Ana Paula da Rosa 228 us to perceive them with closed eyes. Similarly, like frames, images facilitate the narrative reconstruction from our memo- ries of something previously observed. That implies we face an imaginary actively produced and as a product, both individual and collective. It represents a creative force that converges with the influence of the media-driven imaginary. The media imaginary thrives on flows, sustained by repetition, reiteration, and shapes a model that persists across time (in cinema, animation, soap operas, and comics) and holds significance in social interactions. The depiction of the battle between good and evil and a utopian future mediated by machines are interconnected yet they seem to diverge from the representation of the typical person in our era. While all these scenes circulate, it is somewhat challenging to contemplate our present, which is already permeated by machines, and to con- ceive that, beyond visual routes, there is an interplay of imagination: humans imagining machines (ever more advanced and faster), and machines imagining humans (increasingly as mere servants) I . n this sense, the Swedish researcher Hans Ruin (2022) refers to the issue of the fantasy realm linked to discussions of technology in our time, especially concerning artificial intel- ligence. According to the Professor of Philosophy at Södertörn University, artificial intelligence is a prevalent topic, whether by “its new evangelists or its prophets of doomsday.” It perme- ates literature and cinema, with some products launched and relaunched over time. Above all, commercial applications and interest are again at the forefront. The explanation for this change has an interesting philosophical dimension. While AI research believed in recreating human intelligence, it was stuck in a route that did not lead to the promised results. The real breakthrough came when engineers abandoned the idea of trying to model human intelligence and its functions, and instead focused their efforts on creating machines that could “learn” on their own, using algorithms that statically process enormous and continually growing data volumes (Ruin, 2022, p. 30).
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