Michał Wieczorek

This is a response to "Why the User-Friendliness of AI Undermines Education. Commentary on Wieczorek 2025" by Dekker and Hermans. While I agree with many of the arguments made by the authors and sympathise with the educational vision they want to promote, I point out that the political-economic dimension of generative AI may make it incompatible with the idea of good education and particularly with the idea of "constrained AI" proposed in the commentary. I argue that each passing day brings more evidence that the political economy of generative AI should offer us sufficient grounds for rejecting the technology (in education and beyond).

The use of AI in school settings has received widespread attention in recent years. However, there are many unresolved practical and ethical issues surrounding educational AI. In this paper, we contribute to this ongoing debate by examining how AI affects the role and responsibilities of educators. We argue that educational AI will decrease moral entanglement, and consequently teachers’ sense of responsibility. On the one hand, this makes it questionable whether teachers will willingly assume new duties introduced by AI or whether others are justified in expecting them to do so. On the other, it raises concerns about broader shifts to teachers’ professional and personal values and commitments. Moral entanglement is the idea that one can become entangled with other entities based on relational features of our personal identity and commitments. Applied to teachers and students, this entanglement results in the emergence of certain responsibilities and a willingness to take responsibility, the strength of which will be mediated by the introduction of AI in the classroom. We argue that current mainstream AI tools will reduce the number and depth of teacher-student interactions, increase the distance between teachers and students, and alienate teachers by transforming their role in the classroom. Thus, these technologies will reduce moral entanglement between students, change teachers’ professional roles and teachers and decrease teachers’ sense of responsibility. On this basis, we discuss how the idea of moral entanglement can be used for the evaluation of the impact that instrumentally-minded interventions have on the relational work undertaken in care-centric professions.

Recent advances in artificial intelligence (e.g., machine learning, generative AI) have led to increased interest in its application in educational settings. AI companies hope to revolutionize teaching and learning by tailoring material to the individual needs of students, automating parts of teachers' jobs, or analyzing educational data to optimize the delivery of content. This article outlines the role of imaginaries in shaping concrete practices and understandings of educational AI. By building on an expanded notion of sociotechnical imaginaries, we show, through a review of science-fiction narratives about technology and education, that the imaginaries underlying educational AI are lacking or limited. When imagined, educational tools are most often depicted as systems for the efficient transmission of information. We contend that this poor imaginary affects why, how, and what educational AI systems are developed. As we demonstrate by analyzing the paradigmatic ideas espoused by Salman Khan, educational AI is designed to optimize the acquisition of knowledge and largely ignores other aspects of teaching and learning, such as care, play, or curiosity. We observe that educational AI is not an object of lively philosophical debate—unlike, for example, self-driving cars or autonomous weapons, which are, incidentally, also much more present in the popular imaginary. We conclude by discussing imaginaries of educational AI that would offer an alternative to the dominant paradigm, focusing on Neal Stephenson's The Diamond Age, Kazuo Ishiguro's Klara and The Sun, and Ian McEwan's Machines Like Me. We argue that to develop socially beneficial and desirable educational technologies, we need to look beyond AI as an information system, and we point to three narratives that present alternative imaginaries of educational AI that can allow us to conceptualize new desirable forms of incorporating technology in teaching and learning, as well as point to its limitations.

This paper builds on Dewey’s philosophy of education to argue that AI, at least in its current commercial form, is likely to have a negative impact on democratic education. AI and other digital technologies are currently being touted for their potential to “democratise” education, even if it is not clear what this would entail. Adopting Dewey’s notion of democratic education, I emphasise that education needs to provide children with skills and dispositions necessary for democratic living, experience in communication and cooperation, opportunities to codetermine the shape of democratic institutions and education itself, and equal opportunities to participate in learning. This allows me to show that most of the voices discussing AI and democratisation of education, conceptualise it in a narrow sense, focusing primarily on the technology’s potential to increase access to quality education. Consequently, I develop an analysis that investigates the relationship of educational AI to the four aspects inherent to Dewey’s philosophy. By examining today’s commercial AI tools and focusing primarily on Intelligent Tutoring Systems, the most prominent kind of educational AI today, I argue that their emphasis on individualisation of learning, their narrow focus on the mastery of the curriculum, and the drive to automate teachers’ tasks are obstacles to democratic education. I demonstrate that AI deprives children from opportunities to gain experience in democratic living and acquire communicative and collaborative skills and dispositions, while also habituating them to an environment over which they have little or no control, potentially impacting how they will aproach shared problems as democratic citizens. I accompany my analysis with suggestions how AI could be used to better serve the goals and values of democratic education. I highlight the opportunities for experiential learning introduced through simulations and games, note how learning network orchestration could expose students to a wider variety of worldviews, reflect on the use of AI to augment rather than automate teachers’ work, and suggest public development of educational AI.

