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Social Simulation Models at the Ethical Crossroads

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Abstract

Computational models of group opinion dynamics are one of the most active fields of sociophysics. In recent years, advances in model complexity and, in particular, the possibility to connect these models with detailed data describing individual behaviors, preferences and activities, have opened the way for the simulations to describe quantitatively selected, real world social systems. The simulations could be then used to study ‘what-if’ scenarios for opinion change campaigns, political, ideological or commercial. The possibility of the practical application of the attitude change models necessitates that the research community working in the field should consider more seriously the moral aspects of their efforts, in particular the potential for their use for unintended goals. The paper discusses these issues, and offers a suggestion for a new research direction: using the attitude models to increase the awareness and detection of social manipulation cases. Such research would offer a scientific challenge and meet the ethical criteria.

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References

  • Aach, J., Lunshof, J., Iyer, E., & Church, G. M. (2017). Addressing the ethical issues raised by synthetic human entities with embryo-like features. eLife, 6, e20674.

    Article  Google Scholar 

  • Alvarez, R., Garcia, D., Moreno, Y., & Schweitzer, F. (2015). Sentiment cascades in the 15M movement. EPJ Data Science, 4(1), 6.

    Article  Google Scholar 

  • Athey, S. (2017). Beyond prediction: Using Big Data for policy problems. Science, 355(6324), 483–485.

    Article  Google Scholar 

  • Ball, P. (2002). The physical modelling of society: A historical perspective. Physica A: Statistical Mechanics and its Applications, 314(1), 1–14.

    Article  Google Scholar 

  • Ben-Naim, E., Frachebourg, L., & Krapivsky, P. L. (1996). Coarsening and persistence in the voter model. Physical Review E, 53(4), 3078–3087.

    Article  Google Scholar 

  • Bernardes, A. T., Costa, U. M. S., Araujo, A. D., & Stauffer, D. (2001). Damage spreading, coarsening dynamics and distribution of political votes in Sznajd model on square lattice. International Journal of Modern Physics C, 12(2), 159–168.

    Article  Google Scholar 

  • Borge-Holthoefer, J., Meloni, S., Gonçalves, B., Moreno, Y., Moretti, P., Liu, S., et al. (2013). Emergence of influential spreaders in modified rumor models. Journal of Statistical Physics, 151, 383–393.

    Article  Google Scholar 

  • Boyd, D., & Crawford, K. (2011). Six provocations for Big Data. In A decade in internet time: Symposium on the dynamics of the internet and society (Vol. 21). Oxford: Oxford Internet Institute.

  • Castellano, C., Vilone, D., & Vespignani, A. (2003). Incomplete ordering of the voter model on small-world networks. EPL (Europhysics Letters), 63, 153.

    Article  Google Scholar 

  • Cox, J., & Griffeath, D. (1986). Diffusive clustering in the two dimensional voter model. The Annals of Probability, 14(2), 347–370.

    Article  Google Scholar 

  • Das, S., Lavoie, A., & Magdon-Ismail, M. (2016). Manipulation among the arbiters of collective intelligence: How Wikipedia administrators mold public opinion. ACM Transactions on the Web (TWEB), 10(4), 24.

    Google Scholar 

  • Deffuant, G., Neau, D., Amblard, F., & Weisbuch, G. (2000). Mixing beliefs among interacting agents. Advances in Complex Systems, 3, 87–98.

    Article  Google Scholar 

  • Deffuant, G., Amblard, F., Weisbuch, G., & Faure, T. (2002). How can extremism prevail? A study based on the relative agreement interaction model. Journal of Artificial Societies and Social Simulation, 5(4). http://jasss.soc.surrey.ac.uk/5/4/1.html.

  • de Lima, T. F. M., Lana, R. M., de Senna Carneiro, T. G., Codeço, C. T., Machado, G. S., Ferreira, L. S., et al. (2016). DengueMe: A tool for the modeling and simulation of dengue spatiotemporal dynamics. International Journal of Environmental Research and Public Health, 13(9), 920.

    Article  Google Scholar 

  • Dellarocas, C. (2006). Strategic manipulation of Internet opinion forums: Implications for consumers and firms. Management Science, 52(10), 1577–1593.

