David Hand is Emeritus Professor of Mathematics and a Senior Research Investigator at Imperial College, London. He is a Fellow of the British Academy and a former President of the Royal Statistical Society. He has received many awards for his research, including the Guy Medal of the Royal Statistical Society, the Box Medal from the European Network for Business and Industrial Statistics, and the International Research Medal of the IFCS. His 31 books include Principles of Data Mining, Artificial Intelligence Frontiers in Statistics, The Improbability Principle, and The Wellbeing of Nations. His recent book, Dark Data, deals with the challenges for statistics, machine learning, and AI arising from incomplete and distorted data. David is also a co-founder of the Validate AI initiative.
Shakeel Khan is a co-founder and CEO of the Validate AI community interest company. He has been a great advocate of Artificial Intelligence supporting capability building in HMRC as well as sharing his expertise across government departments and tax administrations globally over the last decade. Prior to this he worked in Financial Services leading some major supervised and unsupervised machine learning initiatives for 10 years. In the last six years he has worked closely with academics with extensive tacit industry knowledge to develop a novel Data Science Masterclass program. His extensive experience across private, public and academic sectors has also enabled him to action the triple helix model approach.
With the increasing adoption of AI systems in all aspects of our life, it has become critically important to be confident that they perform in a safe, reliable, timely, and trustworthy way. The Validate AI initiative explores how such systems can depart from this ideal, examining tools and methods for ensuring sound and appropriate behaviour in a variety of different application domains. Issues explored include accurate and unbiased performance and its evaluation, model testing and formal verification, ensuring resilience against adversarial attacks, and the effective maintenance of systems as their working environment changes.
This includes the need for AI systems to be properly formulated; that the system must be bug free, be based on properly representative data, and can cope with anomalies and data quality issues; and that its output is sufficiently accurate for the task. These considerations will be described at this seminar.
We would be keen for volunteers from the audience to join the validate AI initiative to help us to formulate appropriate practitioner centric standards to ensure more trustworthy AI.
Further information about Validate AI and the upcoming VAI21 conference can be found at: www.validateai.org
Validating and Verifying AI Systems
Patterns Magazine, Cell Press, Patterns 1, June 12, 2020
David J. Hand and Shakeel Khan,
Department of Mathematics, Imperial College, London, UK
Chief Data Officer’s team, Her Majesty’s Revenue and Customs, London, UK
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