We ask whether the three domains proposed in Information Domains (individual, social, and signification) can provide a useful framework for analyzing distributed morality (DM) and its potential consequences. DM is present when moral responsibility is distributed across human and artificial agents. The affordances of information and communications technologies (ICTs) have inten- sified interaction between human and artificial moral agents, which has in turn fundamentally altered our concepts of morality and its agency. 21st century moral responsibility is increasingly distributed across human and artificial agents. In our 'always onlife' world, all actions can be combined into good or evil results without human review or recourse. The inclusion of artificial moral agents problematizes the assumption of traditional ethics that agency (and therefore, accountability) is either individual or social. In artificial agents, we witness the re-ontologization of both the infosphere and the ecosphere. Artificial intelligence is a form of re-ontologized signification that may be said to influence or even pre-determine human moral decision-making. Artificial agents may perform actions that have moral consequences, but can we hold them accountable for these consequences? What does that even mean

Burnett, Gary

Burnett, Kathleen

English

Illinois Digital Environment for Access to Learning and Scholarship Repository

Information Domains and the Analysis of Distributed Morality in “Always Onlife” Information Societies Kathleen Burnett1 and Gary Burnett1 1Florida State University kburnett@fsu.edu Abstract. We ask whether the three domains proposed in Information Domains (individual, social, and signification) can provide a useful framework for analyz-ing distributed morality (DM) and its potential consequences. DM is present when moral responsibility is distributed across human and artificial agents. The affordances of information and communications technologies (ICTs) have inten-sified interaction between human and artificial moral agents, which has in turn fundamentally altered our concepts of morality and its agency. 21st century moral responsibility is increasingly distributed across human and artificial agents. In our “always onlife” world [1], all actions can be combined into good or evil re-sults without human review or recourse. The inclusion of artificial moral agents problematizes the assumption of traditional ethics that agency (and therefore, ac-countability) is either individual or social. In artificial agents, we witness the re-ontologization of both the infosphere and the ecosphere [1, 2].  Artificial intelligence is a form of re-ontologized signification that may be said to influence or even pre-determine human moral decision-making. Artificial agents may perform actions that have moral consequences, but can we hold them accountable for these consequences? What does that even mean? Keywords: Information Domains, Information Ethics, Distributed Morality. 1  Introduction 1.1 Statement of Purpose We propose to initiate a conversation about whether analysis of distributed morality (DM) using the Information Domains framework contributes to better understanding of how artificial agents function in our “always onlife” society.  “Onlife” is a neologism coined by Luciano Floridi as early as 2012, and refers to the point in time after which it no longer makes sense to talk about human activity taking place “online” or  “offline.” The poster introduces the Information Domains framework and invites conference attendees to explore and assess its potential for enriching our understanding of how the inclusion of artificial agents in moral decision-making affects distributed morality. Floridi [3] describes DM as the moral consequences of increas-ingly intensive interaction between human and artificial moral agents. The introduction of artificial intelligence among the affordances of ICTs has fundamentally altered moral   agency in the 21st century.  The presence of artificial intelligence problematizes the assumptions of traditional ethics that moral agency is fundamentally human, and that moral responsibility is either individual or social.    1.2 Research Question & Method We ask whether the three domains proposed in the Information Domains framework—individual, social, and signification—can provide a useful framework for the analysis of distributed morality (DM) and its potential consequences. The framework has previ-ously been applied successfully to the exploration of the ethics of cyberbullying and immigration control, where the digital creates new affordances that influence individual and social behavior through the acceptance and adoption of new forms of signification. The potential effects of the participation of artificial agents and intelligence in “always onlife” information societies was not considered in this earlier application.  2 Information Domains Information Domains is proposed as a framework for understanding how distributed morality changes in our understanding of agency and responsibility, particularly in the context of hyperconnected information societies, where both human and artificial agents may contribute to the moral decision-making. Information domains, first outlined in Burnett, G. [4] draws upon previous work in theory, e.g. [5-7] as well as cultural and philosophical hermeneutics, e.g. [8-11]. It in-cludes three “domains,” outlined below. While the three domains – individual, social, and signification – look back to the history of LIS literature, they also, we argue, have the potential to illuminate current issues in information behavior and information eth-ics.  2.1 Domain of the Individual Within the domain of the individual, three factors play predominant roles: First, each individual perceives the world – as well as their own particular information needs – through their own unique cognitive characteristics, often defined, as in Belkin [12] and Dervin [13] as an anomalous state of knowledge or an information gap; individuals seek information to bridge this gap. Second, individuals experience information needs and the process of information seeking through the filter of their own emotions (see, e.g. Kulthau [14]. And, finally, individuals interact with the world through their own par-ticular physical characteristics, ranging from simple things such as height to more com-plex characteristics often defined as disabilities; for example, specific personal charac-teristics such as blindness or confinement to a wheelchair have direct implications for an individual’s ability to search for, find, and use information.    