Comparative Analysis of AI-Predicted and Crowdsourced Food Prices in an Economically Volatile Region
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Washington, DC: World Bank
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High-frequency monitoring of food
commodity prices is important for assessing and responding
to shocks, especially in fragile contexts where timely and
targeted interventions for food security are critical.
However, national price surveys are typically limited in
temporal and spatial granularity. It is cost prohibitive to
implement traditional data collection at frequent timescales
to unravel spatiotemporal price evolution across market
segments and at subnational geographic levels. Recent
advancements in data innovation offer promising solutions to
address the paucity of commodity price data and guide market
intelligence for diverse development stakeholders. The use
of artificial intelligence to estimate missing price data
and a parallel effort to crowdsource commodity price data
are both unlocking cost-effective opportunities to generate
actionable price data. Yet, little is known about how the
data from these alternative methods relate to independent
ground truth data. To evaluate if these data strategies can
meet the long-standing demand for real-time intelligence on
food affordability, this paper analyzes open-source daily
crowdsourced data (104,931 datapoints) from a recently
published data set in Nature Journal, relative to
complementary ground truth sample. The paper subsequently
compares these data to open-source monthly artificial
intelligence–generated price data for identical commodities
over a 36-month period in northern Nigeria, from 2019 to
2022. The results show that all the data sources share a
high degree of comparability, with variation across
commodity and market segments. Overall, the findings provide
important support for leveraging these new and innovative
data approaches to enable data-driven decision-making in
near real time.
Palabras clave
ZERO HUNGER, SDG 2, FOOD SECURITY, FOOD COMMODITY PRICES, ARTIFICIAL INTELLIGENCE, INDUSTRY, INNOVATION AND INFRASTRUCTURE, SDG 9