Tag: ethics

  • Misinformation Course Teaches Ethics for Engineering Students

    Misinformation Course Teaches Ethics for Engineering Students

    Nearly three in four college students say they have somewhat high or very high media literacy skills (72 percent), according to a 2025 Student Voice survey by Inside Higher Ed and Generation Lab. Students are less likely to consider their peers media literate; three in five respondents said they have at least somewhat high levels of concern about the spread of misinformation among their classmates.

    When asked how colleges and universities could help improve students’ media literacy skills, a majority of Student Voice respondents indicated they want digital resources on increasing media literacy or media literacy–related content and training embedded into the curriculum.

    A recently developed course at the University of Southern California’s Viterbi School of Engineering teaches students information literacy principles to help them develop tools to mitigate the harms of online misinformation.

    The background: USC offers an interdisciplinary teaching grant that incentivizes cross-campus collaboration and innovative teaching practices. To be eligible for the grant, applications must include at least one full-time faculty member and faculty from more than one school or division. Each grantee receives up to $20,000 to compensate for applicants’ time and work.

    In 2023, Helen Choi, a faculty member at USC Viterbi, won the interdisciplinary teaching grant in collaboration with Cari Kaurloto, head of the science and engineering library at USC Libraries, to create a media literacy course specifically for engineering students.

    “By focusing on engineering students, we were able to integrate a component of the course that addresses a social issue from an engineering perspective in terms of technical know-how and the professional ethics,” Choi said, which helps students see the relevance of course content to their personal and professional lives.

    What’s the need: Students tend to receive most of their news and information on online platforms; Student Voice data found a majority of learners rely on social media for news content (72 percent), and about one in four engage with news apps or news aggregator websites (27 percent).

    Choi and Kaurloto’s course, titled Information Literacy: Navigating Digital Misinformation, builds academic research skills, teaches information literacy principles and breaks down the social issue of online misinformation.

    “Students examine ways they can navigate online information using their research skills, and then extend that knowledge by considering how they, as prospective engineers, can build technologies that mitigate the harms of online misinformation while enhancing the information literacy of users,” Choi explained.

    USC faculty aren’t the only ones noticing a need for more education around engagement with digital information; a growing number of colleges and universities are making students complete a digital literacy course as a graduation requirement.

    In the classroom: Choi and Kaurloto co-teach the course, which was first offered in this spring to a class of 25 students.

    The students learned to develop effective search strategies and critically examine sources, as well as ethical engineering principles and how to apply them in designing social media platforms, Kaurloto said. Choi and Kaurloto employed active learning pedagogies to give students hands-on and real-life applications including writing, speaking and collaborative coursework.

    One assignment the students completed was conducting library research to develop a thesis paragraph on an information literacy topic with a short, annotated bibliography. Students also presented their research to their peers, Kaurloto said.

    Learners also engaged in a group digital literacy project, designing a public service campaign that included helpful, research-backed ways to identify misinformation, Choi said. “They then had to launch that campaign on a social media platform, measure its impact, and present on their findings.” Projects ranged from infographics on Reddit to short-form videos on spotting AI-generated misinformation and images on TikTok and Instagram.

    The impact: Student feedback said they found the course helpful, with many upper-level learners saying they wished they had taken it sooner in their academic career because of the library research skills they gained. They also indicated the course content was applicable in daily life, such as when supporting family members “who students say have fallen down a few internet rabbit holes or who tend to believe everything they see online,” Choi said.

    Other librarians have taken note of the course as a model of how to teach information literacy, Choi said.

    “We’ve found that linking information literacy with specific disciplines like engineering can be helpful both in terms of building curricula that resonate with students but also for building professional partnerships among faculty,” Choi said. “Many faculty don’t know that university librarians are also experts in information literacy—but they should!”

    This fall, Choi and Kaurloto plan to offer two sections of the course with a cap of 24 students per section. Choi hopes to see more first- and second-year engineering students in the course so they can apply these principles to their program.

    If your student success program has a unique feature or twist, we’d like to know about it. Click here to submit.

    Source link

  • We Already Have an Ethics Framework for AI (opinion)

    We Already Have an Ethics Framework for AI (opinion)

    For the third time in my career as an academic librarian, we are facing a digital revolution that is radically and rapidly transforming our information ecosystem. The first was when the internet became broadly available by virtue of browsers. The second was the emergence of Web 2.0 with mobile and social media. The third—and current—results from the increasing ubiquity of AI, especially generative AI.

    Once again, I am hearing a combination of fear-based thinking alongside a rhetoric of inevitability and scoldings directed at those critics who are portrayed as “resistant to change” by AI proponents. I wish I were hearing more voices advocating for the benefits of specific uses of AI alongside clearheaded acknowledgment of risks of AI in specific circumstances and an emphasis on risk mitigation. Academics should approach AI as a tool for specific interventions and then assess the ethics of those interventions.

