Abstract
Artificial Intelligence-based Decision Support Systems (AI-based DSS) are becoming increasingly important in many contexts. This work aims to define a type of human-machine interactions for new value co-creation processes' ranks, to help identify factors that can stimulate value co-creation in human-machine interactions. To understand if the outcome of a man-machine interaction can contribute to the co-creation of value, and in what way, the work carried out is epistemological and typological, also based on System Thinking. A matrix of novel gradients of the relationships between humans and non-humans has been created, and the typology of human-machine interactions has been identified for the new degrees of value co-creation processes, as well as the new specific scale of skills, in terms of language, learning, know-how, level of trust and endowment of knowledge, as a whole. The main implications concern the need to customize Decision Support Systems (DSS), to enhance different levels of intensity of relationships, and to identify insights for Decision Making AI - based users.
Highlights
When humans and machines and humans work together, they can really achieve higher levels of effectiveness [1], even if AI solutions efficacy is depending on humans’ involvement [2]
Human-Machine Interactions (HMIs) are fostered by AI solutions even more, as they are progressing at a high-speed pace, showing abilities to perceive words, develop cognition, build relationship, and fill roles
Actors involved in a value cocreation have better opportunity in building a positive value understanding process; in this context, machines solutions emerge as actors’ stimulators, and occurring misunderstanding could be reduced thanks to humans’ attitude to be dynamic and open to the change, while machines can act as relevant actors able to share openness, flexibility, and reaction to change
Summary
When humans and machines (including AI solutions) (we can intend as ‘machine’) and humans work together, they can really achieve higher levels of effectiveness [1], even if AI solutions efficacy is depending on humans’ involvement [2]. Humans seem to have always a central role in interacting with AI, since computers plus humans do better than either one alone [3]. As sub-optimal performances may occur, as assessed at different levels than the one of the Human-Machine Interactions (HMIs), due to emergent consequences [5][6]. HMIs are fostered by AI solutions even more, as they are progressing at a high-speed pace, showing abilities to perceive words, develop cognition, build relationship, and fill roles. Many questions on how AI should be developed and used by humans arise [7], for example in values-oriented design and ethics for users [8]
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