Abstract
AbstractThis chapter reviews the technological solutions that organizations leverage to ensure the ethical management and downstream use of collected data for building analytic and AI models. Survey respondents discussed solutions that ranged from privacy preserving data management strategies such as differential privacy, to the use of virtualization and data lake control systems for secure access. Survey respondents also keyed in on the clear and pressing need for data and algorithmic auditing technology and systems to support ethical data governance. With respect to how such data is used ethically, respondents identified the importance of algorithmic fairness as well as model transparency as essential to help identify and also mitigate risks associated with real world modeling failures.
Publisher
Springer International Publishing
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