AI Trustworthiness, Ethical and Societal Implications (e.g., ESG) AAIR Practice Questions (Page 1)

Questions 1–5

1. 1expert · hard

   A law enforcement agency is piloting an AI system to predict potential 'hot spots' for crime. The system uses historical crime data, which is known to be biased by over-policing in certain neighborhoods. The agency's leadership is committed to using the system to allocate resources more effectively but is concerned about reinforcing existing biases. The agency's AI governance board must decide on a deployment strategy. Which strategy best balances the potential benefits of the system with the risk of perpetuating societal harm?

   • ADeploy the system without modification, as its predictions are based on objective historical data and are therefore unbiased.
   • BProhibit the use of the AI system until a completely unbiased dataset can be created, which may take several years.
   • CDeploy the system only in neighborhoods that are not currently over-policed, to avoid reinforcing existing biases.
   • DDeploy the system but require that its predictions be reviewed by a human commander who has the authority to override them, and conduct a public impact assessment.
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2. 2application · medium

   A healthcare provider is adopting an AI system to assist in diagnosing skin conditions from patient photos. The provider's risk team is tasked with integrating ethical considerations into its existing enterprise risk management (ERM) framework. Which action best demonstrates the integration of an ethical AI framework into the organization's governance?

   • AEmbed AI-specific ethical risk criteria, such as patient safety and algorithmic bias, into the existing risk assessment templates and escalation procedures.
   • BConduct a one-time training session for all clinicians on the ethical principles of AI in healthcare.
   • CRequire all AI-related projects to be approved by the legal department before development begins.
   • DCreate a new, standalone AI ethics policy and assign a single ethics officer to be responsible for its implementation.
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4. 3application · medium

   An energy company is using an AI system to optimize the placement of wind turbines. The system's primary objective is to maximize energy output while minimizing cost. The company's ESG committee is reviewing the project. Which additional factor should the committee require the AI system to consider to ensure its ESG alignment?

   • AThe long-term maintenance costs of the turbines and the availability of replacement parts.
   • BThe visual impact of the turbines on the local landscape and the potential effect on property values.
   • CThe potential for the AI system to be replicated for use in other renewable energy projects.
   • DThe need to hire additional data scientists to manage the AI system's ongoing development.
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5. 4application · medium

   A bank's AI risk team is developing a new credit scoring model. The team has been asked to ensure the model's development and use align with the bank's ESG commitments. The bank has a public commitment to 'financial inclusion.' Which specific action best translates this ESG commitment into the AI model's risk management process?

   • AEnsure the model is developed in accordance with all relevant data protection regulations, such as GDPR or CCPA.
   • BConduct a one-time review of the model's training data to ensure it includes a representative sample of the population.
   • CInclude a specific metric in the model's performance evaluation that measures the approval rate for applicants from underbanked or unbanked populations.
   • DPublish a general statement on the bank's website reaffirming its commitment to financial inclusion and ethical AI.
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6. 5foundation · easy

   Which of the following is an example of an environmental (E) factor in AI risk management?

   • AThe energy consumption of AI data centers.
   • BThe transparency of AI decision-making processes.
   • CThe fairness of AI algorithms across different demographic groups.
   • DThe accountability of AI system developers.
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