Michał Wieczorek
Biographic Data
| ID | 9030281 |
|---|---|
| NAME | Michał Wieczorek |
| GIVEN NAMES | Michał |
| FAMILY NAME | Wieczorek |
| SIGNATURE | WIECZOREK M |
| AFFILIATIONS | Dublin City University |
| ORCID | 0000-0003-3688-9684 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Beyond data extraction
This paper discusses data governance models for educational platforms that could better protect students’ and teachers’ privacy and reduce data management burdens for teachers and administrators. Within an ethnographic study involving four Swedish secondary schools and municipal- and national-level administrators working with educational technology, we conduct qualitative interviews informed by educational data-tracing activities done with the he…
Teachers’ Busywork, Moral Entanglement, and the Automation of Responsibility
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 ques…
How to Imagine Educational AI
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 practic…
How AI Will Monetize Education
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 com…
Using ethical scenarios to explore the future of artificial intelligence in primary and secondary education
The ethics of educational artificial intelligence (AIED) has become a prominent topic of debate in recent years. However, many prospective AIED tools are still under development and may change before they are widely deployed in schools. Researchers analyzing the prospective ethical impacts of AIED cannot rely on actual use cases and empirical evidence concerning the experiences of teachers and students affected by AI. To address such limitations,…
Community, solidarity and care through data? An ethical analysis of the interpersonal dimension of self-tracking
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 inter…
Why AI will not Democratize Education
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 di…
Self-tracking, background(s) and hermeneutics. A qualitative approach to quantification and datafication of activity
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, bu…
Would John Dewey Wear a Fitbit? A Pragmatist Analysis of Self-Tracking Technologies’ Impact on Habit Formation
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 demonst…
The Good Life after the Narrative Turn
Ethical Issues in Social Science Research Employing Big Data
This paper analyzes the ethics of social science research (SSR) 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: (1) the interpretative character of both SSR and big data, (2) complexities of anticipating and managing risks in publication and re…
The Struggle for AI’s 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 an…
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The Good Life after the Narrative Turn
Ethical Issues in Social Science Research Employing Big Data
This paper analyzes the ethics of social science research (SSR) 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: (1) the interpretative character of both SSR and big data, (2) complexities of anticipating and managing risks in publication and re…
The Struggle for AI’s 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 an…
Self-tracking, background(s) and hermeneutics. A qualitative approach to quantification and datafication of activity
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, bu…
Would John Dewey Wear a Fitbit? A Pragmatist Analysis of Self-Tracking Technologies’ Impact on Habit Formation
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 demonst…
Using ethical scenarios to explore the future of artificial intelligence in primary and secondary education
The ethics of educational artificial intelligence (AIED) has become a prominent topic of debate in recent years. However, many prospective AIED tools are still under development and may change before they are widely deployed in schools. Researchers analyzing the prospective ethical impacts of AIED cannot rely on actual use cases and empirical evidence concerning the experiences of teachers and students affected by AI. To address such limitations,…
Community, solidarity and care through data? An ethical analysis of the interpersonal dimension of self-tracking
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 inter…
Why AI will not Democratize Education
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 di…
Beyond data extraction
This paper discusses data governance models for educational platforms that could better protect students’ and teachers’ privacy and reduce data management burdens for teachers and administrators. Within an ethnographic study involving four Swedish secondary schools and municipal- and national-level administrators working with educational technology, we conduct qualitative interviews informed by educational data-tracing activities done with the he…
Teachers’ Busywork, Moral Entanglement, and the Automation of Responsibility
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 ques…
How to Imagine Educational AI
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 practic…
How AI Will Monetize Education
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 com…
Ethics and Social Impacts of AI (8 works) · Sociology (8 works) · Psychology (7 works) · Computer Science (4 works) · Digital Education and Society (4 works) · Engineering (4 works) · Engineering ethics (4 works) · Epistemology (4 works) · Philosophy (4 works) · Philosophy of science (4 works)