The authors explore how current mainstream data-driven AI approaches can be questioned critically from a perspective of computational creativity and ecosystemic art. This centres on a critique of the future as being over-determined by the past; both from the data used, and in the questions or objectives assumed by training. The main contributions of this paper are to apply alternative creative approaches to nature-inspired artificial intelligence, and to detail some of these through their embodiment in the authors’ artwork “Infranet”. Infranet is a neuro-evolutionary art installation that exhibited at three international locations over 2018-2019. It uses geospatial data of the host city not as a training material but as a habitat for artificial life. In contrast to training-based AI systems, in Infranet there is no objective or fitness function and very little evolutionary pressure or competition. Moreover, it eschews the trend of a large and pre-specified neural network structure in favour of a population of thousands of small interacting neural networks, each with distinct structure, in a "liquid" process of continuous reorganization; resonating with some contemporary theories and models of non-conscious cognition in biological and ecological systems.