Rosalie Waelen

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.