Artificial Intelligence (AI) is transforming all fields of knowledge and
production. From surgery, autonomous driving, to image and video creation, AI
seems to make possible hitherto unimaginable processes of automation and
efficient creation. Media and communication are not an exception, and we are
currently witnessing the dawn of powerful AI tools capable of creating artistic
images from simple keywords, or to capture emotions from facial expression.
These examples may be only the beginning of what can be in the future the
engines for automatic AI real time creation of media content linked to the
emotional and behavioural responses of individuals. Although it may seem we are
still far from there, it is already the moment to adapt our theories about
media to the hypothetical scenario in which content production can be done
without human intervention, and governed by the controlled any reactions of the
individual to the exposure to media content. Following that, I propose the
definition of the Integrated Model of Artificial Intelligence-Mediated
Communication Effects (IMAGINE), and its consequences on the way we understand
media evolution (Scolari, 2012) and we think about media effects (Potter,
2010). The conceptual framework proposed is aimed to help scholars theorizing
and doing research in a scenario of continuous real-time connection between AI
measurement of people’s responses to media, and the AI creation of content,
with the objective of optimizing and maximizing the processes of influence.
Parasocial interaction and real-time beautification are used as examples to
model the functioning of the IMAGINE process.