Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

Many recent AI policies have been structured under labels that follow a particular trend: national or international guidelines, policies or regulations, such as the EU’s and USA’s ‘Trustworthy AI’ and China’s and India’s adoption of ‘Responsible AI’, use a label that follows the recipe of [agentially loaded notion + ‘AI’]. A result of this branding, even if implicit, is to encourage the application by laypeople of these agentially loaded notions to the AI technologies themselves. Yet, these notions are appropriate only (...) when applied to agents, which current AI technologies are not; and the concern is that this misapplication creates an incentive to inappropriately attribute trustworthiness or responsibility to AI technologies. We endeavour to show that we have good reason to avoid any general AI policy that uses agentially loaded labelling. We suggest labelling these policies not in terms of some qualification of AI, but rather in terms of our approach to the technology and its wider development and use context – focusing on being trustworthy and responsible about AI, rather than on trustworthy or responsible AI. (shrink)

The intention of this paper is to point to the dilemma humanity may face in light of AI advancements. The dilemma is whether to create a world with less evil or maintain the human status of moral agents. This dilemma may arise as a consequence of using automated decision-making systems for high-stakes decisions. The use of automated decision-making bears the risk of eliminating human moral agency and autonomy and reducing humans to mere moral patients. On the other hand, it also (...) has the potential to bring tremendous benefits to humanity by decreasing human-induced harm in the world. After presenting how this dilemma may arise, I explore general avenues for addressing it. I will argue that we do not have to solve this dilemma in an all-or-nothing fashion and that a more nuanced approach may be suitable. However, the main point I want to highlight is that we need to have a principled way of addressing this dilemma, which is currently missing. (shrink)

This paper examines whether machines (algorithms/programs/ AI systems) are apt subjects for praise or blame for some actions or performances. I consider "Move 37" of AlphaGo as a case study. DeepMind’s AlphaGo is an AI algorithm developed to play the game of Go. The AlphaGo utilizes Deep Neural Networks. As AlphaGo is trained through reinforcement learning, the AI algorithm can improve itself over a period of time. Such AI models can go beyond the intended task and perform novel and unpredictable (...) functions. There is a surprise element associated with "Move 37". "Move 37" not only surprises the Go players, the programmers, but also whoever is informed of this unpredicted move. Does someone or something deserve praise or blame for the surprise? If so, who or what deserves the praise or blame for "Move 37"? The programmer cannot be praised for "Move 37", which is either surprising or was not intended or imagined at all. At the same time, would we accept that neither the algorithm deserves praise for the unpredicted move that the algorithm allowed the program to make? From this, would we accept that since neither the programmer nor the algorithm/AI system deserves the praise, there is such a good or exciting move for which no one or nothing could be praised? Would we say this unpredictable move is a move for which no one deserves praise or blame? Wouldn’t there be at least a few who were surprised by the unpredictable move? Should we say that for this pleasant surprise, no one deserves praise? Nonetheless, for us, specifically regarding the particular unpredictable move, we firmly find it counterintuitive to say that there is an exciting move for which no one deserves praise. The surprise element is the result of the property that belongs to the algorithm. It seems quite difficult for us to accept that no one deserves praise for "Move 37" or for similar moves. Therefore, someone or something deserves praise which is a matter of scrutiny. (shrink)