The digital economy is built on data—massive streams of data being created, collected, combined and shared—for which traditional governance frameworks and risk-mitigation strategies are insufficient. In the digital age, analyzing and acting on insights from data can introduce entirely new classes of risk. These include unethical or even illegal use of insights, amplifying biases that exacerbate issues of social and economic justice, and using data for purposes to which its original disclosers would not have agreed, and without their consent. These and other practices can permanently damage consumer trust in a brand.
In the past, the scope for digital risk was limited to cybersecurity threats but leading organizations must now also recognize risks from lackluster ethical data practices. Mitigating these internal threats is critical for every player in the digital economy, and cannot be addressed with strong cybersecurity alone.
Accenture Labs launched a research collaboration with leading thinkers on data ethics to help provide guidelines for security executives and data practitioners and enable development of robust ethical controls throughout data supply chains.
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New risks and challenges in the digital economy extend to various types of automation that are powered by data insights. Sense and respond (S&R) systems have been in use for decades, responding to their environment in real time with little or no human input.
As the prevalence and decision-making capabilities of S&R systems continue to increase, there’s potential for ethical failures with wider impact. If ethics are not properly considered during S&R design, implementation, and use, they can propagate unwanted biases and erode human trust in both the systems and the organizations that deploy them. Practitioners designing S&R systems that will become a key part of consumer life must take these risks into account.
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Data is the lifeblood of the digital economy, and data sharing has become an essential practice, enabling new insights as broader business ecosystems propagate. Yet, new risks loom that require attention from the leaders of any organization that engages in data sharing, aggregating or analytics. We examine a best-practice approach for data sharing to ensure ethics are properly considered and risks are appropriately identified and mitigated.
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