Sonified global wealth gaps provide an abrasive soundtrack to AI-generated solutions to poverty that keep getting increasingly more radical.
Sonifying data sets extracted from widening global income gaps using custom tools developed by the artist, Basic Needs Guaranteed enlists an LLM to generate a series of increasingly radical solutions to poverty. Utilizing predictive text as an unrepentant mirror, the steadily intensifying soundtrack reflects the urgency of growing inequality. A building chorus of RAVE-encoded murmurs tracing the contours of wealth ratios gives voice to the those living below acceptable thresholds. The piece aims to expose poverty's persistence as a Gordian knot at the twisted heart of a tangled web of systemic issues. Expressed with familiar typefaces, the generated sloganeering makes a self-aware nod to propaganda, raising the question: why do fundamental necessities seem beyond reach in our current era of techno-capitalist excess?
noahpred
Sonified global wealth gaps provide an abrasive soundtrack to AI-generated solutions to poverty that keep getting increasingly more radical.
Sonifying data sets extracted from widening global income gaps using custom tools developed by the artist, Basic Needs Guaranteed enlists an LLM to generate a series of increasingly radical solutions to poverty. Utilizing predictive text as an unrepentant mirror, the steadily intensifying soundtrack reflects the urgency of growing inequality. A building chorus of RAVE-encoded murmurs tracing the contours of wealth ratios gives voice to the those living below acceptable thresholds. The piece aims to expose poverty's persistence as a Gordian knot at the twisted heart of a tangled web of systemic issues. Expressed with familiar typefaces, the generated sloganeering makes a self-aware nod to propaganda, raising the question: why do fundamental necessities seem beyond reach in our current era of techno-capitalist excess?
50% of proceeds automatically go to: savethechildren.org
Data sourced from: ourworldindata.org/poverty#explore-data-on-poverty (Joe Hasell, Max Roser, Esteban Ortiz-Ospina, and Pablo Arriagada)