We present PolicyCLOUD: a prototype for an extensible serverless cloud-based system that supports evidence-based elaboration and analysis of policies. PolicyCLOUD allows flexible exploitation and management of policy-relevant dataflows, by enabling the practitioner to register datasets and specify a sequence of transformations and/or information extraction through registered ingest functions. Once a possibly transformed dataset has been ingested, additional insights can be retrieved by further applying registered analytic functions to it. PolicyCLOUD was built as an extensible framework toward the creation of an analytic ecosystem. As of now, we have developed several essential ingest and analytic functions that are built-in within the framework. They include data cleaning, enhanced interoperability, and sentiment analysis generic functions; in addition, a trend analysis function is being created as a new built-in function. PolicyCLOUD has also the ability to tap on the analytic capabilities of external tools; we demonstrate this with a social dynamics tool implemented in conjunction with PolicyCLOUD, and describe how this stand-alone tool can be integrated with the PolicyCLOUD platform to enrich it with policy modeling, design and simulation capabilities. Furthermore, PolicyCLOUD is supported by a tailor-made legal and ethical framework derived from privacy/data protection best practices and existing standards at the EU level, which regulates the usage and dissemination of datasets and analytic functions throughout its policy-relevant dataflows. The article describes and evaluates the application of PolicyCLOUD to four families of pilots that cover a wide range of policy scenarios.

This article consists of two parts. The first part is a review of the book entitled, ‘The Ethical Algorithm: The Science of Socially Aware Algorithm Design’, written by Professors Michael Kearns and Aaron Roth of the Computer and Information Science Department, University of Pennsylvania. The book was published in 2019 by Oxford University Press. The second part consists of thoughts learned from the book and how they could be applied to the work of legal information management professionals when facing tasks related to the ethical algorithms in artificial intelligence (AI) and robotics. How online privacy continues to be the main concern in the AI and robot era will be discussed, as well as the rise of concerns over AI and robots and how they might make unfair decisions toward vulnerable populations which could then become acts of discrimination. Examples of real-world problems of AI and robotics are also noted in this article.

This article considers recent ethical topics relating to medical AI. After a general discussion of recent medical AI innovations, and a more analytic look at related ethical issues such as data privacy, physician dependency on poorly understood AI helpware, bias in data used to create algorithms post-GDPR, and changes to the patient–physician relationship, the article examines the issue of so-called robot doctors. Whereas the so-called democratization of healthcare due to health wearables and increased access to medical information might suggest a positive shift in the patient-physician relationship, the physician’s ‘need to care’ might be irreplaceable, and robot healthcare workers (‘robot carers’) might be seen as contributing to dehumanized healthcare practices.