Once you've established a strong foundation by assessing the vendor, it's time to examine the heart of the technology: the AI model itself. Understanding its capabilities, transparency, robustness, and potential biases is crucial to assess its suitability for your organization. By delving into these technical aspects, you can better understand the potential benefits and risks associated with the AI solution.
Understand the AI Technology and Its Capabilities
- Develop a working knowledge of theunderlying AI algorithms, models, and techniques used by the vendor.
- Define how AI will be used within your organization and evaluate the ability of the vendor's technology to complete those tasks.
- Understand the AI system's accuracy, precision, recall, and other relevant metrics.
Assess the AI Model's Transparency
- Determine the degree to which the AI's decision-making process can be understood (black box vs. white box).
- Evaluate the potential for bias in the AI model's development and output.
- Ensure the vendor provides adequate documentation on the AI model's development and testing.
Evaluate the AI System's Robustness and Resilience
- Assess the quality and reliability of the data used to train the AI model.
- Understand how the AI system handles errors and unexpected inputs.
- Evaluate the vendor's testing and validation processes.
By thoroughly understanding the AI technology, healthcare organizations can make informed decisions about its suitability and potential impact. In the next post, we will explore how to protect sensitive patient data by focusing on data privacy and security when selecting an AI vendor.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.