2.2 Domain of the Social The work of Chatman (e.g. [15-18] and her co-authors [5] turns away from a concep-tualization of the individual as the center of information-related phenomena, emphasiz-ing social factors as the shapers of information behavior within what she called small worlds. However, Chatman relies on an extremely constrained notion of the boundaries around those worlds, arguing that, while individual behaviors are meaningful only within their localized social worlds, such worlds are, themselves, isolated entities al-lowing few, if any influences from external forces into their settings [5].  Melding Chatman’s work with Habermas’ notion of the lifeworld – a culture-wide sum of all available information resources and channels within which both individuals and smaller social worlds are situated—the theory of information worlds [19] proposes that, while individual characteristics play important roles in information behaviors, all information-related activities are also inextricably socially situated; the theory further proposes that worlds are not all small, but exist at a wide variety of scales and sizes, from the absolutely localized (e.g. small families) to the global, and that these many “information worlds” interact with and influence each other in a variety of ways across different types of boundaries. Through social interaction, particular information worlds maintain their own social norms (commonly agreed-upon standards governing accepta-ble forms of observable behavior) and information value (agreed-upon scales for as-sessing the relative importance of different kinds of information and the ways in which such information may be valued).  2.3 Domain of Signification Human users of information, whether conceptualized as individuals or as social groups, do not interact with information as an abstraction, but always as something encoded and communicated in some way via a material system of representation, whether writ-ing, visualization, or some other medium for recording and storing—in a very literal sense, Buckland’s Information as Thing [20].  Information cannot be usefully concep-tualized, sought, retrieved, or used without the mediation of representational practices.  2.4 Entwined Domains These three domains—the individual, the social, and signification— are inextricably intertwined with one another.  Individuals occupy social worlds and interact with one another through the mediation of signification.  Conversely, the domain of the social is the context within which individuals live, exchange information, and engage with each other through signification and representational practices. One implication of this is that information itself is neither static nor disengaged, but is, rather, one component of a complex process of interaction, mediation, and creation of meaning involving all three domains. In particular, information ethics, to which we now turn our attention, is a locus of interaction between individuals and other individ-uals, between individuals and social collectives, and across different social groupings;   signification practices hold the entire process together and makes it work. In what fol-lows, we examine two issues related to information ethics, informed by the three infor-mation domains. 3 Information Ethics and Distributed Morality 3.1 Information Ethics Information ethics explores the relationship between the creation, organization, dissem-ination, and use of information, and the ethical standards and moral codes governing human conduct. In the past we have used technologies to facilitate and empower our individual information behaviors, operating from the assumption that technology is eth-ically neutral, and is always human-directed. Recent experience suggests that this as-sumption is no longer viable. Who is responsible when a trolling bot bullies a vulnera-ble individual? What recourse does the vulnerable individual have against this virtually-instantiated terrorization? In the context of a social media platform, how do we distin-guish the actions of an artificial intelligence from those of a human participant? Is this even possible, and ultimately, does it even matter? A human is terrorized either way.   3.2 Distributed Morality (DM) According to Floridi [3], one of the unexpected consequences of living “always onlife” is that morality is inevitably and unavoidably distributed across human and artificial agents.  “ICTs are a most influential empowering factor behind the emergence of DM, working as powerful moral enablers …” [3], p. 270.  Traditional ethics theories assign moral responsibility to human individuals or groups. Lay ethics sometimes assigns re-sponsibility to animals, but rarely to objects.  What happens when objects are repurposed to represent (or signify) agents from the individual and social domains, and are imbued with intelligence? These objects, or ar-tificial agents, act within these domains. Even if we assume that they are incapable of moral decision-making, their actions may have moral consequences.   3.3 The Amazon Case Amazon announced in 2018 that they were abandoning the use of adaptive artificial intelligence in screening job applications. According to a Reuter’s Business News story [21], a team at Amazon had begun building computer programs in 2014 with the aim of achieving gender-neutral hiring practices, using AI to rate candidates using a rating system similar to the one used by Amazon shoppers to rate products. Within a year, they realized that the resulting ratings were far from  gender-neutral; in fact, the AI was penalizing candidates who had attended women’s colleges or participated in women’s clubs or sports. In other words, it discerned differences between the candidates’ re-sumes and those contained in the training database, and interpreted these differences as signifying negative values.  Three years of retraining brought little improvement, and Amazon scrapped the project.     The team began with the assumption that an AI would provide unbiased analyses of the candidates’ resumes, but  found that it was easier to teach an AI human bias than moral discernment. Artificial intelligence is a new form of signification about which we still have a lot to learn.  As we are learning, we need to monitor its interactions and their affects across the individual and social domains.  