Each year in England, 24.8 million adults volunteer in some way at least once, delivering essential support in their communities, from crisis response and youth programmes to supporting vulnerable ...

Facing the challenge of embedding ethical considerations into your operations. In today’s evolving landscape of data ethics and responsible AI, organisations face the challenge of embedding ethical ...

‘Assessing risk when sharing data: a guide’ has been created to help organisations identify, assess and manage risks related to sharing data that they hold From optimising supply chains and supporting ...

This report aims to map the UK government’s activity on ‘data literacy’, as part of the ODI’s work supporting the development of the UK’s data economy The UK government recognises the importance of ...

As Artificial Intelligence (AI) continues to drive innovation across sectors and advance social good, the demand for well-governed and appropriate data - encompassing diverse formats such as text, ...

Data trusts could be a useful way of increasing access to data while retaining trust, says our latest report To realise the potential benefits of data for our societies and economies we need ...

From October 2024, the ODI will bring Solid - an open standard developed to give individuals and organisations greater control over their data - into its broader data stewardship activities. The Solid ...

In this case study we look at how HiLo Maritime Risk Management supports shipping companies to operate more safely by providing safety recommendations based on insights from the wider industry. This ...

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AI may be grabbing the headlines, but for many people in financial services, it is simply another data ethics use case. Data ethics provides a framework for banks, insurers and card providers to use ...

Geospatial data is about places. It might be about a specific building, a river or other natural feature, or a broader location like a city or country. This report summarises the desk research carried ...

Data is the foundation of AI. Poor quality data drives up costs and can lead to hidden problems for AI, especially in complex fields like healthcare. Meanwhile, biased data negatively affects the ...