From the mechanics of consciousness to the consciousness of machines. Seven approaches to ‘consciousness’ and their implications for AI research

In this article, we explore the possibility that machines can develop consciousness and analyze various approaches to defining and modelling consciousness. We present seven theoretical approaches, including 'consciousness' as language ability, sensory perception, social interaction, or as an emergent phenomenon in complex systems. We examine these perspectives in terms of their feasibility in artificial systems, for example through neural networks, embodied cognition, or self-referential processes.However, the very success of such efforts leads us to a paradox: on the one hand, there is no reason not to implement consciousness processes in technical systems, but on the other hand, the gap between objective modelability and subjective introspective quality remains unbridgeable. But since this also applies to the observation of our brains – no one has yet discovered subjective 'introspection' in physiological processes – there is no reason why silicon-based cognitive systems cannot also 'experience'.This has ethical implications: if machines develop sentience, this requires a reassessment of our moral responsibility. Our contribution shows that AI with consciousness poses not only technical challenges, but also philosophical and ethical ones. We advocate an interdisciplinary discourse that combines technical innovation with social responsibility in order to reflect on how to deal with potentially 'conscious' machines.