While it is clear that AI screening did not contribute to Amazon reaching its goal of gender equity, it is unclear whether there was potential for even greater harm. At the individual level, resumes of some of the most qualified candidates would never have reached recruiters, and many qualified female candidates would have been excluded from the hiring process and even from the opportunity to earn incomes and fulfill their potential in the industry; some may have been diverted to jobs in entirely different areas of the economy.  They may have been excluded from participating in the development of products that might have helped other women to succeed, and therefore, have been denied a sense of fulfilment that they might otherwise achieved. In other words, deci-sions rooted entirely in automating the domain of signification had real impact on indi-vidual lives. There would likely be significant consequences in the domain of the social. Gender equity at Amazon would have remained an unattainable goal, but, more broadly, the underrepresentation of women in IT in the U.S. would not have improved, and the rea-sons for their underemployment might be further obscured.  The lack of participation by women in the company and the industry as a whole might affect gender equity in product availability as well as employment. This would reinforce existing barriers to women’s participation in IT and in advanced information societies more broadly; AI, as a tool of signification, would have significant impact on both the lives of individuals and on the social domain as a whole.   4 Invitation to Participate The goal of this poster is to start a conversation about whether the Information Domains framework can be applied to the analysis of how the incorporation of artificial agents into the infosphere may affect our “always onlife” information society. Here are some questions to get us started:  1. Individual Domain: What impacts do you see in your own life from the incorporation of artificial agents in our “always onlife” information soci-ety?  2. Social Domain: What about the ways that you interact with others in social groups and organizations? Has that changed? Are artificial agents a part of that change? 3. Signification Domain: Is there something fundamentally different about AI? Does it change the way we interact? Is an artificial agent capable of moral discernment? If no, what does it mean to interact with an amoral agent? If yes, can we trust artificial agents to make such decisions?    References 1. Floridi, L.: Digital’s Cleaving Power and Its Consequences. Philosophy & Technol-ogy,30(2), 123-129 (2017). 2. Floridi, L.: The Fourth revolution—How the Infosphere is Reshaping Human Reality. Ox-ford: Oxford University Press (2014). 3. Floridi, L.: The Ethics of Information. Oxford: Oxford University Press (2013). 4. Burnett, G.: Information Worlds and Interpretive Practices: Toward an Integration of Do-mains. Journal of Information Science, Theory and Practice, 3(3): 6-16 (2015). 5. Burnett, G., Besant, M., & Chatman, E.A.: Small worlds: Normative behavior in virtual communities and feminist bookselling. Journal of the American Society for Information Sci-ence & Technology, 52(7), 536-547 (2001). 6. Burnett, G., & Jaeger, P.: Small worlds, lifeworlds, and information: The ramifications of the information behaviors of social groups in public policy and the public sphere. Infor-mation Research, 13(2), n.p. Retrieved August 12, 2015, from http://informationr.net/ir/13-2/paper346.html (2008). 7. Burnett, G., Jaeger, P. T., & Thompson, K. M.: Normative behavior and information: The social aspects of information access. Library & Information Science Research (07408188), 30(1), 56-66 (2008). 8. Burnett, G.: The scattered members of an invisible republic: Virtual communities and Paul Ricoeur’s Hermeneutics. Library Quarterly, 72(2), 155-178 (2002). 9. Burnett, G., Dickey, Kazmer, & Chudoba: Burnett, G., Dickey, M., Kazmer, M., & Chudoba, K.: Inscription and interpretation of text: A cultural hermeneutic examination of virtual community. Information Research, 9(1), n.p. Retrieved August 12, 2015, from http://informationr.net/ir/9-1/paper162.html (2003). 10. Dickey, M. H., Burnett, G., Chudoba, K. M., & Kazmer, M. M.: Do you read me? Perspec-tive making and perspective taking in call center chat communications. Journal of the Asso-ciation of Information Systems, 8(1), 547-70 (2007). 11. Burnett, G., Whetstone, M., & Jaeger, P. T.: Personal health record interfaces: A hermeneu-tic analysis. First Monday, 18(8), n.p. Retrieved August 12, 2015, from http://firstmonday.org/ojs/index.php/fm/article/view/4748 (2013). 12. Belkin, N.J.: Anomalous states of knowledge as a basis for information retrieval. The Cana-dian Journal of Information Science, 5, 133-143 (1980). 13. Dervin, B.: From the mind’s eye of the user: The sense-making qualitative-quantitative methodology. In J. Glazier & R.R. Powell (Eds.), Qualitative research in information man-agement (pp. 61-84). Englewood, CA: Libraries Unlimited (1992). 14. Kuhlthau, C.: Inside the search process: Information seeking from the user’s perspective. Journal of the American Society for Information Science, 42(5), 361-71 (1991). 15. Chatman, E. A.:  Life in a small world: Applicability of gratification theory to information-seeking behavior. Journal of the American Society for Information Science, 42, 438-449  (1991). 16. Chatman, E. A.: The information world of retired women. Westport, CT: Greenwood Press  (1992). 17. Chatman, E. A.: A theory of life in the round. Journal of the American Society for Infor-mation Science, 50, 207-217  (1999). 18. Chatman, E. A. Framing social life in theory and research. The New Review of Information Behaviour Research, 1, 3-17 (2000). 19. Jaeger, P. T., & Burnett, G.: Information Worlds: Social context, technology, & information behavior in the age of the Internet. New York: Routledge (2010).   20. Buckland, M.K.: Information as thing. Journal of the American Society for Information Sci-ence, 42, 351-360 (1991). 21. Dastin, J.: Amazon Scraps Secret AI Recruiting tool that Showed Bias Against Women, San Francisco: Reuters Business News, October 9 (2010).   

Information domains and the analysis of distributed morality in "always onlife" information societies

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Information domains and the analysis of distributed morality in "always onlife" information societies

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