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Trustworthy AI™ framework

Bridging the ethics gap surrounding AI

Deloitte puts trust at the center of our AI approach. Helping you address ethics early, root out bias, and protect customer privacy.

An analysis of recent annual reports shows a very telling trend. According to a Wall Street Journal article, twice as many companies reported the use of artificial intelligence as a risk factor in 2018, compared with those citing it in the previous year.

 While AI can deliver exponential benefits to companies that successfully leverage its power, if implemented without ethical safeguards, it can also damage a company's reputation and future performance.

Consumers conduct transactions with organizations hundreds or thousands of times a day through actions like scrolling web pages, banking online, or calling customer service. These transactions seem free of charge, but they aren't. The currency is consumer data.

 Customers should be able to trust that the data they share will be used ethically and without bias by organizations and the AI algorithms they employ. By focusing on AI bias and emphasizing AI ethics, companies can help protect customer data—while building brand equity and customer trust.

Although we're in the early days of commercial AI regulation, organizations shouldn't sit by and wait for others to create a roadmap. To do that could mean missing out on the gains made possible by AI. 

Instead, an organization's board of directors and C-suite should view ethical AI as an imperative that can't be ignored. To tackle this challenge, C-suite leaders can leverage a Trustworthy AI™ framework that promotes the ethical use of AI and sustains the trust of customers and employees alike.

Deloitte’s Trustworthy AI™ framework

We put trust at the center of everything we do. We use a multidimensional AI framework to help organizations develop ethical safeguards across seven key dimensions—a crucial step in managing the risks and capitalizing on the returns associated with artificial intelligence.

Trustworthy AI™ requires governance and regulatory compliance throughout the AI lifecycle from ideation to design, development, deployment and machine learning operations (MLOps) anchored on the seven dimensions in Deloitte's Trustworthy AI™ framework—transparent and explainable, fair and impartial, robust and reliable, respectful of privacy, safe and secure, and responsible and accountable. At its foundation, AI governance encompasses all the above stages, and is embedded across technology, processes and employee trainings. This includes adhering to applicable regulations, as it prompts risk evaluation, control mechanisms, and overall compliance. Together, governance and compliance are the means by which an organization and its stakeholders ensure AI deployments are ethical and can be trusted.

User privacy is respected, and data is not used or stored beyond its intended and stated use and duration; users are able to opt-in / out of sharing their data.

Users understand how technology is being leveraged, particularly in making decisions; these decisions are easy to understand, auditable, and open to inspection.

The technology is designed and operated inclusively in an aim for equitable application, access, and outcomes.

The technology is created and operated in a socially responsible manner.

Policies are in place to determine who is responsible for the decisions made or derived with the use of technology.

The technology produces consistent and accurate outputs, withstands errors, and recovers quickly from unforeseen disruptions and misuse.

The technology is protected from risks that may cause individual and / or collective physical, emotional, environmental, and / or digital harm.

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Six pillars of Trustworthy AI™

Want to sustain the trust of employees and customers? You should address six critical AI dimensions to help safeguard AI ethics and build a Trustworthy AI™ strategy. Take a closer look at these dimensions—and see how our framework helps identify issues related to AI bias and ethics so you can address them at every stage of the AI lifecycle.

Explore the framework

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Irfan Saif

Irfan Saif

US Board of Directors, DTTL (Global) Board of Directors
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Nitin Mittal

Nitin Mittal

Global Strategy, Analytics and M&A Leader | Consulting
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Beena Ammanath

Beena Ammanath

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Jon Raphael

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Brian Cassidy

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