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Lessons in practical AI ethics

Posted 1 May 2020

AI ethics receives a lot of attention and interest from startup communities and industry in general. Despite this interest and a general upward trend in companies wanting to be more conscientious and transparent, there has been a gap between intent and practical action.

Machine Intelligence Garage – Digital Catapult’s flagship AI acceleration programme – provides the innovation community with access to computational power, alongside business and investment support. While supporting startups in growing and developing their solutions, it’s also important that they have the resources, advice and guidance to be able to do so responsibly and ethically.

In response to the evident need for guidance, Digital Catapult has created an applied and practical methodology for machine learning ethics, designed for businesses and individuals wanting to adopt an ethical and responsible approach to their machine learning development. This methodology is based on four pillars – initiatives which have grown from Digital Catapult’s existing approach to practical AI ethics, and which address the gap between the conceptualisation and application of ethics for machine learning.

This report provides an overview of practical AI ethics, providing context, describing the activities involved and summarising findings from these initiatives to date.