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1. Targeting Development Aid with Machine Learning and Mobile Phone Data: Evidence from an Anti-Poverty Intervention in Afghanistan

   https://doi.org/10.1145/3378393.3402274  

   Aiken, Emily L.; Bedoya, Guadalupe; Coville, Aidan; Blumenstock, Joshua E. (June 2020, ACM SIGCAS Computing and Sustainable Societies (COMPASS 2020))

   null (Ed.)

   Recent papers demonstrate that non-traditional data, from mobile phones and other digital sensors, can be used to roughly estimate the wealth of individual subscribers. This paper asks a question more directly relevant to development policy: Can non-traditional data be used to more efficiently target development aid? By combining rich survey data from a "big push" anti-poverty program in Afghanistan with detailed mobile phone logs from program beneficiaries, we study the extent to which machine learning methods can accurately differentiate ultra-poor households eligible for program benefits from other households deemed ineligible. We show that supervised learning methods leveraging mobile phone data can identify ultra-poor households as accurately as standard survey-based measures of poverty, including consumption and wealth; and that combining survey-based measures with mobile phone data produces classifications more accurate than those based on a single data source. We discuss the implications and limitations of these methods for targeting extreme poverty in marginalized populations. 

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2. Consumer decisions to repair mobile phones and manufacturer pricing policies: The concept of value leakage

   https://doi.org/https://doi.org/10.1016/j.resconrec.2018.01.015  

   Sabbaghi, Mostafa; Behdad, Sara (June 2018, Resources, conservation and recycling)

   Mobile phones have become ‘essential-to-have’ devices for information-gathering and social communication. They are being technologically advanced, while they are readily available at affordable prices. This motivates consumers to upgrade their mobile phones more frequently. Given these considerations and the lack of accessible repair services, mobile phones have a relatively short life span. The underuse of mobile phones, despite the fact that they are made durable, may result in losses or value leakage. In this study, a probabilistic approach is proposed to quantify the value leakage that may occur due to consumer’s decision to not repair broken mobile phones and simply replace them with new ones. A group of 208 mobile phone users has been surveyed to capture consumer’s time-dependent willingness-to-pay for repair services. Then, consumer’s repair behavior is combined with manufacturer’s repair service pricing strategies to calculate the probability of repair or replacement decisions over the life span of mobile phones. Finally, the total expected leakage risk is derived for both consumers and manufacturers. For illustrative purposes, it is shown that a manufacturer may lose up to 331 million dollars over a period of five years due to consumers’ decisions to not repair their cracked-screen mobile phones and switch to another brand. 

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3. Community perspectives of heat and weather warnings for pregnant and postpartum women in Kilifi, Kenya

   https://doi.org/10.1371/journal.pone.0313781  

   Lusambili, Adelaide; Filippi, Veronique; Nakstad, Britt; Natukunda, Julian; Birch, Cathryn E; Marsham, John H; Roos, Nathalie; Khaemba, Peter; Kovats, Sari (November 2024, PLOS ONE)

   Colborn, James (Ed.)

   BackgroundExtreme weather is a recognised risk factor for stillbirth and preterm birth, disrupts women’s access to healthcare during pregnancy and childbirth, and negatively affects the care of newborns. Reliable and accessible heat and weather warning systems are key in alerting individuals to undertake protective measures. There is a notable gap in understanding how women and caregivers in rural East Africa perceive and utilize weather information. We investigated community members’ heat and weather warning information-seeking behaviour, identified available sources, assessed their reliability and utility, and examined their influence on behaviour. SettingsOur research was conducted in rural Kilifi County in Kenya’s coastal region. The area experiences temperatures exceeding 23°C throughout the year, with extended periods of extreme temperatures [> 40°C] and long and severe droughts. MethodsWe conducted in-depth interviews [IDI] with pregnant and postpartum women [n = 21] and held six focus group discussions [FGDs] involving mothers-in-law and community health volunteers [CHVs]. The data were analysed in NVivo 12 using both inductive and deductive approaches. ResultsWe found significant gaps concerning pregnant and post-partum women, and their caregivers, having timely access to weather forecasts and heat information from health or meteorological authorities. Information on heat and weather warnings is disseminated through various channels, including television, radio, mobile phones, and word of mouth, which are facilitated by community influencers such as CHVs and local chiefs. Indigenous methods of weather forecasting, such as cloud observation, consulting local “rainmakers”, and studying the behavioural patterns of amphibians, are employed in conjunction with warnings from the Kenyan Meteorological Department (KMD). Barriers to accessing weather information include the cost of television and smartphones and a lack of segmented information in local languages. ConclusionsNational and county meteorological services need to enhance public participation, communication, and the delivery of heat and weather information to guide community-level response measures and individual behaviour change. They should also collaborate with health professionals to address heat risks for vulnerable groups. Further research is needed to empower indigenous weather predictors with modern weather information and revise national policies to deliver tailored messages to vulnerable populations like pregnant and postpartum women. 

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4. Augmented reality for high-throughput phenotyping

   Wu, Shanshan; Neilsen, Mitchell L. (July 2019, 17th International Conference on Scientific Computing)

   Augmented Reality (AR) enables elements of a computer-generated digital world to be integrated with a user’s perception of the physical world. Smart glasses, like smart phones, have independent operating systems and they can support a variety of different applications and modes of communication to support augmented reality. This paper details the development of a novel new application that extends a widely-used mobile app for phenotyping and allows agronomists to interact with the app while keeping their hands free to perform field work. The smart glasses accept voice commands from the user and communicate with the mobile phone app via Bluetooth. In addition, changes detected by the mobile phone are displayed to the user on the smart glasses. This enables agronomists to efficiently collect phenotypic data. 

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5. No Privacy Among Spies: Assessing the Functionality and Insecurity of Consumer Android Spyware Apps

   https://doi.org/10.56553/popets-2023-0013  

   Liu, Enze; Rao, Sumanth; Havron, Sam; Ho, Grant; Savage, Stefan; Voelker, Geoffrey M.; McCoy, Damon (January 2023, Proceedings on Privacy Enhancing Technologies)

   Consumer mobile spyware apps covertly monitor a user's activities (i.e., text messages, phone calls, e-mail, location, etc.) and transmit that information over the Internet to support remote surveillance. Unlike conceptually similar apps used for state espionage, so-called stalkerware apps are mass-marketed to consumers on a retail basis and expose a far broader range of victims to invasive monitoring. Today the market for such apps is large enough to support dozens of competitors, with individual vendors reportedly monitoring hundreds of thousands of phones. However, while the research community is well aware of the existence of such apps, our understanding of the mechanisms they use to operate remains ad hoc. In this work, we perform an in-depth technical analysis of 14 distinct leading mobile spyware apps targeting Android phones. We document the range of mechanisms used to monitor user activity of various kinds (e.g., photos, text messages, live microphone access) — primarily through the creative abuse of Android APIs. We also discover previously undocumented methods these apps use to hide from detection and to achieve persistence. Additionally, we document the measures taken by each app to protect the privacy of the sensitive data they collect, identifying a range of failings on the part of spyware vendors (including privacy-sensitive data sent in the clear or stored in the cloud with little or no protection). 

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