checklist
Questions to ask when assessing AI-technology
Artificial intelligence (AI) is transforming the way organizations operate, automating processes to enhance efficiency and providing insight for workforce optimization and better overall management of contingent talent.
Many companies have implemented a governance program with policies that control the use of AI-powered solutions, including those used for contingent workforce management. Utilizing AI assessments can help organizations ensure the AI is reliable, ethical, and compliant - ultimately fostering trust and accountability.
As you evaluate AI technology, the following questions will help you gain a deeper understanding of the provider’s expertise and approach to their AI solutions so you can make more informed decisions.
Use case overview
- What is the purpose of the AI solution/use case?
- How will the proposed solution/product/tool be used?
- Describe the current process/business problem.
- What kind of outputs are expected?
- What data inputs are processed by the model?
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How will the output be used by the users?
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Will there be any automation of hiring or selection decisions?
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How will generated output be verified? Will there be a human in the loop?
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Does the proposed solution include an AI-based solution vendor?
Questions to ask your vendor:
Provide vendor name and an overview of the technology stack.
- Where will my data be stored?
- What is your AI solution’s core technology and architecture (e.g., ChatGPT/OpenAI, Claude/ Anthropic, etc.)?
- Where are your models hosted?
- How do you handle model updates (additional training) and maintenance?
- How does the vendor perform model validation testing?
- Do you have a formal data policy in place that ensures privacy and security of any sensitive data collected or used by the AI system?
- How does your AI solution mitigate against inaccurate, biased, or unrepresented outputs?
- How is your AI model updated and improved over time?
You can be confident knowing Beeline’s AI-powered solutions are developed responsibly and deliberately based on three guiding principles
- Ethics and compliance: Beeline AI must comply with laws and with respect for the companies and individuals we serve
- Trust: Beeline AI models are built from accurate ground truths with explainable outcomes and bias and error monitoring
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Human in the loop: Beeline AI supplements, but does not replace, human decision-making