How values-based AI is good for your business
Safer and more accountable products
Advanced technologies are most successful when everyone can benefit from them. Evaluating your AI systems, both when they perform as intended and when they don’t, is crucial to building accountable products.
Earn and keep your customers' trust
Lack of trust in AI systems is a growing barrier to adoption in enterprise with more organizations selecting enterprise products based on AI commitments and practices. A responsible AI approach earns trust.
A culture of responsible innovation
Empowering AI decision-makers and developers to take ethical considerations into account enables them to find new, innovative ways to drive your mission forward.
Learn more about our
perspectives on issues and AI governance
at Google and how we work to
build responsible AI for everyone.
Learn more about our perspectives on issues and AI governance at Google and how we work to build responsible AI for everyone.
Google Cloud’s approach to responsible AI
Since 2018, Google’s AI Principles have served as a living constitution, keeping us motivated by a common purpose. Our center of excellence, the Responsible Innovation team, guides how we put these principles to work company-wide, and informs Google Cloud’s approach to building advanced technologies, conducting research, and drafting our policies.
Putting principles into practice
Rigorous evaluations are a critical component of building successful AI. To drive alignment with our AI Principles at Google Cloud, two diverse review bodies undertake deep ethical analyses and risk and opportunity assessments for any technology product we build and early-stage deals involving custom work. Learn more.
Tools and education
Responsible AI tools are an increasingly effective way to inspect and understand AI models. We’re building resources like Explainable AI, Model Cards, and the TensorFlow open-source toolkit to provide model transparency in a structured, accessible way. We share what we’re learning through Responsible AI practices, fairness best practices, technical references and tech ethics materials.
See the latest on Responsible AI
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