A Checklist for Evaluating AI Vendors: Key Questions to Ask

When considering an AI vendor, it's essential to dig deeper than the sales pitch. You need to ensure their technology aligns with your values, protects your data, and can be tailored to your needs. Here’s a checklist of critical questions to ask AI vendors, compiled from industry best practices and designed to help you make an informed decision.

1. Data Transparency & Usage

• What data was used to train your models?
  Ask if the data includes diverse and representative samples. It's crucial to know whether it was tested for bias to ensure fair outcomes across different demographics.

• How do you handle customer data?
  Understand if your data will be retained or used for training their models. This is vital for maintaining data privacy and compliance with regulations.

2. Model and Technology Details

• What AI models do you use, and where are they applied?
  Inquire about the types of models (e.g., machine learning, LLMs) and their use cases within the application to ensure they fit your business needs.

• Do you integrate AI from other vendors?
  If so, ask what checks and balances are in place to prevent these external models from introducing biases into your application.

• Can we configure how attributes are weighted in your models?
  Flexibility is key. Ensure you have the ability to adjust model parameters to align with your internal policies and objectives.

3. Compliance and Governance

• What is your governance model for data and AI ethics?
  Ask for details on how they ensure ethical use of data and AI. This includes governance frameworks, ethical guidelines, and any third-party audits.
• How do you ensure human oversight in critical decisions?
  Understand how the system keeps humans in control, especially for high-stakes decisions. Confirm if you can influence how factors are weighed in the model’s recommendations.

4. Regulatory Compliance

• Which AI regulations apply to your product?
  AI regulations vary across regions. Ensure the vendor is compliant with laws in your operational regions, such as the USA, EU, or other applicable jurisdictions.

• How do you stay updated with global regulatory changes?
  A responsible vendor should have processes to stay abreast of evolving AI regulations and ensure ongoing compliance.

5. Performance Monitoring

• How do you monitor for performance, reliability, and bias?
  Ask about their methods for tracking the performance and fairness of their AI models. Regular monitoring is crucial for maintaining system integrity.

• Can you provide reports and audits from a reputable 3rd party?
  Access to detailed performance and bias audits helps you verify that the system operates as expected and remains compliant with your internal standards.

6. Support and Implementation

• What support do you offer for responsible implementation?
  Implementing AI responsibly can be complex. Ensure the vendor offers adequate support for integrating their solution into your enterprise.

• How can we address any issues or misunderstandings?
  A good vendor should provide resources and support channels to clarify AI functions and troubleshoot any concerns you may have.

Conclusion

Choosing the right AI vendor isn’t just about features and pricing—it’s about ensuring the technology aligns with your ethical standards and operational needs. By asking these questions, you can gain a clearer understanding of the vendor’s capabilities and commitment to responsible AI. For more insights on ethical AI practices, check out Humanly’s approach to responsible AI and governance and safety measures.

With the right questions, you can find an AI partner that not only enhances your operations but also upholds the values your organization stands for.

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