    Caution is warranted. The burden of building trust should be on the AI developers and corporations. While Web 2.0 delivered on its promise of a more interactive, collaborative experience on the web that centered user-generated content, the fulfillment of that promise was not without societal costs.

    In retrospect, Web 2.0 arguably fails to meet the basic standard of beneficence. It is implicated in the global rise of authoritarianism, in the undermining of truth as a value, in promoting both polarization and extremism, in degrading the quality of our attention and thinking, in a growing and serious mental health crisis, and in the spread of an epidemic of loneliness. The information technology sector has earned our deep skepticism. We should do everything in our power to learn from the mistakes of our past and do what we can to prevent similar outcomes in the future.

    We need to develop an ethical framework for assessing uses of new information technology—and specifically AI—that can guide individuals and institutions as they consider employing, promoting and licensing these tools for various functions. There are two main factors about AI that complicate ethical analysis. The first is that an interaction with AI frequently continues past the initial user-AI transaction; information from that transaction can become part of the system’s training set. Secondly, there is often a significant lack of transparency about what the AI model is doing under the surface, making it difficult to assess. We should demand as much transparency as possible from tool providers.

    Academia already has an agreed-upon set of ethical principles and processes for assessing potential interventions. The principles in “The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research” govern our approach to research with humans and can fruitfully be applied if we think of potential uses of AI as interventions. These principles not only benefit academia in making assessments about using AI but also provide a framework for technology developers thinking through their design requirements.

    The Belmont Report articulates three primary ethical principles:

    1. Respect for persons
    2. Beneficence
    3. Justice

    “Respect for persons,” as it’s been translated into U.S. code and practiced by IRBs, has several facets, including autonomy, informed consent and privacy. Autonomy means that individuals should have the power to control their engagement and should not be coerced to engage. Informed consent requires that people should have clear information so that they understand what they are consenting to. Privacy means a person should have control and choice about how their personal information is collected, stored, used and shared.

    Following are some questions we might ask to assess whether a particular AI intervention honors autonomy.

    • Is it obvious to users that they are interacting with AI? This becomes increasingly important as AI is integrated into other tools.
    • Is it obvious when something was generated by AI?
    • Can users control how their information is harvested by AI, or is the only option to not use the tool?
    • Can users access essential services without engaging with AI? If not, that may be coercive.
    • Can users control how information they produce is used by AI? This includes whether their content is used to train AI models.
    • Is there a risk of overreliance, especially if there are design elements that encourage psychological dependency? From an educational perspective, is using an AI tool for a particular purpose likely to prevent users from learning foundational skills so that they become dependent on the model?

    In relation to informed consent, is the information provided about what the model is doing both sufficient and in a form that a person who is neither a lawyer nor a technology developer can understand? It is imperative that users be given information about what data is going to be collected from which sources and what will happen to that data.

    Privacy infringement happens either when someone’s personal data is revealed or used in an unintended way or when information thought private is correctly inferred. When there is sufficient data and computing power, re-identification of research subjects is a danger. Given that “de-identification of data” is one of the most common strategies for risk mitigation in human subjects’ research, and there is an increasing emphasis on publishing data sets for the purposes of research reproducibility, this is an area of ethical concern that demands attention. Privacy emphasizes that individuals should have control over their private information, but how that private information is used should also be assessed in relation to the second major principle—beneficence.

    Beneficence is the general principle that says that the benefits should outweigh the risks of harm and that risks should be mitigated as much as possible. Beneficence should be assessed on multiple levels—both the individual and the systemic. The principle of beneficence demands that we pay particularly careful attention to those who are vulnerable because they lack full autonomy, such as minors.

    Even when making personal decisions, we need to think about potential systemic harms. For example, some vendors offer tools that allow researchers to share their personal information in order to generate highly personalized search results—increasing research efficiency. As the tool builds a picture of the researcher, it will presumably continue to refine results with the goal of not showing things that it does not believe are useful to the researcher. This may benefit the individual researcher. However, on a systemic level, if such practices become ubiquitous, will the boundaries between various discourses harden? Will researchers doing similar scholarship get shown an increasingly narrow view of the world, focused on research and outlooks that are similar to each other, while researchers in a different discourse are shown a separate view of the world? If so, would this disempower interdisciplinary or radically novel research or exacerbate disciplinary confirmation bias? Can such risks be mitigated? We need to develop a habit of thinking about potential impacts beyond the individual in order to create mitigations.

