Big Data Privacy and Ethical Challenges

Abstract

Big data is a complex phenomenon of technical advances in storage capacity, computational speed, the low cost of data collection and predictive analytics. Artificial Intelligence (AI) is a key to unlocking the value of big data, and machine learning underpins and facilitates AI. All three concepts combine to result in big data analytics, the properties of which challenge compliance with information privacy principles that have led to recent significant legislative changes in data protection. Further, the use of profiling and automated decision-making made possible by machine learning and AI go well beyond privacy protections and will require ethical oversight. Personal data protection regimes, like the European Union General Data Protection Regulation, are instruments for governance of data flows and remain valuable for classical data processing. Yet they may be inadequate to address the unprecedented challenges raised by big data. New digital geopolitics created by differences in data protection rules across national borders no longer represent the limits of data flows, and the consequences for global governance are significant. There is rising consensus that a digital ethics framework is needed to provide modern terms for identifying, analyzing and communicating new human realities with existing and foreseeable technological changes.