Data science the rising use of large datasets for analysis and decision-making is becoming of increasing interest with the growth of new data sources and increased computing power.
As a result, the ethical significance of data science, and the implications for industries and the wider public, is constantly evolving.
As data science methods become more common practice within statistical and actuarial fields, there are both opportunities and challenges for practitioners. Given these challenges and opportunities, the Royal Statistical Society (RSS) Data Science Section and the IFoA partnered to consider the practical and ethical implications of data science. They established a Joint Data Science Focus Group, which developed a practical guide for RSS and IFoA members, as well as data science practitioners, on the ethical use of data science. The guide was developed through engaging with practitioners around the UK, and builds upon existing tools and frameworks.
This guide focuses on five broad principles of data ethics and ways of considering these within data science work: avoiding harm, supporting the value of data science for society, maintaining professional competence, increasing trustworthiness and maintaining accountability and oversight.
John Taylor, president of the IFoA, and Deborah Ashby, president of the RSS (see interview, p14), said: "By seeking to bring the core professional values and our commitment to the public interest, which lies at the heart of our respective professions to the field of AI and data science, our goal is to build public trust in the work that our members undertake through the application of data ethics.
"Created with practitioners in mind, this guide seeks to provide practical support to members on ethical practice. Structured around our five core ethical themes, the guide provides examples of common ethical challenges in the field and how they could be applied. We also provide a wealth of reference material, with links to a wide range of online tools, legal and regulatory reference points and a host of other practical resources on our websites.
"Although we're sure that ethical theory and practice will continue to evolve in this fast-changing field, we're pleased to be able to offer a strong framework for that evolution that aims to support the work of our members, maximise the benefits inherent in data science and protect the public interest."
The guidance is freely available online at: bit.ly/2nKhG8E
