Essential Work Samples for Evaluating AI Project Risk Assessment Skills

AI project risk assessment has become a critical competency as organizations increasingly deploy artificial intelligence systems across their operations. The ability to identify, evaluate, and mitigate risks associated with AI implementations can mean the difference between a successful deployment and one that results in reputational damage, financial loss, or ethical concerns. As AI systems become more complex and ubiquitous, the need for professionals who can effectively assess and manage these risks grows exponentially.

Evaluating a candidate's AI risk assessment capabilities through traditional interviews alone is insufficient. While candidates may articulate theoretical knowledge of risk frameworks or cite previous experience, these verbal accounts don't necessarily demonstrate their practical ability to identify subtle risks, develop mitigation strategies, or communicate effectively with stakeholders about complex technical concerns.

Work samples provide a window into how candidates approach AI risk assessment in realistic scenarios. They reveal a candidate's thought process, technical understanding, ethical awareness, and communication skills—all critical components of effective risk management. By observing candidates working through actual risk assessment challenges, hiring managers can gain confidence in their ability to protect the organization while enabling innovation.

The following exercises are designed to evaluate different dimensions of AI risk assessment competency. They range from framework development to bias identification, stakeholder communication, and regulatory compliance. Together, they provide a comprehensive view of a candidate's readiness to take on AI risk assessment responsibilities in your organization.

Activity #1: AI Risk Framework Development

This exercise evaluates a candidate's ability to develop a structured approach to AI risk assessment. It tests their understanding of AI systems, potential failure modes, and methodical risk categorization—essential skills for anyone responsible for AI project risk assessment. The activity reveals how candidates organize complex information and prioritize different types of risks.

Directions for the Company:

• Provide the candidate with a brief description of a fictional AI project (e.g., a customer service chatbot, an automated loan approval system, or a predictive maintenance algorithm).
• Include key details such as the data sources, intended use cases, stakeholders, and business objectives.
• Allow 45-60 minutes for this exercise.
• Provide access to a whiteboard (physical or digital) or document editor for the candidate to create their framework.
• Consider having a technical team member present who can answer clarifying questions about the fictional AI system.

Directions for the Candidate:

• Review the AI project description provided.
• Develop a comprehensive risk assessment framework specific to this project that includes:
• Categories of risks to evaluate (technical, ethical, regulatory, business, etc.)
• Key questions to ask for each risk category
• Metrics or indicators to measure each risk
• Suggested documentation requirements
• A process for ongoing risk monitoring
• Create a visual representation of your framework that could be used by a cross-functional team.
• Be prepared to explain your rationale for including specific elements and how you would implement this framework.

Feedback Mechanism:

• After the candidate presents their framework, provide feedback on one strength (e.g., comprehensive coverage of ethical considerations) and one area for improvement (e.g., lack of specific technical failure modes).
• Ask the candidate to revise one section of their framework based on your feedback, giving them 10-15 minutes to make adjustments.
• Observe how receptive they are to feedback and how effectively they incorporate it into their revised framework.

Activity #2: AI Bias Identification and Mitigation

This exercise tests a candidate's ability to identify potential biases in AI systems and develop practical mitigation strategies. It evaluates technical understanding of how bias manifests in algorithms and data, as well as creativity in addressing these issues—crucial skills for protecting against discriminatory outcomes in AI deployments.

Directions for the Company:

• Prepare a dataset summary and model description that contains potential bias issues. For example:
• A hiring algorithm trained primarily on data from male employees
• A facial recognition system with imbalanced demographic representation
• A credit scoring model using proxies for protected characteristics
• Include relevant visualizations or statistics that hint at the bias issues without explicitly pointing them out.
• Provide access to a computer with basic data analysis tools if the exercise involves examining actual data.
• Allow 45 minutes for this exercise.

Directions for the Candidate:

• Review the provided dataset summary and model description.
• Identify at least three potential sources of bias in the AI system.
• For each identified bias:
• Explain how it might impact different stakeholders
• Propose specific technical and procedural methods to mitigate the bias
• Suggest metrics to verify that your mitigation strategies are effective
• Create a one-page summary of your findings and recommendations that could be presented to both technical and non-technical stakeholders.
• Be prepared to discuss the tradeoffs between model performance and fairness in your proposed solutions.

Feedback Mechanism:

• Provide feedback on the comprehensiveness of the candidate's bias identification and the practicality of their mitigation strategies.
• Highlight one bias source they may have missed or one mitigation strategy that could be strengthened.
• Give the candidate 10 minutes to revise their recommendations based on this feedback.
• Evaluate their ability to quickly incorporate new perspectives and refine their approach.

Activity #3: AI Risk Stakeholder Communication Role Play

This role play assesses a candidate's ability to communicate complex AI risks to different stakeholders—a critical skill for ensuring organizational alignment and support for risk mitigation efforts. It evaluates how well candidates can translate technical concerns into business language and adapt their communication style to different audiences.

Directions for the Company:

• Prepare a scenario involving an AI system with significant identified risks that need to be communicated to stakeholders.
• Create brief profiles for three different stakeholders: a C-level executive (e.g., CEO or CFO), a legal/compliance officer, and a product manager.
• Assign team members to play each stakeholder role with specific concerns and questions relevant to their position.
• Provide the candidate with a summary of the AI system, the identified risks, and brief stakeholder profiles 30 minutes before the exercise.
• Allow 30 minutes for the role play (approximately 10 minutes per stakeholder).

