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Craig
Jolley
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Access to Internet & Digital Communications
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Digital Economies & Markets
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Digital Divide, Digital Inequalities
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Freedom of Expression Online, Internet Freedom
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Language
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Output Type
Digital Ecosystem Country Assessment (DECA): Nepal
USAID, Digital Frontiers Project (2022), 92 pp.
"Nepal’s digital ecosystem does not yet meet the needs of all Nepalis and runs the risk of falling further behind. Over the past decade, mobile phones, and mobile internet have become increasingly widespread in Nepal; however, the government’s capacity to implement digital policies and solutions
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Digital Ecosystem Country Assessment (DECA): Libya
USAID, Digital Frontiers Project (2022), 85 pp.
"Key findings include: Connectivity infrastructure is fairly well developed in coastal urban areas but lags behind in Libya’s sparsely populated southern region; COVID-19 has accelerated the adoption of digital tools and services across sectors; however, Libyans are reluctant to adopt new tools du
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Digital Ecosystem Country Assessment (DECA): Serbia
USAID, Digital Frontiers Project (2021), 58 pp.
"The Serbian government prioritizes digitalization. Serbia’s digital transformation accelerated in 2017 with the government’s focus on building a digital government, or “digitalization” as defined by Serbians, and Serbia’s participation in the Digital Agenda for the Western Balkans. As one
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Digital Ecosystem Country Assessment (DECA): Colombia
USAID, Digital Frontiers Project (2020), 43 pp.
"[...] The DECA is a decision-making tool to help USAID Missions, their partners, and other relevant stakeholders identify the opportunities, maximize the benefits, and manage the risks associated with digital technology. The goal is to help USAID’s partner countries along their journey to self-re
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Reflecting the Past, Shaping the Future: Making AI Work for International Development
USAID (2018), 97 pp.
"This document aims to inform and empower those who may have limited technical experience as they navigate an emerging ML/AI landscape in developing countries. Donors, implementers, and other development partners should expect to come away with a basic grasp of common ML techniques and the problems
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