    Article  Google Scholar 

  • DellaVigna, S., & Kaplan, E. (2007). The Fox News effect: Media bias and voting. The Quarterly Journal of Economics, 122(3), 1187–1234.

    Article  Google Scholar 

  • Duggins, P. (2017). A psychologically-motivated model of opinion change with applications to American politics. Journal of Artificial Societies and Social Simulation, 20, 13.

    Article  Google Scholar 

  • Ehni, H. J. (2008). Dual use and the ethical responsibility of scientists. Archivum Immunologiae et Therapiae Experimentalis, 56(3), 147.

    Article  Google Scholar 

  • Epstein, R., & Robertson, R. E. (2015). The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences, 112(33), E4512–E4521.

    Article  Google Scholar 

  • Faria, N., Quick, J., Claro, I., Thézé, J., de Jesus, J., Giovanetti, M., et al. (2017). Establishment and cryptic transmission of Zika virus in Brazil and the Americas. Nature, 546(7658), 406–410.

    Article  Google Scholar 

  • Fleischmann, K. R., & Wallace, W. A. (2006). Ethical implications of values embedded in computational models: An exploratory study. Proceedings of the Association for Information Science and Technology, 43(1), 1–16.

    Article  Google Scholar 

  • Fleischmann, K. R., & Wallace, W. A. (2017). Ethical implications of computational modeling. The Bridge, 41(1), 45–51.

    Google Scholar 

  • Forelle, M., Howard, P., Monroy-Hernández, A., & Savage, S. (2015). Political bots and the manipulation of public opinion in Venezuela. arXiv preprint arXiv:150707109.

  • Fortunato, S., & Castellano, C. (2007). Scaling and universality in proportional elections. Physical Review Letters, 99(13), 138–701.

    Article  Google Scholar 

  • Galam, S. (2012). Sociophysics: A physicist’s modeling of psycho-political phenomena. Berlin: Springer.

    Book  Google Scholar 

  • Galam, S. (2016). The Trump phenomenon, an explanation from sociophysics. arXiv preprint arXiv:160903933.

  • Galam, S., Chopard, B., & Droz, M. (2002). Killer geometries in competing species dynamics. Physica A: Statistical Mechanics and Its Applications, 314(1), 256–263.

    Article  Google Scholar 

  • Gorwa, R. (2017). Computational propaganda in Poland: False amplifiers and the digital public sphere. Technical report working paper 2017. 2, Project on Computational Propaganda, University of Oxford.

  • Grubaugh, N. D., Ladner, J. T., Kraemer, M. U., Dudas, G., Tan, A. L., Gangavarapu, K., et al. (2017). Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Nature, 546(7658), 401–405.

    Article  Google Scholar 

  • Hegselmann, R., & Krause, U. (2002). Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of Artificial Societies and Social Simulation, 5(3). http://jasss.soc.surrey.ac.uk/5/3/2.html.

  • Holyst, J., Kacperski, K., & Schweitzer, F. (2001). Social impact models of opinion dynamics. Annual Reviews of Computational Physics, 9, 253–273. https://doi.org/10.1142/9789812811578.

    Article  Google Scholar 

  • Horbulin, W. P., Dodonow, O. G., & Lande, D. W. (2009). Informacijni operacji ta bezpeka suspilstwa: zagrozy, protidatia modellowanja. Technical report, Institut Problem Nacionalnoi Bezpieki i Oborony Ukraini (National Security and Defense Council of Ukraine).

  • Hosni, H., & Vulpiani, A. (2017). Forecasting in light of Big Data. Philosophy & Technology. https://doi.org/10.1007/s13347-017-0265-3.

  • Hufnagel, L., Brockmann, D., & Geisel, T. (2004). Forecast and control of epidemics in a globalized world. Proceedings of the National Academy of Sciences of the United States of America, 101(42), 15124–15129.

    Article  Google Scholar 

  • Kacperski, K., & Holyst, J. (1999). Opinion formation model with strong leader and external impact: A mean field approach. Physica A, 269, 511–526.

    Article  Google Scholar 

  • Kacperski, K., & Holyst, J. (2000). Phase transitions as a persistent feature of groups with leaders in models of opinion formation. Physica A, 287, 631–643.

