; 9(12):2193. https://doi.org/10.3390/su9122193Chicago/Turabian Style
Sugiyama, Masahiro, Hiroshi Deguchi, Arisa Ema, Atsuo Kishimoto, Junichiro Mori, Hideaki Shiroyama, and Roland W. Scholz. 2017. "Unintended Side Effects of Digital Transition: Perspectives of Japanese Experts" Sustainability 9, no. 12: 2193. https://doi.org/10.3390/su9122193