This paper outlines the spectrum of AI technology, from rules-based and symbolic AI to advanced, developing forms of neural networks.
This discussion paper looks at the implications of big data, artificial intelligence (AI) and machine learning for data protection, and explains the ICO’s views on these
In this blog, ICO explores some of the most relevant techniques for supervised Machine Learning (ML) systems, which are currently the most common type of AI in use.
European Parliament’s Think Tank has published AI ethics. This study arrives at policy options for public administrations and governmental organisations who are looking to deploy AI/ML solutions, as well as the private companies who are creating AI/ML solutions for use in the public arena. The reasons for targeting this application sector concern: the need for […]
The paper provides clear instructions on how to fulfill the DPbD obligation and how to build a DPbD strategy in line with data protection principles.
This short whitepaper aims to create the beginnings of a framework for best practices standards by focusing on specific privacy and security vulnerabilities within ML systems. At present, we view these vulnerabilities as warning signs—either of a future in which the benefits of ML are not fully embraced, or a future in which ML’s liabilities […]
This guide explains the technological basics of AI and ML systems at a level of understanding useful for non-programmers, and addresses certain privacy challenges associated with the implementation of new and existing ML-based products and services.