Responsible Generative AI
Navigate GenAI Risks
With Confidence
With the rise of GenAI, organizations must build AI systems responsibly and with proper governance. This ebook explores the risks and introduces the RAFT (Reliable, Accountable, Fair, and Transparent) framework for Responsible AI, applicable to both traditional and GenAI systems.
Refine Your GenAI Strategy Today
67% of Respondents Expect GenAI to Alter Their Market and Competitive Landscape
According to a Forrester Opportunity Snapshot — a customer study conducted by Forrester Consulting on behalf of Dataiku — 67% of respondents believe that GenAI will dramatically reshape their market dynamics and competitive landscape, driving significant changes in how businesses compete and innovate.
To navigate these changes responsibly, it's crucial to address the complexities of GenAI. Learn how to mitigate challenges like toxicity, data privacy, and model security by applying the RAFT framework, ensuring your AI deployments are ethical and effective.
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(1).jpg)
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(2).jpg)
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(4).jpg)
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(5).jpg)
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(7).jpg)
.jpg?width=500&height=500&name=GenAI%20Logos%20Hubspot-High-Quality%20(11).jpg)
Introducing the RAFT Framework
Discover RAFT for Responsible AI Design, Deployment, and Governance
Risks of
Generative AI
Mitigate the challenges posed by Generative AI, such as toxicity, discrimination, and data privacy issues to ensure Responsible AI implementation.
Concerns Based on Expected Audience
Establish clear criteria for reliability and transparency to ensure trust in AI systems for all audiences, including business users and consumers.
Potential Impacts of AI
Putting Principles Into Practice
Adapt the RAFT framework to meet industry requirements and local regulations, ensure data privacy and reliability with third-party models, and more.
“It’s also important to recognize that the risks posed by GenAI are only one part of a broader Responsible AI program. Responsible AI is an approach that aligns the output of AI with an organization’s values by proactively building systems that are reliable, accountable, fair, and transparent. Together, these comprise the RAFT framework for Responsible AI.”