Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools
Одного искусственного интеллекта недостаточно для демократизации образования: об образовательном неравенстве, технорешенчестве и инклюзивных инструментах
2024-01-16
SCID: 54.1/zbkg34cz
Discuss with AI
AI in Educationdigital divideeducational inequalityinclusive AItechno-solutionism
Figures from the paper
Abstract (AI)
Artificial Intelligence (AI) in Education claims to have the potential for building personalised curricula, as well as bringing opportunities for democratising education and creating a renaissance of new ways of teaching and learning. Millions of students are starting to benefit from the use of these technologies, but millions more around the world are not, due to the digital divide and deep pre-existing social and educational inequalities. If this trend continues, the first large-scale delivery of AI in Education could lead to greater educational inequality, along with a global misallocation of educational resources motivated by the current techno-solutionist narrative, which proposes technological solutions as a quick and flawless way to solve complex real-world problems. This work focuses on posing questions about the future of AI in Education, intending to initiate the pressing conversation that could set the right foundations (e.g., inclusion and diversity) for a new generation of education that is permeated with AI technology. The main goal of our opinion piece is to conceptualise a sustainable, large-scale and inclusive AI for the education ecosystem that facilitates equitable, high-quality lifelong learning opportunities for all. The contribution starts by synthesising how AI might change how we learn and teach, focusing on the case of personalised learning companions and assistive technology for disability. Then, we move on to discuss some socio-technical features that will be crucial to avoiding the perils of these AI systems worldwide (and perhaps ensuring their success by leveraging more inclusive education). This work 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 emphasise the need for collectively designing human-centred, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as supporting new emerging pedagogies. Finally, we ask what it would take for this educational revolution to provide egalitarian and empowering access to education that transcends any political, cultural, language, geographical and learning-ability barriers, so that educational systems can be responsive to all learners’ needs.
Key Findings
1
AI alone is unlikely to democratise education because the digital divide and pre-existing inequalities restrict access to its benefits.
2
Large-scale AI deployment in education could widen educational inequality and misallocate resources if guided by techno-solutionist assumptions.
3
Personalised learning companions and AI-based assistive technologies could reshape teaching and learning, including support for people with disabilities.
4
Sustainable and equitable AI in education requires inclusion, diversity, and socio-technical safeguards rather than technology-focused solutions alone.
5
The paper advocates collectively designed, human-centred, transparent, interactive, and collaborative AI systems integrated with free, participatory, democratic, and open educational resources.
Research Object
AI in Education ecosystem, including personalised learning companions and assistive technologies for disability
Research Subject
The potential of AI in Education to democratise learning and the socio-technical conditions required for inclusive, equitable, sustainable, and high-quality lifelong education
Publication Details
Publication Date
2024-01-16
Journal
Publisher
ISSN
Cited by
251
Open access PDF
Access Type
Author Information
Download PDF
Subscribe to digest
References available in scid.ai4
Transformers: State-of-the-Art Natural Language Processing2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text\n Transformer2019
A comprehensive AI policy education framework for university teaching and learning2023
New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution2023