Media and Environment: AI and Autonomous Systems in Data-Based Environmental Research
Today, there is an urgent public request for citizens to engage in and educate themselves about, the societal and ethical effects that artificial intelligence (AI) and autonomous systems produce. In line with this, national and international education policies assert that citizens also need to acquire various skills to successfully adapt to the changes that AI will bring to society. But what political and educational problems are such policy requests in fact a solution to? And what are citizens supposed to learn exactly? What counts as valid knowledge? Who do we need to become in order to survive and thrive in a future when AI and autonomous systems are ubiquitous? This project seeks to empirically investigate how knowledge about AI is construed, represented, and enacted, and which social, political, and epistemic meanings are produced by that knowledge.
This future is, however, not without historical and (media) ecological entanglements. So, it is also urgent that we develop analytical and practical tools that highlight how education about AI, and the imaginaries they contain, can be understood, and reflected upon, in terms of ‘deep’ temporalities and media and environmental history. So, by taking a fundamentally ecological perspective on problematizations (ways that problems and solutions are co-constructed) and epistemic injustice (ways in which certain knowledge is privileged) in international technology-education policies, public science communication, and technological designs, I want to explore how ecological, educational and technological sensibilities can be co-developed, and how we can advance structural justice and ecological survival in relation to AI and education. The purpose is to support the development of critically reflexive and just education (and policies) about an imminent AI future.
Assistant Professor, KTH Royal Institute of Technology