Believe it Yourself, Automato
The fast spreading and ease of access to Machine Learning and Cloud computing has brought to a boom of experiments and excitement around our ability to build machines that make sense, learn, measure and predict the world around us.
Moreover, with enough examples, we can train a tool or a ‘machine’ to recognize or quantify pretty much anything we want. ‘Beauty’, ‘Hotdog-ness’ or the more problematic ‘Criminal-ness’ and ‘Sexual orientation’ can be now measured within a few frames, based on a model, a probability, determined by a set of arbitrarily collected data. Subjective judgments and biased datasets can easily be turned into objective measures and potential truths, which will then be embedded in devices around us.
But what if we would train machines to measure even more unmeasurable, personal and culturally driven things? If we gather enough samples could we detect signs that prove and detect our superstitions? and can we use that to build tools and devices that reflect our own beliefs?
BIY™- Believe it Yourself is a series of real-fictional belief-based computing kits to make and tinker with vernacular logics and superstitions.