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In this paper, we utilize duoethnography -- a research method in which practitioners discursively interrogate the relationships between culture, context, and the mechanisms which shape individual autobiographical experiences -- to explore what may be beyond ethics in the context of data science. Although ethical frameworks have the ability to reflect cultural priorities, a singular view of ethics, as we explore, often fails to speak to the multiple and diverse priorities held both within and across institutional spaces. To that end, this paper explores multiple perspectives, epistemologies, and worldviews that can collectively push researchers towards considerations of a data science education that is equity-minded both in concept and practice. Through a set of dialogues which examine our positionalities, journeys, ethics, local cultures, and accountabilities, this paper explores the contextual realities rooted in the authors' educational settings. These conversations focus on the humanity of our students, the communities from which we come from and serve, as well as the unintentional harms and possibilities associated with the development of data science programs across institutional types. We take a set of five core questions to examine how we made, and continue to make, sense of our diverse cultural perspectives on data science education and equity with/in relation to others' realities. Broadly, this paper seeks to offer reflections on the related but differing functions of ethics and equity in data science education. [ABSTRACT FROM AUTHOR]

Almost exactly fifty years ago, Friedrich Kambartel, in his classic essay "Ethics and Mathematics," did pioneering work in an intellectual environment that almost self-evidently assumed a strict separation of the two fields. In our first section we summarize and discuss that classical paper. The following two sections are devoted to complement and contrast Kambartel's picture. In particular, the second section is devoted to ethical aspects of the indirect and direct mathematization of modern societies. The final section gives a short categorization of various philosophical positions with respect to the rationality of ethics and the mutual relation between ethics and mathematics. [ABSTRACT FROM AUTHOR]

When our students enter the workforce, be it in academia or in business, industry, government, they will be forced to make decisions about various ethical dilemmas. Once in a while, the scandalous stories like that of Enron, the three German auto-makers' diesel fuel pact, and the Equifax data breach make the headlines. However, employees at every workplace are faced with small to large-scale ethical situations almost daily. In our majors' future careers, a manager can be using an inappropriate graphic to display data to make the numbers look better, or the data collection processes used in a large public policy project can be completely skewed to support one conclusion that the client desires vs. another more reasonable conclusion. How well are our students prepared for dealing with these dilemmas? Can they even recognize an ethical dilemma? Do we provide them with the tools to be more vigilant about these situations and to make the appropriate decisions when the difficult choices have to be made? In this paper, I would like to invite us all to think about possible ways we can incorporate ethical decision making frameworks and case studies into our classes, particularly if our university does not have an ethics requirement for all majors. Even if there is a general ethics requirement, it is especially important for our students to be exposed to scenarios that are more relevant to the use of mathematics in the workforce since a general ethics course will not necessarily prepare them well for identifying subtle abuses of data processing and mathematical modeling. [ABSTRACT FROM AUTHOR]

Following the summer 2020 civil rights movement and increasing attention to the intersections of mathematics with politics and power, many math educators have reported a desire to implement an antiracist pedagogy and to examine the intersections of their subject with issues of equity, inclusion, and social justice. Many resources exist for K-12 math educators interested in incorporating social justice into their curricula, but resources are comparatively scarce for college and university instructors (though this is changing quickly!). We discuss why one may want to teach mathematics for social justice, how to begin to implement issues of social justice into postsecondary math courses, and publicly available social justice materials for postsecondary math courses. [ABSTRACT FROM AUTHOR]

The term "genocide" emerged out of an effort to describe mass atrocities committed in the first half of the 20th century. Despite a convention of the United Nations outlawing genocide as a matter of international law, the problem persists. Some organizations (including the United Nations) are developing indicator frameworks and "early-warning" systems that leverage data science to produce risk assessments of countries where conflict is present. These tools raise questions about responsible data use, specifically regarding the data sources and social biases built into algorithms through their training data. This essay seeks to engage mathematicians in discussing these concerns. [ABSTRACT FROM AUTHOR]

In mathematics class, violence is carried out in some usually not recognized situations. In this article, I share some reflections on the topic inspired by some passages of Totality and Infinity, work of the French-Lithuanian philosopher Emmanuel Levinas (1906-1995). I find violence by the teacher in not promoting students' understanding of mathematics, in a distorted use of rhetoric, and in interrupting an ethical relation. This article analyses situations taken from class activities, focusing on the teacher's presentation of mathematical content and students' interventions. I also propose that the improvement of interventions in mathematics education is possible and suggest theoretical ideas for acting on situations of violence. [ABSTRACT FROM AUTHOR]

Education for concepts such as ethics and societal responsibility that are critical in building robust and applicable mathematical and statistical models do currently exist in isolation but have not been incorporated into the mainstream curricula at the school or university level. This is partially due to the split between fields (such as mathematics, statistics, and computer science) in an educational setting but also the speed with which education is able to keep up with industry and its requirements. I argue that principles and frameworks of socially responsible modelling should begin at school level and that this would mean that ethics and real-life modelling are introduced much earlier than is currently done. Integrating these concepts with philosophical principles of society and ethics would ensure suitable foundations for future modellers and users of technology to build upon. [ABSTRACT FROM AUTHOR]

Erlwanger [18] shook the mathematics education world when he introduced Benny, a student who successfully worked through a behavioristic curriculum. Erlwanger showed how far removed Benny's understanding of mathematics was from expectations. Erlwanger's legacy is the basis for this comparative case study which explores students' actions in the modern, in-class computer-centered emporium classroom. Many striking similarities are found between Pearson's My- MathLabs (MML) and Benny's Individually Prescribed Instruction curriculum. In this case study we meet Barbara, a student who succeeds in MML but shows little understanding of mathematical concepts and demonstrates that the legacy of Benny is his continued appearance in our current students. However, what differentiates Benny and Barbara is more than time; it's the inequities resulting from imposing a pedagogy with well-known problematic characteristics to developmental mathematics students. Most of these developmental students are members of marginalized communities. As such, the social justice and ethical implications of using such a course structure are explored. [ABSTRACT FROM AUTHOR]

This article describes a one-credit class on ethics in mathematics, which met once a week for an hour and discussed topics in cryptography, algorithms, and big data, and the role of mathematics in public life. I offer anecdotal evidence that even a course with relatively little time commitment for both students and faculty can have a significant impact on students' understanding of and interest in ethics in mathematics. I also collect recommendations and resources in the hopes of encouraging others to consider teaching such a course. [ABSTRACT FROM AUTHOR]