Learning to Live with Gen-AI

In 2023, in the wake of the launch of ChatGPT, based on GPT-3, we invited contributions on the Topic AI chatbots: threat or opportunity? [1] This elicited a wide range of submissions and resulted in published papers covering many issues including the impact of these technologies on education, code generation, mental health, and qualitative research.

Just over two years later, the impact of Generative AI—Gen-AI—has become an increasingly prominent topic, attracting widespread interest and attention well beyond the confines of academic research and publication. Moreover, the sense of expectation and excitement that accompanied the release and adoption of ChatGPT and other chatbots from late 2023 is now increasingly tempered by concern and uncertainty.

In 2023, Gen-AI was moving through the initial Technology Trigger phase of Gartner’s Hype Cycle, seen as a breakthrough technology generating significant media and general interest. In Gartner’s model, this is followed by the Peak of Inflated Expectations, followed by the Trough of Disillusionment—i.e., a phase in which increasingly grandiose claims about a technology are reassessed, many found wanting, resulting in growing disappointment. The model includes two further phases: the Slope of Enlightenment and the Plateau of Productivity.

According to Gartner, by mid-2025 Gen-AI had moved beyond the Peak of Inflated Expectations into the Trough of Disillusionment. Given the excessive claims made for the technology this was hardly unexpected, but unlike other technological breakthroughs, Gen-AI involves far wider potential ramifications that go well beyond those encompassed by the Hype Cycle model. Gen-AI itself is now seen by some as the precursor to Artificial General intelligence—AGI—systems that can learn, adapt and evolve far beyond the scope and intentions of human developers.

It is likely that some aspects of Gen-AI will emerge from the Trough of Disillusionment into the latter two phases, providing a foundation for enhanced performance and implementation, albeit at the possible expense of human skills, employment prospects, and overall control. Yet the broader picture is less encouraging, and a growing chorus of concern is emerging regarding the possible consequences of further developments.

At one extreme, the most optimistic view holds that the current trend will continue and accelerate to the point where AGI technologies develop in ways that transform fundamental aspects of our lives beyond recognition. This is referred to as ‘The Singularity’, a term coined by Ray Kurzweil who predicts that this will occur by 2045. As he suggests, ‘Ultimately, it will affect everything… We’re going to be able to meet the physical needs of all humans. We’re going to expand our minds and exemplify these artistic qualities that we value’ [2]. In this view, developments in Gen-AI leading to AGI will usher in a utopian age with infinite resources for all, accompanied by biomedical advances that cure or prevent disease and lay the foundation for extreme longevity, or even immortality.

Others, including many who contributed to the development of Gen-AI itself, take a far more pessimistic view. Geoffrey Hinton, often called ‘The Godfather of AI’ and a former vice-president at Google, now warns that AI may ultimately displace humanity. ‘There’s risks that come from people misusing AI, and that’s most of the risks and all of the short-term risks. And then there’s risks that come from AI getting super smart and understanding it doesn’t need us’ [3].

The pessimists may be more firmly grounded in reality than the optimists; however, this perspective has at least contributed to a growing recognition of the risks inherent in Gen-AI and its potential evolution into AGI.

As Editor-in-Chief of Informatics, I am particularly keen to encourage people to ‘think informatically’, fostering an understanding that ‘encompasses the technologies of information and communication as well as the biological, social, linguistic and cultural changes that initiate, accompany and complicate their development’ [4]. In the context of the current and prospective developments arising from Gen-AI, it is hoped that the call for contributions to this new section on ‘Generative AI’ will elicit submissions that encompass not only the various technologies themselves but also the social and economic contexts within which these advances operate.

We therefore invite submissions that engage with one or more of the following questions:

• The development of Gen-AI has been claimed to herald a new era, offering significant benefits through the increasing integration of technology into people’s lives and interactions. Is this likely to be the case, and if so, where are these impacts likely to be most pervasive and effective?
• Is it possible to strike an appropriate balance in the deployment of these technologies so that any potential harms are minimized while benefits are maximized and shared?
• How can the academic community and the wider public be protected against the generation of ‘hallucinations’—i.e., fabrications—by AI? Should researchers be required to submit their data with manuscripts to show that the data are authentic? What is the role of ethics committees in protecting the integrity of research?
• Is Retrieval-Augmented Generation—RAG—a feasible response to the problem of Gen-AI ‘hallucinations’? If so, how can it be more widely incorporated into Gen-AI systems?
• How should educators respond to the challenge posed by Gen-AI? Should they embrace this technology and reorient teaching and learning strategies around it, or seek to safeguard traditional practices from what is seen as a major threat leading to an erosion of critical skills?
• There is a growing body of evidence that the design and implementation of many AI applications, i.e., algorithms, incorporate bias and prejudice. How can this be countered and corrected?
• How can the substantial increases in energy consumption necessitated by Gen-AI be mitigated?
• What is the nature and role of emerging models and algorithms for using Gen-AI in various personalized contexts, e.g., counselling and healthcare?

The potential impact of these technologies on topics covered by Informatics in general and the new section ‘Generative AI’ in particular is twofold: on the one hand, there is a need for research on the technological bases underlying Gen-AI; on the other, there are many aspects of how Gen-AI can challenge, support and assist designers, developers, and practitioners operating across many diverse fields that need to be explored.