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The proliferation of AI-powered bots and sophisticated fraudsters poses a significant threat to the integrity of scientific studies reliant on online surveys across diverse disciplines, including health, social, environmental and political sciences. We found a substantial decline in usable responses from online surveys from 75 to 10% in recent years due to survey fraud. Monetary incentives attract sophisticated fraudsters capable of mimicking genuine open-ended responses and verifying information submitted months prior, showcasing the advanced capabilities of online survey fraud today. This study evaluates the efficacy of 31 fraud indicators and six ensembles using two agriculture surveys in California. To evaluate the performance of each indicator, we use predictive power and recall. Predictive power is a novel variation of precision introduced in this study, and both are simple metrics that allow for non-academic survey practitioners to replicate our methods. The best indicators included a novel email address score, MinFraud Risk Score, consecutive submissions, opting-out of incentives, improbable location.

California is the largest agricultural economy in the United States; however, its current and projected climate risks pose significant challenges. Farmers will need to adapt to climate change in their farming practices. The goal of this needs assessment was to understand farmers' perceptions and experiences with climate change exposures; the risk management practices they currently use; and what tools and resources would assist them in making strategic decisions. A statewide survey was conducted through Qualtrics with farmers (n = 341). Results showed that 67% of the farmers agree (agree + strongly agree) that climate change is happening, and 53.1% agreed that actions are required. Moreover, historically underrepresented farmers were very concerned about climate change-related impacts related to water, temperatures, and natural disasters. Farmers are currently implementing adaptation practices related to water management, soil health, and renewable energy and are also seeking insurance and government assistance programs to increase agricultural resilience. They also expressed interest and a high need for information on those adaptation practices to acquire skills and knowledge to manage various challenges of farming in variable climates. Also, the assessment established that farmers (47.5%) use decision-support tools, mostly weather stations (22.4%); and 51.9% indicated their interest in using online tools designed to translate climate information into forms that support production decision-making. Farmers (60.8%) responded that they would or may attend workshops to learn about adaptation practices. The findings of this needs assessment will inform the development of extension education programs on climate-smart agriculture for farmers in California and elsewhere. [ABSTRACT FROM AUTHOR]

The proliferation of AI-powered bots and sophisticated fraudsters poses a significant threat to the integrity of scientific studies reliant on online surveys across diverse disciplines, including health, social, environmental and political sciences. We found a substantial decline in usable responses from online surveys from 75 to 10% in recent years due to survey fraud. Monetary incentives attract sophisticated fraudsters capable of mimicking genuine open-ended responses and verifying information submitted months prior, showcasing the advanced capabilities of online survey fraud today. This study evaluates the efficacy of 31 fraud indicators and six ensembles using two agriculture surveys in California. To evaluate the performance of each indicator, we use predictive power and recall. Predictive power is a novel variation of precision introduced in this study, and both are simple metrics that allow for non-academic survey practitioners to replicate our methods. The best indicators included a novel email address score, MinFraud Risk Score, consecutive submissions, opting-out of incentives, improbable location., Competing Interests: NP, WD, and MB were employed by Rhizobia LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer SM declared a shared affiliation with the author NT-F to the handling editor at the time of review., (Copyright © 2024 Pinzón, Koundinya, Galt, Dowling, Baukloh, Taku-Forchu, Schohr, Roche, Ikendi, Cooper, Parker and Pathak.)