Dr Ashwini Datt, Faculty of Medical and Health Sciences, University of Auckland

The proliferation of AI is undeniable, leading to concerns on the relevance of higher education qualifications and questions on the outcomes of formal learning processes in the future. There is also some scepticism that AI’s impact on higher education is overhyped.

To use discretion in the contemporary design of learning and to assess appropriately, we as educators need to be aware of what AI is (technically) and its implications on education and employment in general. Are we ready to adapt to integrate AI in our practice? How do we build such capacity? Given that not all of us have a background in information technology or computing, there will always be a gap in how well we understand AI as a technology and/or a pedagogical tool for designing learning experiences. With the fast pace of developments in the generative AI space, we need to be proactive. Can networks play a role in bridging this gap and helping us build awareness of AI and develop knowledge and skills to appropriately integrate it in teaching and learning in higher education?

Recently I published a mixed-methods study on the value of networking to develop capacity for teaching with technologies. All participants, despite coming from 23 different countries, leveraged networks in some form to build awareness, knowledge and skills to teach with technologies. They created value by actively connecting for on-going interaction, exchange of information and building of lasting professional collaborations, or passively accessing and benefitting from collective wisdom in the network. It is appropriate to then consider AI as the technology within the context of the study.

Active and passive roles, a convenient dichotomy of Poster and Lurker represented extensively in literature, do not represent the whole range of roles participants play in networks. By analysing their agency and type of accumulated capital (value created) in networks, I proposed the Lurker-Seeker-Leader roles. Some networkers choose to ‘lurk’ behind the scenes, observe and build awareness of good practice. They might not necessarily be passive but be active observers waiting for the right context to have the confidence to actively contribute than just observe. How many of us assume this role amidst all the noise on AI in higher education. Are you perhaps reflecting on what it means to be a digital citizen in the age of AI, hence only confident enough to lurk for now? Do you feel out of your depth in understanding the technical aspects of AI?

You could also be seeking answers on identity, citizenship, ethics, pedagogy and/or the role of higher education in general. To seek, means to be an active agent in networks, albeit aware of the limitations of networks, requiring some reflection on the information you access to answer questions or solve problems. You need to engage with like-minded people but also seek new ideas for critical engagement. Having the space and time to connect is important but do you feel that AI developments are occurring at such a pace that it is impossible to keep up? Seekers play an integral role in networks as they look for credibility and reputation in experts for an opportunity to connect, critique and create value over a long-term. You can seek to influence on-going development of AI to suit your context.

Leaders are change agents, creating solutions to problems posed by AI but they work within the constraints of their organisations or institutions. Sometimes the incentives to create change are hard to come by. Leaders in the field of AI in higher education might be keen to provide service to society (developing AI literacy), build a reputation (adaptive platforms suited to use in higher education akin to social tools being used in educational contexts). To lead in AI circles is not only to disseminate knowledge but also actively critique the practices like pedagogical change to integrate AI in teaching and learning. Constraints could be technological/computing capability and resourcing, funds to invest in research and development.

Be a lurker, seeker or leader, an important thing to remember is that we can collectively build the capacity to reflect on and critique the developments in AI to ensure equal representation, equity in participation and appropriate pedagogical integration. We can transition between lurker, seeker and leader for these reasons and need to engage in different ways to experience the full range of learning in networks. Ultimately, we have the agency to steer our own way.