Ethical Living with Algorithms Extended abstract Trifuljesko Sonja1[] and Ruckenstein Minna 1[0000-0002-7600-1419] University of Helsinki sonja.trifuljesko@helsinki.fi, minna.ruckenstein@helsinki.fi The last several years have seen an intensification of discussions on the ethical aspects of algorithms and artificial intelligence (AI) more generally. The heightened focus on the ‘AI Ethics’ is a consequence of the fact that AI has started to appear in public dis- course as a powerful force shaping people’s lives. The term ‘AI’ is used in the debate loosely, to refer to algorithmic technologies that rely on data and encoded assumptions to identify patterns in a given domain or a topic area, in order to make it comprehensi- ble. Recently, various organizations and initiatives have produced a torrent of ethical statements. Among these, the core principles of bioethics (beneficence, non-malefi- cence, autonomy and justice) remain prominent. In addition, the principle of explica- bility, incorporating intelligibility and accountability, is introduced as a response to the overarching concern of the traceability of algorithmic operations (Floridi et al. 2018; Mittelstadt et al. 2016). At the same time, calls for moving ‘from principles to practices’ are becoming more frequent. Such a step entails the development of methods and tools for the ‘applied AI ethics’. These are supposed to prompt engineers of algorithmic sys- tems to reflect on the impacts of their solutions on the ‘end users’, and on the ways in which those impacts could be mitigated by certain design decisions at different stages of development. The success of such tools is, nevertheless, premised on the increased coordination between various stakeholders, coming both from within and outside of developer communities (Morley et al. 2019). Unsurprisingly, the ‘AI Ethics’ debate has been critiqued extensively by social sci- entists. The approach is said to reduce ethics to a technical or design issue while keeping the status quo of current business practices (Greene, Hoffman and Stark 2018). The lack of legal regulation has generated talk of ‘ethics washing’, referring to the fact that while companies exercise self-regulation, they can define how they implement ethical principles (Wagner 2018). This has led to a call for abandoning the discussion on AI ethics altogether and instead concentrating on questions of social inequalities and social justice (Sloane 2019). Calls for disrupting a debate by ending it can be seen as a form of ‘fearless speech’: no attempts for further dialogue are left open (Englund 2018). To engage with the ethics debate in a more productive manner, we propose an approach to algorithmic systems and AI as ‘matters of care’ (Puig de la Bellacasa 2011; 2017). Care involves ‘everything we do to maintain, continue, and repair ‘the world’ so that we can live in it as well as possible’ (Tronto 1993, p. 103). This means that care includes all those (devalued) ‘pro- ductive doings that support liveable relationalities’ (Puig de la Bellacasa 2011, p. 93). Caring entails not only ‘assembling concerns’ (Latour 2005), but also addressing those Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 71 not assembled, as well as adding new layers of concerns (Puig de la Bellacasa 2011; 2017). Thus, care, focusing on doings and relationalities, is situated at the core of the social scientific interest in exclusion and power dynamics. To demonstrate what the move towards care and caring in the AI ethics debate might mean, we discuss one possible way to promote it. After completing the Algo- rithmWatch report, Finland section (Ruckenstein and Velkova 2019), we used the em- pirical cases described in the report as a conversation opener in three workshops. With this move, we acknowledged the openness of ethical and political questions concerning algorithmic systems and opened a space for critical reflection. We learned that the neg- ative reactions concerning automated decision making were mainly focused on citizen monitoring and its imagined consequences. For instance, the piloting of the uses of data analytics in the public sector, with the aim of predicting future child service needs, provoked fears about a deepening surveillance society and algorithmic control. Thus, with the move to care, we can intensify the awareness of how technologies shape the imaginaries of everyday lives. It prompts us to acknowledge that we live interde- pendently with algorithmic systems rather than separated from them. In doing so, we can expand the discussion from the focus on ethical algorithms to ethical living with algorithms. Our workshop participants did not care about the specifics of algorithms, but they cared deeply about the consequences of AI for their everyday lives and future interactions as citizens. The lens offered by care is, hence, suited for exploring human-technology relations, but also for caring for them. In line with this, attention to care expands the debate on AI ethics to issues currently excluded and neglected, involving maintaining and repair- ing our shared life with algorithms. A credit scoring controversy, discussed in the Al- gorithmWatch report, underlines both citizens’ and ombudsman’s role in resourcefully using existing legal and political tools to combat harms generated by algorithmic sys- tems. This brings to the fore that harms caused by algorithms can and need to be re- paired. Care introduces into the ethics discussion the erased human involvements with technologies, from production, implementation and maintenance, to repair (Suchman 2007). Care is a starting point for exploring the complexities of AI ethics by re-estab- lishing the human as a critical and creative actor, deeply interwoven with current tech- nological arrangements. If we aim for an ethical life with algorithms, we need to know the consequences of AI systems intimately, as well as work with those systems, and shape them. References 1. Englund, H. (2018). The front line of free speech: Beyond parrhêsia in Finland’s migrant debate. American Ethnologist, 45(1), 100-111. doi:10.1111/amet.12602 2. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., and Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. 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