A Machine Trained with Love: What does reciprocal AI look like?
To reimagine a slow and hopeful model of intelligence could mean asking AI to move like a swallow, adapt like slime mould or sense like a root system. Artist and activist Beccy McCray weaves together collective memory, environmental rhythms, and her own lineage to ask how machine learning might support - not replace - intuitive, interspecies ways of knowing.
Beccy McCray

What if artificial intelligence wasn’t designed for optimisation, efficiency or control - but for reciprocity, embedded knowledge, and collective movement?
This question emerged for me in the making of Intuition Maps - a participatory artwork grounded in the instincts of humans and more-than-human species. Rooted in Northamptonshire, and commissioned by Fermynwoods Contemporary Art, the artwork brought together local communities and native migratory species - chiffchaffs, swallows, painted lady butterflies, migrant hawker dragonflies, and more - to explore how capitalism and climate collapse are reshaping the intuitive rhythms that guide us. Together, we created more than maps, these were divinatory tools: drawings, dialogues, and speculative routes that traced instinct and imagination.
I found myself turning to artificial intelligence - not for answers, but as a kind of collaborator. I started to see AI as more than a tool of control, but as an unpredictable and uncanny model. A new kind of crystal ball. A machine trained on signs and patterns, learning to ‘read’ the world. Increasingly, I believe AI is our latest act of divination - playing into our ancient urge to foresee, foretell, and make meaning out of uncertainty.
For me, this is deeply personal. My Romany heritage includes a cultural connection to fortune telling that stretches back generations - not as a novelty, but as a serious practice of intuition and survival. I increasingly work more intuitively, using art and ritual to tune into the world and read its signs. And I see parallels here with AI - particularly machine learning - as a process that searches for signals, finds patterns, and generates possibilities. At its best, it’s a collaboration between the known and the unknown.
I trained the machine with love - not just to perform tasks, but to listen. To become a participant in a wider ecology of intelligence.