Assessment Framework for Algorithmic Impact: AIA Outline
The National Medical Imaging Platform (NMIP) dataset, managed by the NHS AI Lab team, is accessible to project teams who have completed an Algorithmic Impact Assessment (AIA). Here's a guide to help you navigate the AIA process.
The AIA, a document hosted on Google Docs, is a prerequisite for accessing the NMIP dataset. It is used by the NHS AI Lab team to evaluate the potential impacts of deploying AI systems, focusing on transparency, data privacy, bias, safety, and compliance with relevant laws and ethics standards.
Completing an AIA typically involves describing the AI system’s purpose and scope, the datasets involved, the potential risks, and mitigation strategies. For NHS-specific data access, such as NMIP imaging datasets, adherence to NHS data governance, patient confidentiality, and ethical use standards is essential.
To ensure a successful AIA, follow these key points:
- Clearly articulate the AI algorithm’s clinical use case.
- Provide a detailed description of data sources and protection methods.
- Identify and mitigate any algorithmic biases or risks.
- Comply with NHS and legal data protection standards.
- Commit to transparency and ongoing oversight.
For a more comprehensive understanding of the AIA process, consult the NHS AI Lab resources and AI knowledge repository, NHS Digital data governance frameworks for AI applications involving clinical data, and guidance on AI tech adoption in NHS, such as those by NICE.
In case you cannot find a specific AIA template guide, contacting the NHS AI Lab directly or accessing their official documentation portal would be the recommended next step. The full report on the AIA project in healthcare can be accessed through a project page.
Remember, the AIA process is part of a wider collaboration between the NHS AI Lab and other entities, focusing on AIAs in healthcare. By following these guidelines, you're taking a significant step towards responsible AI adoption and gaining access to the valuable NMIP dataset.
The AIA process, crucial for accessing the NMIP dataset, requires a clear articulation of the AI algorithm's clinical use case in health-and-wellness, as well as a detailed description of data sources and protection methods in science and technology. Furthermore, identifying and mitigating algorithmic biases or risks is essential in this process for the ethical use of NHS-specific data, especially imaging datasets.
