Data science created unprecedented opportunities but also new risks. Data Science techniques might expose sensitive traits of individuals and invade their privacy, and this information could be used to discriminate people based on their presumed characteristics, or profiles. Gartner stated that, within 2018, half of business ethics violations will occur through improper use of Big Data analytics. Often, the achievements of data science are the result of re-interpreting available data for analysis goals that differ from the original reasons motivating data collection. Examples include mobile phone call records, originally collected by telecom operators for billing and operations, used for accurate and timely demography and human mobility analysis at country or regional scale. This re-purposing of data clearly shows the importance of legal compliance and data ethics technologies and safeguards to protect privacy and anonymity, secure data, engage users, avoid discrimination and misuse, account for transparency - to the purpose of seizing the opportunities of data science while controlling the associated risks. We discuss the most impactful data-privacy research results at SoBigData.eu, focusing on two lines: i) our privacy-by-design framework for big data analytics, based on a practical methodology for evaluating and managing the privacy risk associated to sharing specific datasets, and ii) a novel user-centric model for personal data analytics, aimed at empowering users to control and use own data and boosting individual and collective awareness.

Invited talk by Fosca Giannotti.