Rosalie Waelen

The philosophy of AI currently centers around moral themes and ethical concerns. Despite the fact that AI is an interesting and consequential topic for many subdomains of philosophy, it seems that philosophical analyses of AI are taken to be relevant by the wider research community only when they ultimately serve the goal of addressing AI’s ethical and societal implications. Accordingly, philosophers conducting research on AI often seek to develop recommendations for policy-makers and tech-developers, about how to design, govern, and implement AI. Few, however, are advising the average AI-user on how to live. That the omnipresence of AI in contemporary life is radically changing how people relate to their surroundings, to their loved ones, to their jobs and colleagues, and to their own identity and abilities, is not only of ethical and societal importance, it also fundamentally changes the meaning and experience of being human. Therefore, the existential strand of philosophy may aid philosophical research on AI by emphasizing the impact of AI on the human condition, while simultaneously providing AI-users with much-needed guidance in making sense of the new reality they have come to live in. Given the growing ubiquity of AI in everyday life, this essay calls for an existentialist philosophy of AI.

Recent technological developments have given rise to debates about automation and the future of work. These debates touch on concerns about the availability, nature, and meaningfulness of jobs in the present and near future. The aim of this article is to show that Hannah Arendt’s phenomenology of labor, work, and action can improve current debates about automation and the future of work. First of all, an analysis of Arendt’s critique of modern society and the more recent notion of ‘immaterial labor’ demonstrates that we (still) live in a society dominated by labor and consumption. Second, a conceptual distinction between labor, work, and action can add relevant nuances to contemporary debates about automation and the future of work. Third, Arendt’s warning for a society of laborers without labor inspires to add over-consumption to the list of problems arising from automation. Fourth, Arendt’s description of the human condition can give clarity to contemporary worries about automation’s impact on meaning. It is concluded, finally, that a revaluation of work and action can counter the threats associated with the automation of labor.

In recent years, the notion of ‘sustainable AI’ has emerged as a new topic within the wider debate on artificial intelligence (AI). Although sustainability is usually understood as having three dimensions – the environment, society, and the economy – the debate on sustainable AI, so far, is characterized by a narrow focus on the environmental sustainability of AI. In this article, it is argued that the debate on sustainable AI should not only be about AI’s environmental costs, but also incorporate social and economic concerns. More precisely, the article shows that AI’s environmental impact is often connected to important social and economic issues. Through an analysis of existing literature on the sustainability of AI, it is demonstrated that ethical and philosophical arguments about the importance of considering the environmental costs of AI apply just as well to the social and economic dimensions of AI development. The aim of this article is thus to present a broader understanding of sustainable AI; one that includes all three pillars of sustainability and acknowledges the interdependence between AI’s environmental, social and economic costs.

The debate about the impact and desirability of automizing labor is one that emerges alongside every major technological development. In recent years, attention for the potential ethical and social implications of automizing labor increased once again, in response to the successes and promises of artificial intelligence (AI) and other modern technologies. The aim of this article is, first and foremost, to introduce the reader to recent work on the desirability of automizing labor. The article distinguishes two philosophical debates about replacing human jobs with AI systems or robots. The first debate has to do with questions of distributive justice, in light of the prospect of structural technological unemployment. The second debate has to do with questions about the relation between a job and a meaningful life. In addition to sketching these debates, the article highlights environmental concerns regarding automation as a possible future direction for research on the future of work.

Emotion recognition technology uses artificial intelligence to make inferences about a person’s emotions, on the basis of their facial expressions, body language, tone of voice, or other types of input. Underlying such technology are a variety of assumptions about the manifestation, nature, and value of emotions. To assure the quality and desirability of emotion recognition technology, it is important to critically assess the assumptions embedded in the technology. Within philosophy, there is a long tradition of epistemological, ontological, phenomenological, and ethical reflection on the manifestation, nature, and value of emotions. This article draws from this tradition of philosophy of emotions, in order to challenge the assumptions underlying current emotion recognition technology and to promote a more critical engagement with the concept of emotions in the tech-industry.

Computer vision is a subfeld of artifcial intelligence, aimed at making computers see. Computer vision tools enable a system or device to automatically analyze, interpret, and respond to images and videos. Computer vision tasks range from object detection and tracking, to the recognition of people’s faces and emotional states. While the ethics of AI in general has received signifcant attention, and the ethics of facial recognition (a computer vision application) too, little of the AI ethics literature focuses specifcally on the ethics of computer vision. In this chapter, I create an overview of ethical, social, and political issues related to computer vision, using a critical approach. This means that I identify issues in terms of power and evaluate them in function of their impact on the value of autonomy and the normative goal of emancipatory progress. The aim of this chapter is frst and foremost to ofer an overview of potential normative implications of computer vision. Additionally, the chapter functions as an example for the use of a critical approach to AI ethics.

Facial recognition is a promising emerging technology, but it sometimes fails to recognize people adequately. Facial recognition applications have been found to regularly misidentify certain demographics, misinterpret traits like gender, age, beliefs, or emotions, and categorize individuals in ways that do not resonate with their own sense of identity. In this paper, I argue that in each of these cases, the person who has their face analyzed is not merely misidentified or misunderstood, but misrecognized in an ethically relevant sense. Following Charles Taylor’s The Politics of Recognition (1992) and Axel Honneth’s The Struggle for Recognition (1996), I describe how those subjected to facial recognition systems on the one hand struggle to obtain adequate recognition on a universal level, as being equally important to others, and lack recognition for their individual uniqueness, on the other hand. These forms of misrecognition are of ethical concern, because they can harm a person’s identity formation. So, ironically, facial recognition technology can give rise to a struggle for recognition.

AI systems have often been found to contain gender biases. As a result of these gender biases, AI routinely fails to adequately recognize the needs, rights, and accomplishments of women. In this article, we use Axel Honneth’s theory of recognition to argue that AI’s gender biases are not only an ethical problem because they can lead to discrimination, but also because they resemble forms of misrecognition that can hurt women’s self-development and self-worth. Furthermore, we argue that Honneth’s theory of recognition offers a fruitful framework for improving our understanding of the psychological and normative implications of gender bias in modern technologies. Moreover, our Honnethian analysis of gender bias in AI shows that the goal of responsible AI requires us to address these issues not only through technical interventions, but also through a change in how we grant and deny recognition to each other.

The ethics of artificial intelligence is an upcoming field of research that deals with the ethical assessment of emerging AI applications and addresses the new kinds of moral questions that the advent of AI raises. The argument presented in this article is that, even though there exist different approaches and subfields within the ethics of AI, the field resembles a critical theory. Just like a critical theory, the ethics of AI aims to diagnose as well as change society and is fundamentally concerned with human emancipation and empowerment. This is shown through a power analysis that defines the most commonly addressed ethical principles and topics within the field of AI ethics as either to do with relational power or with dispositional power. Moreover, it is concluded that recognizing AI ethics as a critical theory and borrowing insights from the tradition of critical theory can help the field forward.