Directions for the Candidate:

• Review the AI system description, risk assessment findings, and stakeholder profiles provided.
• Prepare a brief (2-3 minute) initial explanation of the key risks for each stakeholder, tailored to their role and likely concerns.
• During the role play:
• Clearly communicate the nature and severity of the risks
• Adapt your language and focus based on each stakeholder's role
• Recommend appropriate next steps or mitigations
• Answer questions and address concerns raised
• Be prepared to handle pushback or resistance, especially when risks might impact business objectives or timelines.
• Your goal is to ensure each stakeholder understands the risks and supports necessary mitigation actions.

Feedback Mechanism:

• After the role play, provide feedback on the candidate's communication effectiveness with one specific stakeholder.
• Highlight what worked well and suggest one specific improvement in their communication approach.
• Ask the candidate to re-do their interaction with this stakeholder, incorporating the feedback.
• Evaluate how well they adapt their communication style based on feedback.

Activity #4: AI Regulatory Compliance Mapping

This exercise evaluates a candidate's knowledge of AI regulations and their ability to apply this knowledge to specific projects. It tests their understanding of the evolving regulatory landscape and their skill in translating abstract requirements into concrete project actions—essential for ensuring AI deployments remain compliant with relevant laws and standards.

Directions for the Company:

• Create a description of an AI project that spans multiple jurisdictions or industries (e.g., a healthcare AI system to be deployed in both the EU and US).
• Provide a list of relevant regulations and standards that might apply (e.g., GDPR, HIPAA, FDA regulations, AI Act, industry-specific guidelines).
• Include a project timeline with key development and deployment milestones.
• Prepare a template for the compliance mapping document.
• Allow 45-60 minutes for this exercise.

Directions for the Candidate:

• Review the AI project description and the list of potentially applicable regulations.
• Create a compliance mapping document that:
• Identifies which regulations apply to this specific AI system and why
• Maps specific regulatory requirements to project development stages
• Highlights potential compliance conflicts between different jurisdictions
• Recommends documentation and evidence needed to demonstrate compliance
• Suggests 3-5 key risk mitigation actions to ensure regulatory compliance
• Prioritize the compliance requirements based on risk level and implementation complexity.
• Be prepared to explain your rationale for these priorities and how you would integrate compliance activities into the project timeline.

Feedback Mechanism:

• Provide feedback on the comprehensiveness of the regulatory mapping and the practicality of the implementation recommendations.
• Point out one regulatory consideration they may have overlooked or misinterpreted.
• Give the candidate 15 minutes to revise their compliance mapping based on this feedback.
• Evaluate their regulatory knowledge and their ability to quickly incorporate new regulatory considerations into their planning.

Frequently Asked Questions

How long should we allocate for these work samples in our interview process?

Each of these exercises is designed to take 45-60 minutes, including time for setup, execution, feedback, and revision. If you're incorporating multiple exercises, consider spreading them across different interview stages or condensing them to focus on specific aspects most relevant to your organization's needs.

Should we provide these exercises to candidates in advance?

For the Framework Development and Regulatory Compliance exercises, providing the basic scenario 24-48 hours in advance can yield more thoughtful responses. However, the Bias Identification and Stakeholder Communication exercises are better conducted with minimal advance preparation to assess the candidate's ability to think on their feet.

How technical should our AI project descriptions be for these exercises?

The project descriptions should include enough technical detail to make the exercise realistic but not so complex that candidates spend most of their time understanding the system rather than demonstrating their risk assessment skills. Include information about the model type, data sources, intended use, and deployment context.

What if a candidate identifies risks or regulatory requirements we hadn't considered?

This is actually a positive outcome! One purpose of these exercises is to evaluate a candidate's ability to identify risks your team might have missed. Use this as an opportunity to assess the validity of their insights and their potential value to your organization.

How should we evaluate candidates who have experience in different industries or with different AI technologies?

Focus on the candidate's risk assessment process and reasoning rather than specific industry knowledge. Strong candidates should be able to ask clarifying questions and adapt their approach to unfamiliar contexts, demonstrating transferable risk assessment skills.

Can these exercises be conducted remotely?

Yes, all of these exercises can be adapted for remote interviews using video conferencing, collaborative documents, and digital whiteboards. For the role play exercise, ensure all participants have stable internet connections and consider a practice run with your internal team before using it with candidates.

Effective AI risk assessment is a multifaceted skill that combines technical understanding, ethical awareness, regulatory knowledge, and communication abilities. By incorporating these work samples into your hiring process, you'll gain deeper insights into candidates' practical capabilities beyond what traditional interviews reveal. This approach not only helps you identify the most qualified candidates but also demonstrates your organization's commitment to responsible AI development and deployment.

For more resources to enhance your AI hiring process, explore Yardstick's suite of tools, including our AI job descriptions generator, interview question generator, and comprehensive interview guide creator.

Ready to build a complete interview guide for assessing AI project risk assessment skills? Sign up for a free Yardstick account today!