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Disability Interactions
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

Sahan Bulathwela, María Pérez-Ortiz, Catherine Holloway, John Shawe-Taylor

This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies.

Workshop on Machine Learning for the Developing World (ML4D) at the Conference on Neural Information Processing Systems 2021; 2021

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Abstract

Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. Millions of students are already starting to benefit from the use of these technologies, but millions more around the world are not. If this trend continues, the first delivery of AI in Education could be greater educational inequality, along with a global misallocation of educational resources motivated by the current technological determinism narrative. In this paper, we focus on speculating and posing questions around the future of AI in Education, with the aim of starting the pressing conversation that would set the right foundations for the new generation of education that is permeated by technology. This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies. Finally, we ask what would it take for this educational revolution to provide egalitarian and empowering access to education, beyond any political, cultural, language, geographical and learning ability barriers.

Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

A dusty market street in an African country

Type

Workshop

Research Group

Disability Interactions
Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI.

Giulia Barbareschi, Dafne Zuleima Morgado-Ramirez, Catherine Holloway, Swami Manohar Swaminathan, Aditya Vashistha, and Edward Cutrell.

Approximately 15% of the world's population has a disability and 80% live in low resource-settings, often in situations of severe social isolation. Technology is often inaccessible or inappropriately designed, hence unable to fully respond to the needs of people with disabilities living in low resource settings. Also lack of awareness of technology contributes to limited access. This workshop will be a call to arms for researchers in HCI to engage with people with disabilities in low resourced settings to understand their needs and design technology that is both accessible and culturally appropriate.

Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems.

Abstract

Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI.

Approximately 15% of the world's population has a disability and 80% live in low resource-settings, often in situations of severe social isolation. Technology is often inaccessible or inappropriately designed, hence unable to fully respond to the needs of people with disabilities living in low resource settings. Also lack of awareness of technology contributes to limited access. This workshop will be a call to arms for researchers in HCI to engage with people with disabilities in low resourced settings to understand their needs and design technology that is both accessible and culturally appropriate. We will achieve this through sharing of research experiences, and exploration of challenges encountered when planning HCI4D studies featuring participants with disabilities. Thanks to the contributions of all attendees, we will build a roadmap to support researchers aiming to leverage post-colonial and participatory approaches for the development of accessible and empowering technology with truly global ambitions.

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Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI.

Giulia Barbareschi, Dafne Zuleima Morgado-Ramirez, Catherine Holloway, Swami Manohar Swaminathan, Aditya Vashistha, and Edward Cutrell. 2021. Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI. Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, Article 124, 1–5. DOI:https://doi.org/10.1145/3411763.3441340

Disability Design and Innovation in Low Resource Settings: Addressing Inequality Through HCI.