Thomas Corbin

This case study is designed to help students evaluate ethical boundaries in employment contracts and workplace responsibilities. A job description typically outlines an employee’s primary responsibilities, but it cannot account for every possible task. To address this, the “other duties as assigned” clause in employment contracts allows employers to add responsibilities beyond the listed core duties. This clause ensures flexibility in handling unforeseen or necessary tasks that support the organization’s goals even if not explicitly mentioned in the job description. When such tasks arise, employees are expected to perform these “other duties” as part of their role. However, ethical and legal issues may arise when tasks assigned under the “other duties as assigned” clause are excessively burdensome, unrelated to an employee’s primary responsibilities, or inconsistent with the intent—or a violation of the spirit—of the employment contract. These “other duties” may be perceived as exploitative or abusive, potentially resulting in disputes between employers and employees. The case study under discussion explores an instance in which an employer exceeds these boundaries by regularly assigning tasks that deviate significantly from the intended scope of the employees’ roles. This analysis will highlight the potential for misuse of the “other duties as assigned” clause and its broader implications for both parties.

Generative AI (GenAI) grading and tutoring systems are rapidly entering higher education, promising increased efficiency and personalized learning experiences. We believe this technology should be viewed with caution, particularly in the case of philosophy. In this article, we first outline the nature and purported benefits of these systems. Next, we examine the economic motivations driving their adoption within institutions, such as reducing labor costs. Finally, we argue that these motivations, while compelling to administrators, may fail to consider potential negative consequences. We present six pedagogical reasons to be critical of the widespread implementation of GenAI in education: (1) limitations on teacher efficacy; (2) increased student alienation; (3) the undermining of educators’ duty of care; (4) the outsourcing of core teaching tasks; (5) questions regarding the accuracy and utility of GenAI graders; and (6) the risk of implementing GenAI as a misguided solution to real problems in education.

The essay is facing a legitimacy crisis. With students increasingly able to generate plausible submissions using Generative AI, the essay’s status as a valid instrument of assessment of student learning is under serious threat. Yet, rather than abandoning the essay or turning to superficial fixes, this paper argues that the current disruption offers a chance to reconsider what essays are for as well as the chance to consider what they could be. In this paper, we distinguish between the standardised academic essay of today from the historically contextualised essay. Drawing from the history of ideas, we argue that essays are best understood not as products to be measured against static criteria, but exploratory engagements with thought, shaped by uncertainty, divergence, and the recursive relationship between writer and text. This understanding has long been at odds with how essays are typically assessed and it is this misalignment, not AI alone, that we suggest underpins the current crisis. In response, we propose a set of structural changes to essay assessment design. We propose a holistic approach to assessment which, we suggest, helps show how the essay can be reconfigured as both an educationally meaningful and valid assessment task, fit for an age of AI without being defined by it.

This paper employs Axel Honneth’s recognition theory to interpret ‘quiet quitting’ – the practice of limiting work efforts to contracted requirements – as a strategic response by workers facing misrecognition in their work environment. Honneth argues that misrecognition in any one of three social spheres (the family, political society, and the workplace) constitutes disrespect and causes psychological harm. While Honneth contends that experiences of disrespect tend to motivate collective “struggles for recognition,” we suggest that quiet quitters present an alternative response to disrespect, individually seeking recognition in other social spheres rather than engaging in collective action. Further, we draw on Honneth to suggest that the contemporary “entrepreneurial” work ethic – the widespread expectation that workers invest emotionally in their work role – can in practice undermine workplace recognition, contributing to quiet quitters’ compensatory emphasis on recognitive relations outside of work. This recognition-theoretical approach extends current discussions around quiet quitting and yields valuable insights for management theory and practice regarding the critical role of genuine employee recognition in promoting individual well-being and meaningful work experiences.

A significant theory of corporate social responsibility is the Stakeholder Model. Within this model, entities make decisions that impact all stakeholders. Occasionally, the decision that is made ultimately impacts one stakeholder differently than another. Negative data by its very definition is seen as problematic for any organization as it pertains to its stakeholders. When confronted with the data or the potential of the data being negative to desired outcomes or directions of programs, an organization’s leadership may be faced with an ethical conundrum. Should the data be included and shown to all stakeholders? Or should the data be buried and avoided even to the point of engaging in questionable conduct in the management of paperwork and record keeping?

This review seeks to present a comprehensive picture of recent discussions in the social sciences of the anticipated impact of AI on the world of work. Issues covered include: technological unemployment, algorithmic management, platform work and the politics of AI work. The review identifies the major disciplinary and methodological perspectives on AI’s impact on work, and the obstacles they face in making predictions. Two parameters influencing the development and deployment of AI in the economy are highlighted: the capitalist imperative and nationalistic pressures.

Often conflicts arises between stakeholders of a firm. Instances where one stakeholder’s needs conflict with the rights of other stakeholders can put managers in a precarious situation. Strict adherence to contract rules, for example, may be the absolute right of the firm but at the same time enforcement of that contractual right or rule may be unduly damaging to another stakeholder. Managers in these situations may seek to find a balancing act between the two conflicting sides in order to maintain the balance that prioritizes the competing and conflicting responsibilities. The following case study, based on an actual managerial decision in an industrial setting, seeks to bring the lessons of balancing competing interests into harmony, as best as possible, in order to pursue the survival and success of the enterprise while realizing that all stakeholders are vital to the said success and survival.

This case study attempts to frame the ethical considerations between hiring a known smoker over a non-smoker in today’s cultural climate. Referenced data from a parallel project gauging the likelihood of Human Resources representatives to hire smokers and accommodate them in the workforce could help manage the response and critical thinking components of the case scenario. Questions also arise as to whether it is advisable for employers to take particular attitudes toward smoking in the workplace. This is not only in the interest of the health of employees, customers and clients, but is also on the basis of a concern that employers may otherwise expose themselves to lawsuits where employees may, on the basis of illness contracted due to a smoking environment supported by an employer, sue for the costs of care and income.