    There are many potential benefits to certain uses of AI. There are real possibilities it can rapidly advance medicine and science—see, for example, the stunning successes of the protein structure database AlphaFold. There are corresponding potentialities for swift advances in technology that can serve the common good, including in our fight against the climate crisis. The potential benefits are transformative, and a good ethical framework should encourage them. The principle of beneficence does not demand that there are no risks, but that we should identify uses where the benefits are significant and that we mitigate the risks, both individual and systemic. Risks can be minimized by improving the tools, such as work to prevent them from hallucinating, propagating toxic or misleading content, or delivering inappropriate advice.

    Questions of beneficence also require attention to environmental impacts of generative AI models. Because the models require vast amounts of computing power and, therefore, electricity, using them taxes our collective infrastructure and contributes to pollution. When analyzing a particular use through the ethical lens of beneficence, we should ask whether the proposed use provides enough likely benefit to justify the environmental harm. Use of AI for trivial purposes arguably fails the test for beneficence.

    The principle of justice demands that the people and populations who bear the risks should also receive the benefits. With AI, there are significant equity concerns. For example, generative AI may be trained on data that includes our biases, both current and historic. Models must be rigorously tested to see if they create prejudicial or misleading content. Similarly, AI tools should be closely interrogated to ensure that they do not work better for some groups than for others. Inequities impact the calculations of beneficence and, depending on the stakes of the use case, could make the use unethical.

    Another consideration in relation to the principle of justice and AI is the issue of fair compensation and attribution. It is important that AI does not undermine creative economies. Additionally, scholars are important content producers, and the academic coin of the realm is citations. Content creators have a right to expect that their work will be used with integrity, will be cited and that they will be remunerated appropriately. As part of autonomy, content creators should also be able to control whether their material is used in a training set, and this should, at least going forward, be part of author negotiations. Similarly, the use of AI tools in research should be cited in the scholarly product; we need to develop standards about what is appropriate to include in methodology sections and citations, and possibly when an AI model should be granted co-authorial status.

    The principles outlined above from the Belmont Report are, I believe, sufficiently flexible to allow for further and rapid developments in the field. Academia has a long history of using them as guidance to make ethical assessments. They give us a shared foundation from which we can ethically promote the use of AI to be of benefit to the world while simultaneously avoiding the types of harms that can poison the promise.

    Gwendolyn Reece is the director of research, teaching and learning at American University’s library and a former chair of American’s institutional review board.

    Source link

  • Mind the policy gaps: regulating quality and ethics in digitalised and privatised crossborder education

    Mind the policy gaps: regulating quality and ethics in digitalised and privatised crossborder education

    by Hans de Wit, Tessa DeLaquil, Ellen Hazelkorn and Hamish Coates

    Hans de Wit, Ellen Hazelkorn and Hamish Coates are editors and Tessa DeLaquil is associate editor of Policy Reviews in Higher Education. This blog is based on their editorial for issue 1, 2025.

    Transnational education (TNE), also referred to as crossborder education, is growing and morphing in all kinds of interesting ways which, while exciting for innovators, surface important policy, regulatory, quality and ethical concerns. It is therefore vital that these developments do not slip around or through policy gaps. This is especially true for on-line TNE which is less visible than traditional campus-based higher education. Thus, it is vital that governments take the necessary actions to regulate and quality assure such education and training expansion and to inform the sector and broader public. Correspondingly, there is a pressing need for more policy research into the massive transformations shaking global higher education.

    TNE and its online variants have been part of international higher education for a few decades. As Coates, Xie, and Hong (2020) foreshadowed, it has seen a rapid increase after the Covid-19 pandemic. In recent years, TNE operations have grown and diversified substantially. Wilkins and Huisman (2025) identify eleven types of TNE providers and propose the following definition to help handle this diversity: ‘Transnational education is a form of education that borrows or transfers elements of one country’s higher education, as well as that country’s culture and values, to another country.’

    International collaboration and networking have never been more important than at this time of geopolitical and geoeconomic disruption and a decline in multilateral mechanisms. But TNE’s expansion is matched by growing risks.

    International student mobility at risk

    International degree student mobility (when students pursue a bachelor, master and/or doctoral degree abroad) continues to be dominant, with over six million students studying abroad, double the number of 10 years ago. It is anticipated that this number will further increase in the coming decade to over 8 million, but its growth is decreasing, and its geographical path from the ‘global south’ to the ‘global north’ is shifting towards a more diverse direction. Geopolitical and nationalist forces as well as concerns about adequate academic services (accommodation in particular) in high-income countries in the global north are recent factors in the slowing down of the growth in student mobility to Australia, North America and Europe, the leading destinations. The increased availability and quality of higher education, primarily at the undergraduate level, in middle-income countries in Asia, Latin America and parts of the Middle East, also shape the decrease in student mobility towards the global north.