    Article  Google Scholar 

  • Kelman, H. C. (1965). Manipulation of human behavior: An ethical dilemma for the social scientist. Journal of Social Issues, 21(2), 31–46.

    Article  Google Scholar 

  • Kijowski, D. J., Dankowicz, H., & Loui, M. C. (2013). Observations on the responsible development and use of computational models and simulations. Science and Engineering Ethics, 19(1), 63–81.

    Article  Google Scholar 

  • Kleijnen, J. P. (2001). Ethical issues in modeling: Some reflections. European Journal of Operational Research, 130(1), 223–230.

    Article  Google Scholar 

  • Koepsell, D. (2010). On genies and bottles: Scientists moral responsibility and dangerous technology R&D. Science and Engineering Ethics, 16(1), 119–133.

    Article  Google Scholar 

  • Le Menestrel, M., & Van Wassenhove, L. N. (2004). Ethics outside, within, or beyond or models? European Journal of Operational Research, 153(2), 477–484.

    Article  Google Scholar 

  • Lekka-Kowalik, A. (2010). Why science cannot be value-free. Science and Engineering Ethics, 16(1), 33–41.

    Article  Google Scholar 

  • Metsky, H. C., Matranga, C. B., Wohl, S., Schaffner, S. F., Freije, C. A., Winnicki, S. M., et al. (2017). Zika virus evolution and spread in the Americas. Nature, 546(7658), 411–415.

    Article  Google Scholar 

  • Mihaylov, T., Georgiev, G., & Nakov, P. (2015a). Finding opinion manipulation trolls in news community forums. In CoNLL (pp. 310–314).

  • Mihaylov, T., Koychev, I., Georgiev, G., & Nakov, P. (2015b). Exposing paid opinion manipulation trolls. In RANLP (pp. 443–450).

  • Miller, S., & Selgelid, M. J. (2007). Ethical and philosophical consideration of the dual-use dilemma in the biological sciences. Science and Engineering Ethics, 13(4), 523–580.

    Article  Google Scholar 

  • Moran, K. R., Fairchild, G., Generous, N., Hickmann, K., Osthus, D., Priedhorsky, R., et al. (2016). Epidemic forecasting is messier than weather forecasting: The role of human behavior and Internet data streams in epidemic forecast. Journal of Infectious Diseases, 214(Suppl 4), S404–S408.

    Article  Google Scholar 

  • Nowak, A., & Lewenstein, M. (1996). Modeling social change with cellular automata. In R. Hegselmann, U. Mueller, & K. G. Troitzsch (Eds.), Modelling and simulation in the social sciences from a philosophy of science point of view (pp. 249–285). Dordrecht: Kluver.

    Chapter  Google Scholar 

  • Nowak, A., Szamrej, J., & Latané, B. (1990). From private attitude to public opinion: A dynamic theory of social impact. Psychological Review, 97(3), 362–376.

    Article  Google Scholar 

  • O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. New York, NY: Crown Publishing Group.

    Google Scholar 

  • Palmer, E. (2017). Beyond proximity: Consequentialist ethics and system dynamics. Etikk i praksis-Nordic Journal of Applied Ethics, 11(1), 89–105.

    Google Scholar 

  • Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. London: Penguin.

    Google Scholar 

  • Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Peña-López, I., Congosto, M., & Aragón, P. (2014). Spanish Indignados and the evolution of the 15M movement on Twitter: Towards networked para-institutions. Journal of Spanish Cultural Studies, 15(1–2), 189–216.

    Article  Google Scholar 

  • Pruyt, E., & Kwakkel, J. (2007). Combining system dynamics and ethics: Towards more science. In 25th international conference of the system dynamics society, Boston, July 2007.

  • Sabatelli, L., & Richmond, P. (2003). Phase transitions, memory and frustration in a Sznajd-like model with synchronous updating. International Journal of Modern Physics C, 14, 1223–1229.

    Article  Google Scholar 

  • Sabatelli, L., & Richmond, P. (2004). Non-monotonic spontaneous magnetization in a Sznajd-like consensus model. Physica A: Statistical Mechanics and its Applications, 334(1), 274–280.

