The Arts Face a Lesson in Data Handling: Insights from the Dismissal at the Bureau of Labor Statistics
In a world where data is increasingly becoming a vital tool for understanding and navigating complex issues, two distinct approaches to handling challenging data have emerged, particularly in the arts and cultural sector and the labor statistics sector.
Last week, the head of the Bureau of Labor Statistics (BLS) was forced out, sparking outrage among those who see it as an attack on the integrity of public data. Reports suggest that the firing was due to delivering jobs numbers that didn't align with Donald Trump's preferred narrative, a scenario that highlights tensions around uncomfortable or challenging data in governmental contexts.
In stark contrast, the arts and cultural sector tends to approach data that challenges assumptions or requires uncomfortable conversations with a mixture of critical self-reflection and innovative investigative methods. Journalists and researchers employ a "data mindset" to creatively investigate cultural funding, impact, and infrastructure, even creating their own datasets or using AI to make data accessible and understandable in innovative ways.
The sector critically acknowledges the difficulty of integrating digital metrics and the importance of asking probing questions, even if the data reveals inconvenient truths about cultural relevance, financial sustainability, or societal impact. There is an ethical awareness informed by respect for cultural values and sovereignty, especially around Indigenous data governance, emphasizing contextual, protective, and accountable approaches to data use in culturally sensitive ways.
Arts organizations also face pressures related to philanthropy and impact measurement, reflecting evolving values that challenge traditional notions of "art for art's sake," encouraging transparent justification of cultural investment and outcomes.
In contrast, sectors like labor statistics, exemplified by the BLS case, often operate within rigid bureaucratic and political frameworks. The firing of a head over data issues reflects a scenario where data that challenge official narratives or political interests can lead to direct consequences for the data handlers, illustrating less tolerance for uncomfortable data interpretations or disclosures outside accepted norms.
This difference highlights how data culture varies substantially by sector and context. In the arts sector, the focus should be on who's thriving, who's struggling, where the bottlenecks are, and what the structural dynamics look like. Not knowing the full scope of problems in the arts sector is a choice to remain in the dark, and cherry-picking only positive data erodes trust and weakens the ability to respond to real problems or argue for change.
Data is crucial for museum directors, grantmakers, and nonprofit leaders to benefit their organizations and the communities they serve. It should be a public good, shared by all, not owned by funders, institutions, or advocacy shops. The arts sector should not only treat data as useful when it flatters but also when it presents challenges.
Lasting solutions to deep structural challenges in the arts sector cannot be built without understanding the full scope of the problems. The call is made for supporting basic research to understand the true state of the arts field, and investment in infrastructure is needed for consistent and independent data collection and analysis.
In the spirit of transparency and self-criticism, the arts sector should match its continuous criticism of political leaders for rejecting inconvenient data with a similar self-criticism. Museum directors, grantmakers, and nonprofit leaders should seek data actively, not just accept it, to benefit their organizations and the communities they serve.
Sources:
[1] Creative PEC. (n.d.). Arts Analytics. Retrieved from https://creativepec.org/arts-analytics/
[2] National Endowment for the Arts. (2019). The Arts and Philanthropy. Retrieved from https://www.arts.gov/grants-organizations/grants/the-arts-and-philanthropy
[3] National Endowment for the Arts. (2018). Arts Data Profile. Retrieved from https://www.arts.gov/data-research/research-reports/arts-data-profile
[4] Smithsonian Institution. (2019). Indigenous Data Sovereignty. Retrieved from https://www.si.edu/spotlight/indigenous-data-sovereignty
- In the arts and cultural sector, data is utilized creatively to investigate cultural funding, impact, and infrastructure, often employing AI to make data more accessible and understandable.
- Journalists and researchers in this sector adopt a "data mindset," critically acknowledging the difficulty of integrating digital metrics, and are mindful of the importance of asking probing questions, even if the data reveals inconvenient truths.
- The arts sector values cultural values and sovereignty, especially around Indigenous data governance, emphasizing contextual, protective, and accountable approaches to data use in culturally sensitive ways.
- Meanwhile, labor statistics sectors like the Bureau of Labor Statistics (BLS) operate within strict bureaucratic and political frameworks, where data that challenges official narratives or political interests can lead to direct consequences for the data handlers.
- The general news sector has reported on the firing of the head of the BLS due to delivering jobs numbers that didn't align with Donald Trump's preferred narrative, highlighting tensions around uncomfortable or challenging data in governmental contexts.
- In the realm of data-and-cloud-computing and technology, policy and politics play a significant role in shaping data culture, with research revealing substantial differences between sectors like the arts and labor statistics.
