Purpose This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field. Design/methodology/approach The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review (...) followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI. Findings This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection. Originality/value The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies. (shrink)

As science focuses exclusively on the physical, it seems to assume that the brain has a key role in the origin if not also the constitution of our consciousness; and thus the destruction of the brain, the nervous system, and the body makes it pointless or even absurd to think of any personal consciousness after death. But one need not be convinced by this. However, any effort to investigate a possible post-mortem life depends on forming a coherent conception of what (...) such a life could be. Can we speak, without incoherence or contradiction, of a person continuing to exist after death in a disembodied state? Our concern in this study lies here. Based on Lund’s view, we will present and defend an argument that one can conceive of a self who is fully embedded in the natural world and deeply embodied in a physical organism, and yet could have a rich variety of experiences in an afterworld encountered after death. In this theory, the close association of the mental and the physical is due to a causal connection - a connection that fails to establish that the physical brings the mental into existence and is compatible with theories that the source of consciousness is not in the brain. (shrink)