Most of human-robot interaction (HRI) research relies on an implicit assumption that seems to drive experimental work in interaction studies: the more anthropomorphism we can reach in robots, the more effective the robot will be in “being social.” The notion of “sociomorphing” was developed in order to challenge the assumption of ubiquitous anthropomorphizing. This paper aims to explore the notion of sociomorphing by analysing the possibilities offered by actor-network theory (ANT). We claim that ANT is a valid framework to re-think the conceptual couple anthropomorphizing / sociomorphing and answer the following question: What kind of negotiation process and social practices can be developed in HRI, given the notion of sociomorph interactional networks?

Purpose The purpose of this paper is to present the conceptual model of an innovative methodology (SAT) to assess the social acceptance of technology, especially focusing on artificial intelligence (AI)-based technology. Design/methodology/approach After a review of the literature, this paper presents the main lines by which SAT stands out from current methods, namely, a four-bubble approach and a mix of qualitative and quantitative techniques that offer assessments that look at technology as a socio-technical system. Each bubble determines the social variability of a cluster of values: User-Experience Acceptance, Social Disruptiveness, Value Impact and Trust. Findings The methodology is still in development, requiring further developments, specifications and validation. Accordingly, the findings of this paper refer to the realm of the research discussion, that is, highlighting the importance of preventively assessing and forecasting the acceptance of technology and building the best design strategies to boost sustainable and ethical technology adoption. Social implications Once SAT method will be validated, it could constitute a useful tool, with societal implications, for helping users, markets and institutions to appraise and determine the co-implications of technology and socio-cultural contexts. Originality/value New AI applications flood today’s users and markets, often without a clear understanding of risks and impacts. In the European context, regulations (EU AI Act) and rules (EU Ethics Guidelines for Trustworthy) try to fill this normative gap. The SAT method seeks to integrate the risk-based assessment of AI with an assessment of the perceptive-psychological and socio-behavioural aspects of its social acceptability.

A crucial philosophical problem of social robots is how much they perform a kind of sociality in interacting with humans. Scholarship diverges between those who sustain that humans and social robots cannot by default have social interactions and those who argue for the possibility of an asymmetric sociality. Against this dichotomy, we argue in this paper for a holistic approach called “Δ phenomenology” of HSRI (Human–Social Robot Interaction). In the first part of the paper, we will analyse the semantics of an HSRI. This is what leads a human being (x) to assign or receive a meaning of sociality (z) by interacting with a social robot (y). Hence, we will question the ontological structure underlying HSRIs, suggesting that HSRIs may lead to a peculiar kind of user alienation. By combining all these variables, we will formulate some final recommendations for an ethics of social robots.