Abstract
The task of this essay is to respond to the question concerning robots and responsibility—to answer for the way that we understand, debate, and decide who or what is able to answer for decisions and actions undertaken by increasingly interactive, autonomous, and sociable mechanisms. The analysis proceeds through three steps or movements. (1) It begins by critically examining the instrumental theory of technology, which determines the way one typically deals with and responds to the question of responsibility when it involves technology. (2) It then considers three instances where recent innovations in robotics challenge this standard operating procedure by opening gaps in the usual way of assigning responsibility. The innovations considered in this section include: autonomous technology, machine learning, and social robots. (3) The essay concludes by evaluating the three different responses—instrumentalism 2.0, machine ethics, and hybrid responsibility—that have been made in face of these difficulties in an effort to map out the opportunities and challenges of and for responsible robotics.
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Notes
This effort is informed by and consistent with the overall purpose and aim of philosophy, strictly speaking. Philosophers as different (and, at times, even antagonistic, especially to each other) as Heidegger (1962), Dennett (1996), Moore (2005), and Žižek (2006), have all, at one time or another, described philosophy as a critical endeavor that is more interested in developing questions than in providing definitive answers. “There are,” as Žižek (2006, p. 137) describes it, “not only true or false solutions, there are also false questions. The task of philosophy is not to provide answers or solutions, but to submit to critical analysis the questions themselves, to make us see how the very way we perceive a problem is an obstacle to its solution.” This is the task and objective of the essay—to identify the range of questions regarding responsibility that can and should be asked in the face of recent technological innovation. If, in the end, readers emerge from the experience with more questions—“more” not only in quantity but also (and more importantly) in terms of the quality of inquiry—then it will have been successful and achieved its end.
Because of the recent proliferation of and popularity surrounding connectionist architecture, neural networks, and machine learning, there are numerous examples from which one could select, including natural language generation (NLG) algorithms, black box trading, computational creativity, self-driving vehicles, and autonomous weapons. In fact, one might have expected this essay to have focused on the latter—autonomous weapons—mainly because of the way the responsibility gap, or what has also been called “the accountability gap,” has been positioned, addressed, and documented in the literature on this subject (Arkin 2009; Asaro 2012; Beard 2014; Hammond 2015; Krishnan 2009; Lokhorst and van den Hoven 2012; Schulzke 2013; Sharkey 2012; Sparrow 2007; Sullins 2010). I have, however, made the deliberate decision to employ other, perhaps more mundane, examples like AlphaGo and Tay.ai. And I have done so for two reasons. First, questions concerning machine autonomy and responsibility, although important for and well-documented in the literature concerning autonomous weapons, is something that is not (and should not be) limited to weapon systems. Recognizing this fact requires that we explicitly identify and consider other domains where these question appear and are relevant—domains where the issues might be less dramatic but no less significant. Second, and more importantly, I wanted to deal with technologies that are actually in operation and not under development. Despite its popularity in investigations of machine agency and responsibility, autonomous weapons are still somewhat speculative and in development. Rather than address what might happen with technologies that could be developed and deployed, I wanted to address what has happened with technologies that are already here and in operation.
Just to be clear, the problem with social robots is not that they are or might be capable of becoming moral subjects. The problem is that they are neither instruments nor moral subjects. They occupy an in-between position that effectively blurs the boundary that had typically separated the one from the other. The problem, then, is not that social robots might achieve moral status equal to or on par with human beings. That remains a topic of and for science fiction. The problem is that social robots complicate the way one decides who has moral status and what does not, which is a more difficult/interesting philosophical question. For more on this subject, see Coeckelbergh (2012), Gunkel (2012), and Floridi (2013).
There is some debate concerning this matter. What Coeckelbergh (2010, p. 236) calls “psychopathy”— e.g. “follow rules but act without fear, compassion, care, and love”—Arkin (2009) celebrates as a considerable improvement in moral processing and decision making. Here is how Sharkey (2012, p. 121) characterizes Arkin’s efforts to develop an “artificial conscience” for robotic soldiers: “It turns out that the plan for this conscience is to create a mathematical decision space consisting of constraints, represented as prohibitions and obligations derived from the laws of war and rules of engagement (Arkin 2009). Essentially this consists of a bunch of complex conditionals (if-then statements)….Arkin believes that a robot could be more ethical than a human because its ethics are strictly programmed into it, and it has no emotional involvement with the action.” For more on this debate and the effect it has on moral consideration, see Gunkel (2012).
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Gunkel, D.J. Mind the gap: responsible robotics and the problem of responsibility. Ethics Inf Technol 22, 307–320 (2020). https://doi.org/10.1007/s10676-017-9428-2
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DOI: https://doi.org/10.1007/s10676-017-9428-2