Why do you need a responsible AI strategy?
While 84% of companies agree that Responsible AI & Ethics should be a top mannagement priority, only 16% have a fully mature program. True leaders in AI recognize that not only are responsible practices the key to success, but that it requires a holistic cross-organizational approach to achieve.
28%
Companies with mature and holistic Responsible AI programs reduce the risk of AI failure rates up to 28%
50%
Half of Responsible AI leaders report an increase in quality of products and services as a result of Responsible AI efforts
48%
In addition to product quality, 48% of Responsible AI leaders experience enhanced brand differentiation
43%
In addition to risk mitigation and regulation readiness, 43% of Responsible AI leaders report accelerated innovation
Responsible AI
Get the playbook on why, how, and when to use the Values Canvas to drive higher returns on your investment in artificial intelligence.
Responsible AI guides readers step-by-step through the process of establishing robust yet manageable ethical AI initiatives for any size organization, providing the insight and guidance needed to help leaders fully understand the technical and commercial potential of ethics in AI while also covering the operations and strategy needed to support implementation.
Case Studies
The Values Canvas is made up of nine different elements, each highlighting an important impact point in which you can translate your ethical values into reality. This can be achieved through a variety of strategic solutions. To help give you an idea of what a good element solution can look like, check out the Values Canvas case study series covering all nine of the elements in action.
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Establishing a clear and consistent strategic direction on how to manage ethical values in action.
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Creating a comprehensive and standard course of action for execution of ethical values and practices.
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Standardizing execution, automate processes where appropriate, and increase efficiency of Responsible AI practices at scale.
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Aligning your data lifecycle management with your ethical values so that your AI is being built on an ethically sound foundation.
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To create transparency of the ethical decisions being taken during the AI development lifecycle.
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To incrementally iterate and refine AI models into ethical value alignment through insights from people directly affected by the AI systems.
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The Values Canvas
© Olivia Gambelin 2024