Environmental footprint of GenAI – Changing technological future or planet climate? - Vaclav Moravec; Beata Gavurova; Viliam Kovac (Journal of Innovation & Knowledge)
The beginnings of generative artificial intelligence (GenAI), led by Chat Generative Pre-Trained Transformer (ChatGPT), not only change the behaviour of digital media ecosystem users but also increase the energy consumption of enterprises working with GenAI, which presents them with a fundamental challenge in the era of climate change. This study aims to examine the relationships between the selected aspects of the use of GenAI tools and the environmental perception and behaviour of their users to understand the population's current environmental attitudes towards environmental risks and environmental sustainability. The survey was conducted in October 2024 on a sample of 1,268 respondents of the Czech Republic population. To process the data set, a logistic regression analysis, chi-squared test, Akaike information criterion, and Bayesian information criterion are employed. The results show that the more often people use GenAI tools, the more distant they consider the effects of climate change in time. The low frequency of use of ChatGPT may influence a higher willingness to change popular GenAI tools that are not maintained by environmentally friendly data centres. The frequency of ChatGPT use influences individuals’ perception of the importance of climate-change solving. The more frequently the respondents use artificial intelligence (AI) systems, they less perceive climate change as important. The low frequency of ChatGPT usage is associated with lower willingness to change email provider, transfer own data, leave social networks, stop using a favourite streaming platform and stop using a favourite GenAI platform. The respondents’ attitudes show a visible behavioural change. Internal personal motivation and self-confidence in learning, interest in career and self-confidence when using AI, the behavioural aspects, and the cognitive aspects are altered considerably. Based on the outcomes of the population survey, the study concludes that the issue of environmental friendliness of AI tools should become part of AI literacy that could strengthen population's willingness to use more energy-efficient GenAI platforms. The listed challenges are important in the perspective of the latest technological development, as shown by the discussion on the energy and computational demands of the GenAI platform DeepSeek, which is also discussed in the study.