AI Project Impact Assessment Template
One of the most important ways to operationalize AI within your business is to assess the risk associated with each AI project or use case. In addition, evaluate the impact of those projects for the company, customers, individuals and beyond.
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You can leverage this template as a starting point to conduct your assessments.
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AI Project Impact Assessment
Project Name: __________________________
Project Owner: __________________________
Date: __________________________
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Project Overview
1.1. Project Description
Provide a brief description of the project, including the purpose and objectives of the AI system being developed or implemented.
1.2. Project Scope
Outline the scope of the project, including the specific AI technologies being used, the intended users, and the target audience.
1.3. Project Timeline
Provide an estimated timeline for the project, including key milestones and implementation dates.
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2. Ethical and Legal Considerations
2.1. Compliance with Laws and Regulations
Identify the relevant laws and regulations applicable to the project and describe how the AI system will comply with these requirements.
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2.2. Ethical Principles
Discuss how the project aligns with the organization’s AI Ethics Policy and the ethical principles outlined therein.
3. Potential Impacts
3.1. Economic Impacts
Assess the potential economic impacts of the AI system on stakeholders, including employees, customers, and partners, and outline any strategies for addressing or mitigating these impacts.
3.2. Social and Cultural Impacts
Identify potential social and cultural impacts of the AI system, both positive and negative, and describe how these impacts will be addressed or mitigated.
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4. Fairness and Bias
4.1. Potential Biases
Identify any potential biases that may be present in the AI system, including those related to data, algorithms, or user interfaces.
4.2. Mitigation Strategies
Describe the strategies that will be implemented to address and mitigate the identified biases.
5. Privacy and Data Protection
5.1. Data Collection and Usage
Outline the types of data that will be collected and used by the AI system and describe the purpose and legal basis for collecting and processing this data.
5.2. Data Security and Privacy Measures
Describe the data security and privacy measures that will be implemented to protect the data collected and processed by the AI system.
6. Transparency and Explainability
6.1. System Transparency
Discuss the level of transparency of the AI system, including the extent to which users and stakeholders can understand how the system works and the logic behind its outputs.
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6.2. Explainability Measures
Describe the measures that will be implemented to ensure that the AI system's outputs are explainable and understandable to users and stakeholders.
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7. Safety and Security
7.1. Potential Risks
Identify any potential safety and security risks associated with the AI system and describe the likelihood and potential impact of these risks.
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7.2. Risk Mitigation Strategies
Outline the strategies and measures that will be implemented to mitigate the identified safety and security risks.
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8. Human-AI Collaboration
8.1. Human Involvement
Describe the level of human involvement in the AI system, including the roles of humans in decision-making processes and system oversight.
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8.2. Human-AI Collaboration Measures
Discuss the measures that will be implemented to ensure effective human-AI collaboration and to maintain human control over the AI system.
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9. Monitoring and Evaluation
9.1. Monitoring Plan
Outline the plan for monitoring the AI system's performance, ethical compliance, and impact on stakeholders.
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9.2. Evaluation Metrics
Identify the key evaluation metrics that will be used to assess the AI system's performance and impact.
​10. Stakeholder Engagement
10.1. Stakeholder Identification
Identify the key stakeholders involved in the project, including internal and external stakeholders.
10.2. Stakeholder Engagement Plan
Describe the plan for engaging with stakeholders throughout the project