    Several ‘sending countries’, for instance, China, South Korea and Turkey, are also becoming receiving countries. Countries like Kazakhstan, Uzbekistan, Ukraine (until the Russian invasion), Egypt and some of the Caribbean countries have also become study destinations for students from neighbouring low-income countries. These countries provide them with higher education and other forms of postsecondary education sometimes in their public sector but mostly in private institutions and by foreign providers.

    An alternative TNE model?

    Given the increased competition for international students and the resulting risks of falling numbers and related financial security for universities, TNE has emerged as an alternative source of revenue. According to Ilieva and Tsiligiris (2023), United Kingdom TNE topped more than 530,000 students in 2021. In the same year, its higher education institutions attracted approximately 680,000 international students. It is likely that TNE will surpass inward student mobility.

     As the United Kingdom case makes clear, TNE originally was primarily a ‘north-south’ phenomenon, in which universities from high-income and mostly Anglophone countries, offered degree programmes through branch campuses, franchise operations and articulation programmes. Asia was the recipient region of most TNE arrangements, followed by the Middle East. As in student mobility, TNE is more diverse globally both in provision and in reception.

    The big trend in TNE is the shift to online education with limited in-person teaching. A (2024) report of Studyportals found over 15,000 English-taught online programmes globally. And although 92 per cent of these programmes are supplied by the four big Anglophone countries – the United Kingdom, United States, Canada and Australia – the number of programmes offered outside those four doubled since 2019 from 623–1212, primarily in Business and Management, Computer Sciences and IT.

    Private higher education institutions

    This global growth in online delivery of education goes hand in hand with the growth in various forms of private higher education. Over 50% of the institutions of higher education and over one-third of global enrolment are in private institutions, many of which are commercial in nature. Private higher education has become the dominant growth area in higher education, as a result of the lack of funding for public higher education as well as traditional HE’s sluggish response to diverse learner needs. Although most private higher education, in particular for-profit, is taking place in the global south, it is also present in high-income countries, and one can see a rise in private higher education recently in Western Europe, for instance, Germany and France.

    TNE is often a commercial activity. It is increasingly a way for public universities to support international and other operations as public funding wanes. Most for-profit private higher education targets particular fields and education services and tends to be more online than in person. There is an array of ownership and institutional structures, involving a range of players.

    Establishing regulations and standards

    TNE, especially online TNE, is likely to become the major form of international delivery of education for local and international students especially where growing demand cannot be met domestically. Growth is also increasingly motivated by an institution’s or country’s financial challenges or strategic priorities – situations that are likely to intensify. This shift could help overcome some of the inequities associated with mobility and address concerns associated with climate change but online TNE is significantly more difficult to regulate.

    A concerning feature of the global TNE market is how learners and countries can easily become victims. Fraud is associated with the exponential rise in the number of fake colleges and accreditors, and document falsification. This is partly due to different conceptions and regulatory approaches to accreditation/QA of TNE and the absence of trustworthy information. Indeed, the deficiency in comprehensive and accessible information is partly responsible for on-going interest in and use of global rankings as a proxy for quality.

    A need for clearer and stronger TNE and online quality assurance

    The trend in growth of private for-profit higher education, TNE and online delivery is clear and given its growing presence requires more policy attention by national, regional and global agencies. As mentioned, public universities are increasingly active in TNE and online education targeting countries and learners underserved in their home countries whilst  looking for other sources of income as a result of decreasing public support and other factors.

    The Global Convention on the Recognition of Qualifications makes clear the importance of ensuring there are no differences in quality or standards between learners in the home or host country regardless of whether the delivery of education programmes and learning activities is undertaken in a formal, non-formal or informal setting, in face-to-face, virtual or hybrid formats, traditional or non-traditional modes. Accordingly, there are growing concerns about insufficient regulation and the multilateral framework covering international education, and especially online TNE.

    In response, there is a need for clearer and stronger accreditation/quality assurance and standards by national regulators, regional networks and organisations such as UNESCO, INQAAHE, the International Association of Universities (IAU) with regards to public and private involvement in TNE, and online education. This is an emerging frontier for tertiary education, and much more research is required on this growing phenomenon.

    Professor Ellen Hazelkorn is Joint Managing Partner, BH Associates. She is Professor Emeritus, Technological University Dublin.

    Hamish Coates is professor of public policy, director of the Higher Education Futures Lab, and global tertiary education expert.

    Hans de Wit is Professor Emeritus and Distinguished Fellow of the Boston College Center for International Higher Education, Senior Fellow of the international Association of Universities.

    Tessa DeLaquil is postdoctoral research fellow at the School of Education at University College Dublin.

    Author: SRHE News Blog

    An international learned society, concerned with supporting research and researchers into Higher Education

    Source link