Trusted Data Revised and Expanded Edition

<b>How to create an Internet of Trusted Data in which insights from data can be extracted without collecting holding or revealing the underlying data.</b><p><i>Trusted Data</i> describes a data architecture that places humans and their societal values at the center of the discussion. By involving people from all parts of the ecosystem of information this new approach allows us to realize the benefits of data-driven algorithmic decision making while minimizing the risks and unintended consequences. It proposes a software architecture and legal framework for an Internet of Trusted Data that provides safe secure access for everyone and protects against bias unfairness and other unintended effects. This approach addresses issues of data privacy security ownership and trust by allowing insights to be extracted from data held by different people companies or governments without collecting holding or revealing the underlying data. The software architecture called Open Algorithms or OPAL sends algorithms to databases rather than copying or sharing data. The data is protected by existing firewalls; only encrypted results are shared. Data never leaves its repository. A higher security architecture ENIGMA built on OPAL is fully encrypted.</p><p><b>Contributors<br></b>Michiel Bakker Yves-Alexandre de Montjoye Daniel Greenwood Thomas Hardjoni Jake Kendall Cameron Kerry Bruno Lepri Alexander Lipton Takeo Nishikata Alejandro Noriega-Campero Nuria Oliver Alex Pentland David L. Shrier Jacopo Staiano Guy Zyskind</p><p>An MIT Connection Science and Engineering Book</p>