This paper discusses the interpersonal dimension of self-tracking technologies from the standpoint of Dewey’s pragmatist ethics. Users of self-tracking routinely exchange data with others, interact through social features embedded in their tools, and form communities focused on the sharing and discussion of data. I employ Dewey’s notion of transaction to discuss how self-quantification impacts users’ perception of others and how it mediates interpersonal relations. In Dewey’s ethics engagement with others is a fundamental part of moral life and individual flourishing can only be achieved in social contexts and through the extension of care towards other people. The ethical ideals and epistemic concepts present in pragmatism allow me to argue that despite claims that self-tracking technologies lead to the formation of communities, pro-social instincts exist prior to the adoption of the devices and self-tracking actually inhibits the formation of mutually uplifting social bonds. In my discussion, I focus on the degree of epistemic distance that makes genuine engagement with others difficult, limits to transactional agency that prohibits users from deciding how they are perceived by others, and the reductive and instrumental nature of interactions embedded in the social features of self-tracking technologies. Moreover, I also analyse some political aspects of community-formation in the context of self-quantification and criticise the ownership structures of data and infrastructure that limit communities’ political agency.

In this article, we address the case of self-tracking as a practice in which two meaningful backgrounds (physical world and technological infrastructure) play an important role as the spatial dimension of human practices. Using a (post)phenomenological approach, we show how quantification multiplies backgrounds, while at the same time generating data about the user. As a result, we can no longer speak of a unified background of human activity, but of multiple dimensions of this background, which, additionally, is perceived as having no pivotal role in the process, often being hidden, situated beyond human consciousness, or taken for granted. Consequently, the phenomenological experience of the background turns into a hermeneutic practice focused on the interpretation of representations and descriptions. By adopting a (post)phenomenological approach, we show the problems and limitations of quantification of human activities occurring in self-tracking and the theoretical problems associated with the scheme of human-technology relations.

In this paper, I discuss the formation of habits with the help of self-tracking technologies. Although devices like Fitbit smart bands come with promises of empowerment through the means of increased control over users’ habits, existing literature does not provide conclusive findings about the validity of such claims. I contribute to the ongoing debate by relying on John Dewey’s pragmatist philosophy and its notion of intelligent habit. I demonstrate that from a pragmatist standpoint, habits that are the most likely to accomplish users’ goals contribute to their flourishing need to be reflective (accompanied by adequate deliberation) and flexible (adaptable to the changing circumstances). On this basis I highlight some ethical-epistemic issues surrounding self-tracking technologies that inhibit the formation of habits desirable from a Deweyan standpoint. These include a lack of reflection on the part of the developers, difficulties for users to deliberate and consciously shape the habits developed by their devices, and dependence upon self-tracking tools that makes it difficult to adapt habits to individual needs and circumstances. I conclude the paper by discussing self-tracking’s general impact on flourishing, as well as placing my arguments in the context of the diversity of self-tracking practices and identifying how users attempt to alleviate the shortcomings of the technology and make it more suitable to their goals and needs.

This paper discusses how John Dewey’s notion of intelligent habit could contribute to technology ethics. For Dewey, intelligent (i.e., desirable) habits are reflective – arising from inquiry into the appropriate courses of action in each situation – and flexible – easily adaptable to the changing circumstances. We should strive to develop intelligent habits as they are the best tools for the achievement of our goals and are necessary for individual and societal flourishing. I argue that Dewey’s notion of intelligent habit makes it possible to identify the impact of technology on users’ identity and self-determination, advocate for the extension of user choice and malleability of technologies, and analyse the connections between the epistemic dimension of technology and users’ ability to flourish.

