An overemphasis on data-driven work within the nonprofit sector has been shown to result in cycles of disempowerment, driven by third-party data demands of funding bodies.. This compounds due to the many market orientations nonprofits need to adopt, particularly prevalent among the arts. A key to navigating these markets and funder requirements lies in identifying a specific data culture best fit for your organization and investing in resources and training in order to achieve that framework sustainably.
With AI’s ability to automatically produce content and process complicated datasets with high accuracy, museums worldwide are exploring ways in which this innovative technology can help them better achieve their missions and advance accessibility efforts. Through case studies, learn about three applications of this technology: content digitalization, language accessibility, and visual description.
October was filled with new debates on AI policies, a halt to one of the most significant AI safety bills in the United States, and a host of new AI developments in video, music, and even podcasts.
Arts and cultural nonprofits often operate in multiple markets for earned and contributed revenue. With increasing attention on data-driven decision making, effective market orientation often depends on effective data use. This fundamental collection, transmission, use, and interpretation of data within an organization collectively contributes to what can be considered an organization’s data culture.
Museums have increasingly begun to volunteer their spaces as polling places, acting as a democratic vehicle for their communities and adding to the greater fabric of America’s election infrastructure. In doing so, they can support local democratic processes and prove to their communities that they are not unbreachable temples for the elite, but open platforms for the people.
