The PRIDAR Dashboard
USER FEEDBACK
....PRIDAR has revolutionised our approach to AI investment and governance.
NHS Commisioner
...we have found PRIDAR an very rewarding framework for presenting our progress internally, and with customers
NHS Solutions Provider
...it has been a pleasure to feature PRIDAR case studies on our Assurance Portal
UK Government Centre for Data Ethics and Innovation
Background
The PRIDAR framework is a tool that helps organisations make more informed and effective decisions about AI development and deployment. It does this by focusing on three key areas: Design, Assurance, and Organisational Preparedness. Here's how each area contributes to better decision-making:
By focusing on these three areas, the PRIDAR framework helps organizations to consider a wide range of factors that can impact the success of AI initiatives. This can lead to more effective decision-making, as it encourages a comprehensive and thoughtful approach to AI development and deployment. It also helps to surface potential risks and issues early on, allowing them to be addressed proactively rather than reactively.
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The PRIDAR framework is a tool that helps organisations make more informed and effective decisions about AI development and deployment. It does this by focusing on three key areas: Design, Assurance, and Organisational Preparedness. Here's how each area contributes to better decision-making:
- Design: This aspect of PRIDAR emphasizes the importance of user-led design and the use of a design sandbox. By ensuring that AI systems are designed with the needs and input of their end-users in mind, organizations can increase the likelihood that these systems will be effective and well-received. The use of a design sandbox allows for safe experimentation and testing, which can help identify and address potential issues early in the development process.
- Assurance: This aspect of PRIDAR focuses on various forms of assurance, including compliance with sector regulations, public disclosure of risks and mitigations, and adherence to relevant BSI/ISO standards. By considering these factors, organizations can ensure that their AI systems are safe, reliable, and trustworthy. This can also help to build confidence among stakeholders, including investors, customers, and regulators.
- Organizational Preparedness: This aspect of PRIDAR emphasizes the importance of having the necessary structures and agreements in place to support the successful deployment of AI. This includes defining KPIs for system use, obtaining user-to-board approval, agreeing on development and support costs at the board level, and establishing IP, information governance, and data/model/system integration agreements. By ensuring that these elements are in place, organizations can increase the likelihood that their AI initiatives will be successful and sustainable.
By focusing on these three areas, the PRIDAR framework helps organizations to consider a wide range of factors that can impact the success of AI initiatives. This can lead to more effective decision-making, as it encourages a comprehensive and thoughtful approach to AI development and deployment. It also helps to surface potential risks and issues early on, allowing them to be addressed proactively rather than reactively.
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To complete a PRIDAR Report on an AI solution complete the form below. You will need a CarefulAI Reference number to do this. If you do not have a CarefulAI Reference Number please read our Privacy Policy and complete the registration from shown here. We will then send you a CarefulAI reference number by email. On submission of a PRIDAR form the risk profile of an AI Solution relative to others used by a customer will become apparent.
