Question33 To address the AI "black box" problem and ensure responsible use of AI in finance, the article "Regulating Artificial Intelligence in Finance: Putting the Human in the Loop" proposes strengthening internal governance. Which of the following is presented as a key tool for achieving this? Mandating that AI development be outsourced to third-party technology experts to ensure that risks are well managed. Removing human involvement in AI-driven decision-making processes for enhanced efficiency and objectivity without bias. Relying on a "blame-free remediation" approach without worrying about personal responsibility. Implementing AI due diligence, AI explainability, and AI review committees. ResetMaximum marks: 1 Flag question undefined单项选择题
A
Mandating that AI development be outsourced to third-party technology experts to ensure that risks are well managed.
B
Removing human involvement in AI-driven decision-making processes for enhanced efficiency and objectivity without bias.
C
Relying on a "blame-free remediation" approach without worrying about personal responsibility.
D
Implementing AI due diligence, AI explainability, and AI review committees.

Question

Question33 To address the AI "black box" problem and ensure responsible use of AI in finance, the article "Regulating Artificial Intelligence in Finance: Putting the Human in the Loop" proposes strengthening internal governance. Which of the following is presented as a key tool for achieving this? Mandating that AI development be outsourced to third-party technology experts to ensure that risks are well managed. Removing human involvement in AI-driven decision-making processes for enhanced efficiency and objectivity without bias. Relying on a "blame-free remediation" approach without worrying about personal responsibility. Implementing AI due diligence, AI explainability, and AI review committees. ResetMaximum marks: 1 Flag question undefined单项选择题

A

Mandating that AI development be outsourced to third-party technology experts to ensure that risks are well managed.

B

Removing human involvement in AI-driven decision-making processes for enhanced efficiency and objectivity without bias.

C

Relying on a "blame-free remediation" approach without worrying about personal responsibility.

D

Implementing AI due diligence, AI explainability, and AI review committees.

BlackTom AI · Accepted Answer

AI due diligence, AI explainability, and AI review committees directly target the "black box" problem by bringing visibility, accountability, and structured oversight into AI systems used in finance.

1) Relevant knowledge points and concepts
- Black box problem: complex AI models (especially deep learning) produce outputs that are difficult for humans to interpret.
- Governance tools: due diligence involves risk assessment and validation before deployment; explainability provides interpretable reasons for model outputs; review committees impose human oversight and responsibility.
- Responsible AI in finance requires both technical and organizational measures to manage model risk, legal exposure, and ethical concerns.

2) Step-by-step reasoning
- The article’s goal is to “put the human in the loop.” That implies strengthening internal governance rather than removing humans or outsourcing responsibility.
- Option evaluation: Only an approach that explicitly reintroduces interpretability and human checks solves the black box issue.
- Implementing due diligence ensures models are tested, validated, and stress‑tested before use.
- AI explainability provides interpretable outputs so decisions can be audited and justified to regulators and customers.
- AI review committees create repeated human checkpoints for deployment, monitoring, and remediation.

3) Intermediate steps (conceptual)
- Identify problem: opaque decision logic → risk of unfair/erroneous outcomes.
- Apply controls: due diligence → detect weaknesses; explainability → interpret outputs; review committees → assign human oversight.
- Result: reduced opacity, clearer accountability, and improved risk management.

4) Why the correct answer is correct
These three tools together form an integrated governance framework that addresses opacity, assigns responsibility, and enables remediation — precisely the remedy recommended in a paper focused on responsible AI in finance.

5) Why the other options are incorrect
- Outsourcing development: shifts responsibility outward but does not guarantee internal governance or explainability.
- Removing human involvement: exacerbates the black box and reduces accountability.
- Blame-free remediation: ignores the need for accountability and preventive oversight; it’s insufficient as a primary governance tool.

Conclusion: Implementing AI due diligence, AI explainability, and AI review committees is the correct choice, matching the provided answer.

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