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Research Group
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

Type
Tabish Ahmed, Sahan Bulathwela
The informational needs of people are highly contextual and can depend on many different factors such as their current knowledge state, interests and goals [1, 2, 3]. However, an effective information retrieval companion should minimise the human effort required in i) expressing a human information need and ii) navigating a lengthy result set. Using topical representations of the user history (e.g. [4]) can immensely help formulating zero shot queries and refining short user queries that enable proactive information retrieval (IR). While the world has digital textual information in abundance, it can often be noisy (e.g. extracted through Automatic Speech Recognition (ASR), PDF text extraction etc.), leading to state-of-the-art neural models being highly sensitive to the noise producing sub-optimal results [5]. This demands denoising steps to refine both query and document representation. In this paper, we argue that Wikipedia, an openly available encyclopedia, can be a humanly intuitive knowledge base [6] that has the potential to provide the world view many noisy information Retrieval systems need.
Published at the First Workshop on Proactive and Agent-Supported Information Retrieval at CIKM 2022; 2022

Type
This article was featured in Nature and discusses tools that help visually impaired scientists read data and Journals. Innovation Manager, Daniel Hajas, was interviewed as part of this piece and highlights the need for an ecosystem approach, and access to data / visualisations for blind members of the research and science community.
Nature; 2023

Type
Research Group
; 2021

Type
As an entrepreneur, learning how to solve problems by creating and experimenting with different strategies is a core pillar of the entrepreneurial mindset you need to succeed. However, there’s rarely a single correct way to solve problems as an entrepreneur, so you need to learn how to create and compare different solutions.
The open entrepreneurship toolkit is a set of learning materials that can help you and your team do just that. Covering the domains of user, product, market and business development, the set of cards have been designed to be used by two or more group members to actively experiment with different solutions.
Innovate Now

Type
Research Group
Nusrat Jahan and Catherine Holloway
This working paper was developed to support the development of challenge statements for a GDI Hub innovation challenge fund call related to improving access to and retention of employment for persons with disabilities in Kenya and Bangladesh and is written by GDI Hub's Nusrat Jahan and Professor Catherine Holloway.
The issue of disability and employment has taken centre stage on the global arena in part because it is recognised across several areas of the United Nations Sustainable Development Goals, in which confrontation of extreme poverty in its many manifestations is the number one goal [2]. The World Health Organization (2011) reports about 15 percent of the world’s population has a disability [1]. In developing countries, 80 to 90 percent of people with disabilities of working age are unemployed.