This dissertation is devoted to the ethical issues arising in connection to self-tracking practices and technologies. Today, various digital devices (such as Fitbit or Apple Watch) and smartphone apps (e.g.,MyFitnessPal) allow users to collect, quantify and analyse information about their behaviour and bodily parameters, typically for the purposes of behaviour change and management. Self-tracking is commonly associated with the promise of translating quantified data into greater knowledge about oneself, as well as greater control over one’s habits and body. Over the course of the dissertation, I identify the normative issues surrounding selftracking by means of a systematic literature review and adapt John Dewey’s ethical theory to apply it to the analysis of the issues that have not yet been adequately analysed in the literature, namely, the impact on the individual and habit formation, the impact on interpersonal relations, and just distribution of benefits and burdens produced through self-tracking. With the help of Dewey’s ethical ideals of inclusive, continuing growing, and democracy (understood as a cooperative and participatory way of life, rather than a political system), I argue that self-tracking 1) has a negative impact on users’ identity and autonomy by manipulating them into behaviours that are not necessarily in line with their sense of self; 2) limits the quality and depth of users’ engagement with others; and 3) allows companies to exert control over users and profit from their data without adequate compensation, and benefits users from privileged groups to a much greater degree than those coming from marginalised backgrounds. The analysis is accompanied by a set of recommendations for users, developers and policymakers that would ensure that self-tracking positively contributes to individual and societal flourishing/wellbeing and operates in line with the ideal of social justice.

Mobile health (mHealth) technologies for self-monitoring health-relevant parameters such as heart frequency, sleeping patterns or exercise regimes aim at fostering healthy behavior change and increasing the individual users to promote and maintain their health. We argue that this aspect of mHealth supports healthism, the increasing shift from institutional responsibility for public health toward individual engagement in maintaining health as well as mitigating health risks. Moreover, this healthist paradigm leads to a shift from understanding health as the absence of illness to regarding health as the performance of certain rituals in order to project healthiness. By drawing from the analogy between healthiness and traditional virtues, we evaluate the promises made by proponents of mHealth technologies for self-monitoring. We argue that the implementation and use of mHealth risk entrenching existing inequalities and, more particularly, tend to exclude populations situated at the losing end of those inequalities from participating in the quasi-virtue of healthiness. Consequently, the implementation and use of mHealth technologies not only present challenges for social justice but also undermine their primary societal goal—to promote public health. Finally, we offer several suggestions on how to realize the potential benefit of mHealth.

This paper analyzes the ethics of social science research employing big data. We begin by highlighting the research gap found on the intersection between big data ethics, SSR and research ethics. We then discuss three aspects of big data SSR which make it warrant special attention from a research ethics angle: the interpretative character of both SSR and big data, complexities of anticipating and managing risks in publication and reuse of big data SSR, and the paucity of regulatory oversight and ethical recommendations on protecting individual subjects as well as societies when conducting big data SSR. Against this backdrop, we propose using David Resnik’s research ethics framework to analyze some of the most pressing ethical issues of big data SSR. Focusing on the principles of honesty, carefulness, openness, efficiency, respect for subjects, and social responsibility, we discuss three clusters of ethical issues: those related to methodological biases and personal prejudices, those connected to risks arising from data availability and reuse, and those leading to individual and social harms. Finally, we advance considerations to observe in developing future ethical guidelines about big data SSR.

This paper presents a literature review on the ethics of self-tracking technologies which are utilized by users to monitor parameters related to their activity and bodily parameters. By examining a total of 65 works extracted through a systematic database search and backwards snowballing, the authors of this review discuss three categories of opportunities and ten categories of concerns currently associated with self-tracking. The former include empowerment and well-being, contribution to health goals, and solidarity. The latter are social harms, privacy and surveillance, ownership control and commodification of data, autonomy, data-facilitated harm, datafication and interpretability of data, negative impact on relation to self and others, shortcomings of design, negative impact on health perception, and regulation and enforcement of rules. The review concludes with a critical analysis of the existing literature and an overview of a future research agenda that could complement the current work on ethics of self-tracking.

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.