Abstract
Short for “Generative Pre-trained Transformer,” Chat GPT is an of example of generative artificial intelligence (AI) technology that allows users to converse with machines in a natural way. Headlines have touted that AI technologies will be the death of the traditional college essay or how faculty need to AI-proof their assignments, and others say that AI could be great for college essays (Kelley, 2023; Lametti, 2022; Marche, 2022). Currently there is no consensus in higher education on the best approach to generative AI.
Fear about new technology is typical, and innovations such as the calculator, computers, and even virtual communication platforms like Zoom have been met with resistance. Currently, generative AI is already being used in some professions, such as architecture and law in producing documentation and drawings (Purtill, 2023). Online customer service textboxes frequently rely on AI. Given the efficiencies it can provide now, it is virtually certain that its use will expand to other professions as they begin to realize its potential. At the same time, generative AI will become increasingly useful, and cost effective, driving broader and more sophisticated use. On its current trajectory, generative AI will become an essential component of many thinking professions in the foreseeable future (Williams, 2023).
While the balance depends on the individual, the institution and the degree, most students expect higher education will provide them with two broad classes of benefit. The first is better positioning in the job market, including employability and income (Pew Research Center, 2016). The second is an improved mind, including knowledge, skills, and abilities. The advent of a world with generative AI complicates the ability of educators to deliver on both benefits. Some potential educational responses would compromise one for the sake of the other, but it is vital that higher education find ways to retain both.
The higher education system as a whole is poorly positioned to hold back the tide of market forces, while individual institutions and educators are utterly impotent in this regard. Conversely, there is a strong incentive for higher education to surf the wave of generative AI by preparing students to use it in their future work. Pricewaterhouse Coopers predicts that AI could add $15 trillion to global GDP by 2030, but that up to 30% of jobs will be at risk from automation, including AI and robotics, by the mid-2030s. The proportion of jobs potentially at risk expands to 44% for workers with low education (Pricewaterhouse Coopers, 2023). People with skills to automate processes, or to work with generative AI to increase productivity, will be in demand. Apart from being an employable skill, use of generative AI is already providing some job seekers with competitive advantages, including honing cover letters and CVs, and generating lists of interview questions to help job seekers prepare (Torres, 2023).
To be able to fulfil students’ expectation of better prospects in the job market, educators will need to ensure students are equipped to use generative AI, rather than insulate them from it. Universities are already adopting AI to automate answers to commonly asked questions and even using AI tools to review students resumes prior to them talking to career consultants.
The successful adoption of AI and other advanced technologies will require cooperation from multiple stakeholders, especially employers, the public sector, and academia. Employers can work to inform education providers with a clearer sense of the skills that will be needed in the workplace of the future, even as they look to hone these specific skills for their own workforce. To do this, educators musk keep abreast of rapidly evolving workforce trends. Industry partnerships, including both research partnerships and student placements, will be key. Another potential strategy is increasing the rotation of staff between higher education and industry roles. Universities could find it strategic to expand their faculties focused on AI to enable better transdisciplinary teaching and research across many subject areas.
Increasing automation will require large parts of the workforce to be reskilled and upskilled, with governments and businesses working together to achieve this substantial recalibration (Pricewaterhouse Coopers, 2023). This provides universities with a remarkable opportunity to engage with workers at multiple points in their career pathways. To meet demand, universities themselves will need to look for efficiencies, potentially relying on generative AI to assist educators and administrators. Furthermore, AI could be utilized to learn about topics or spark ideas when writing. Tasks which could benefit from increased use of AI in the next decade include those in admissions, grading, and student feedback—indeed, this may already be occurring.
It remains vital that higher education helps students come to know and think about the world. Apart from the discipline of writing itself, processes for teaching critical thinking such as engaging with challenging texts and having robust classroom discussions remain largely unchanged by generative AI. The challenge posed by generative AI is that it diminishes the utility of written assignments for the assessment of critical thinking. Educators will need to use methods other than the standard take home essay. In application-based professions, such as public health, alternatives to the essay are many, and an experiential learning component to ensure students can translate classroom learning into action. A movement towards authentic assessments is already underway within most fields of study, and the disruption of the traditional essay will hasten this trend. Authentic assessments focus on messy, complex real-world situations and their accompanying constraints, and are often developed with stakeholder input.
Generative AI is set to remake the world, not least by changing the way that educated people sell their labor. It is possible that some of the initial academic interest in generative AI is that it challenges a set of skills on which academics pride, and feed, themselves.
Efficiencies aside, as technology democratizes education by making it accessible outside of universities, higher education must retain its three competitive advantages over self-teaching with technology. The first is the human connection that occurs between educators and students and among students themselves. While AI may help with providing feedback on student’s assessments, it seems a to be a stretch (at least for now) to think that AI can create and foster such connections to help students through challenging life events, or even help them to decide on future careers (Felten & Lambert, 2020).
The second is the formation of potentially lifelong professional, and social, networks for students. Building networks and connections can be fostered through technology, such as the professional network LinkedIn, but relies on human interaction.
The third is the guarantee to employers and others of knowledge, skills, and abilities that a degree confers. As generative AI impedes the ability of employers to assess potential employees through written applications, other methods of assessment will become more important (Hunkenschroer & Luetge, 2022). If higher education can meet the challenge of enhancing critical thinking skills and measuring them appropriately, then the educational attainments of applicants will become more important in the job selection process.
Providing students with experiential opportunities allows them to apply the skills they learn in the classroom to the messiness they experience in the field (Morris, 2020). Educational institutions are uniquely poised to teach students how AI can help them to learn more about health problems that populations may face, while still using the critical thinking and problem-solving skills to apply this to real-world situations.
Education has for some decades functioned as the primary way that people from disadvantaged backgrounds could pull themselves up society’s ladder. In many respects, ChatGPT is a relatively benign introduction to generative AI because it is free and open to virtually all students and their educators. The ethical and practical challenges for teaching and assessment will proliferate as this technology evolves, especially as some versions are released that have a cost barrier which only some students and educators can overcome. This will be yet another important advantage to the wealthy, and further solidify inequality, especially as the technology is improved. Educational institutions will need to decide how much they invest in leveling the playing field. The stakes for society and class relations are high.
As AI technology moves forward, so must the ethical considerations for its use. It is imperative to begin the conversations about social responsibility and about the relationship between labor and capital as more categories of labor are outmoded. Other ethical considerations with which academia must wrestle include appropriate and inappropriate uses of this technology, such as potential limits on using generative AI to gather information on people or generate publications (Liebrenz et al., 2023).
Academics are not in a position to prevent students from using generative AI, and need to rapidly adapt. It will be important to learn more about the technology, and keep pace as it evolves. We need to ensure that students understand the use cases and policies that surround AI and the use in the classroom. With work, educators can minimize its genuine disadvantages for assessment while leveraging potential advantages to continue to deliver enhanced critical thinking and employment outcomes for students. Renewing focus on higher education’s three competitive advantages of caring relationships between educators and students, helping students develop networks, and acting as a guarantor of competence to employers, will assist in this goal.
