Geek Heresy: Rescuing Social Change from the Cult of Technology
By Kentaro Toyama. 2015
336 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Shakir Mohamed
- Vinodkumar Prabhakaran
- Abeba Birhane
- William S. Isaac
- Junaid Qadir
- Marie-Therese Png
- Mark Díaz
- Iason Gabriel
Citations in the corpus
- Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020, methodology): “To do so, we can draw from existing analysis of ICT for Development, which are often based on historical analysis and decolonial critique (Irani et al. 2010; Toyama 2015).”
- Power to the People? Opportunities and Challenges for Participatory AI (2022, background): “When such collective knowledge is missing, its absence leads to failure leaving projects to be based solely upon technocratic or elite perspectives [30, 64, 82].”
- End User Security and Privacy Concerns with Smart Homes (2017, background): “Technological solutions when not implemented correctly may amplify social issues [58].”
- Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education (2023, background): “As Kentaro Toyama notes in his book “Geek Heresy: Rescuing Social Change from the Cult of Technology,” the effectiveness of any resource or tool is limited by an individual’s existing knowledge and background [22].”
- Will digital technologies transform agriculture in developing countries (2016, unknown): “Third, technology-enabled interventions are no panacea in themselves, and need to be backed by complementary investments in physical infrastructure, electricity, literacy, and so on (Toyama 2015).”
- Critical Race Theory for HCI (2020, background): “It actualizes the economic concentration of wealth through technological infrastructures that exploit private data [123], harvest human attention [138], and squeeze workers and consumers, all while supposedly color-blind algorithms propagate, reinforce, automate, and amplify past and present racial ”