    Article  Google Scholar 

  • Selgelid, M. J. (2009). Governance of dual-use research: An ethical dilemma. Bulletin of the World Health Organization, 87(9), 720–723.

    Article  Google Scholar 

  • Slanina, F., & Lavicka, H. (2003). Analytical results for the Sznajd model of opinion formation. European Physical Journal B-Condensed Matter, 35(2), 279–288.

    Google Scholar 

  • Sobkowicz, P. (2009). Modelling opinion formation with physics tools: Call for closer link with reality. Journal of Artificial Societies and Social Simulation, 12(1). http://jasss.soc.surrey.ac.uk/12/1/11.html.

    Google Scholar 

  • Sobkowicz, P. (2010). Effect of leader’s strategy on opinion formation in networked societies with local interactions. International Journal of Modern Physics C (IJMPC), 21(6), 839–852.

    Article  Google Scholar 

  • Sobkowicz, P. (2016). Quantitative agent based model of opinion dynamics: Polish elections of 2015. PLoS ONE, 11(5), e0155098.

    Article  Google Scholar 

  • Stauffer, D. (2001). Monte Carlo simulations of Sznajd models. Journal of Artificial Societies and Social Simulation, 5(1). http://jasss.soc.surrey.ac.uk/5/1/4.html.

  • Stauffer, D. (2002). Sociophysics: The Sznajd model and its applications. Computer Physics Communications, 146(1), 93–98.

    Article  Google Scholar 

  • Stauffer, D., & de Oliveira, P. M. C. (2002). Persistence of opinion in the Sznajd consensus model: Computer simulation. The European Physical Journal B-Condensed Matter, 30(4), 587–592.

    Google Scholar 

  • Sunstein, C. R. (2016). Fifty shades of manipulation. Journal of Marketing Behavior, 1(3–4), 213–244.

    Google Scholar 

  • Sznajd-Weron, K., & Sznajd, J. (2000). Opinion evolution in closed community. International Journal of Modern Physics C, 11, 1157–1166.

    Article  Google Scholar 

  • Tufekci, Z. (2014). Engineering the public: Big Data, surveillance and computational politics. First Monday, 19(7). https://doi.org/10.5210/fm.v19i7.4901.

  • Van den Broeck, W., Gioannini, C., Gonçalves, B., Quaggiotto, M., Colizza, V., & Vespignani, A. (2011). The Gleamviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infectious Diseases, 11(1), 37.

    Article  Google Scholar 

  • Verelst, F., Willem, L., & Beutels, P. (2016). Behavioural change models for infectious disease transmission: A systematic review (2010–2015). Journal of the Royal Society Interface, 13(125), 20160820.

    Article  Google Scholar 

  • Weisbuch, G. (2004). Bounded confidence and social networks. The European Physical Journal B-Condensed Matter and Complex Systems, 38(2), 339–343.

    Article  Google Scholar 

  • Weisbuch, G., Deffuant, G., Amblard, F., & Nadal, J. P. (2003). Interacting agents and continuous opinions dynamics. In R. Cowan & N. Jonard (Eds.), Heterogenous agents, interactions and economic performance. Lecture notes in economics and mathematical systems (Vol. 521, pp. 225–242). Berlin: Springer.

    Chapter  Google Scholar 

  • Wragg, T. (2006). Modelling the effects of information campaigns using agent-based simulation. http://www.dsto.defence.gov.au/publications/4498/DSTO-TR-1853.pdf.

  • Zhang, M., Verbraeck, A., Meng, R., Chen, B., & Qiu, X. (2016). Modeling spatial contacts for epidemic prediction in a large-scale artificial city. Journal of Artificial Societies and Social Simulation, 19(4). http://jasss.soc.surrey.ac.uk/19/4/3.html.

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Acknowledgements

The author would like the anonymous Reviewers for their stimulating remarks leading to significant improvements in understanding of the nature of the ethical issues involved in opinion modeling research.

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    Pawel Sobkowicz

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Sobkowicz, P. Social Simulation Models at the Ethical Crossroads. Sci Eng Ethics 25, 143–157 (2019). https://doi.org/10.1007/s11948-017-9993-0

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