RSS Merseyside Local Group: Ethics and Biases in AI and Machine Learning

As growth in the use of machine learning continues, we will rely on automated predictive systems more and more. AI-informed decision making has the potential to revolutionise healthcare, social support, education and many other aspects of everyday life. However, if using inappropriate data or careless methodology, these systems can inadvertently reproduce or worsen existing inequalities. These talks will explore how to avert harmful biases and create a more ethical future with AI.

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Dr Allison Gardner (Keele University): "Ethical Funding for Trustworthy AI: Hit them where it hurts"

Despite several years of fevered activity in the AI ethics arena, with high level principles, standards, regulation and frameworks we still see AI systems developed that prove to be biased and unfair. Looking at the accountability pathway this project places a lens at the very beginning of the developer journey, at funding. What responsibility do funders have to assure that the projects they fund are trustworthy and ethically designed. The EFTAI project addresses this gap by proposing a framework for the funding for ethical AI. A year after publication the talk will update on the positive outcomes thus far.

Allison Gardner is an expert in AI and Data Ethics with interests in health technology, algorithmic bias, HCI, diversity and inclusion. She is an experienced educator and is an (Hon) Senior Research Fellow at Keele University. She co-founded Women Leading in AI and is CEO of AI Aware Ltd. Allison sits on a number of standards committee including ISO/IEC SC42 UK National and CEN-CENELEC JTC21 as a ForHumanity Fellow. Allison is a renowned speaker on AI ethics, with several media appearances including as a TEDx speaker.

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Dr Mavis Machirori (Ada Lovelace Institute): "The bias pathway in AI and machine learning – what can health and data teach us?"

Mavis Machirori is a Senior Researcher at the Ada Lovelace Institute, leading on the Health and Covid19 Technologies programme. Her work interrogates data-driven and genomic technologies, legacies on society and their impacts on health and social inequalities. Mavis has extensive clinical background in midwifery, and social research expertise, drawing on a range of disciplines such as medical anthropology and sociology. She gained a PhD in Health Studies Research at King’s College London and has since worked on governance and use of health and genomic data. She is particularly interested in the long-term legacies of digital health technologies on society, inequalities and how to align data and tech policy and practice with public expectations. Mavis was previously a member of the World Economic Forum Future Council on Biotechnology and is a current Visiting Researcher at Newcastle University’s Policy, Ethics and Life Sciences Research Centre.