When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?
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A. B. C. D.A
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Incorrect Answers:
B: Inclusiveness mandates that AI should consider all human races and experiences, and inclusive design practices can help developers to understand and address potential barriers that could unintentionally exclude people. Where possible, speech-to-text, text-to-speech, and visual recognition technology should be used to empower people with hearing, visual, and other impairments.
C: Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed.
Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.
D: A data holder is obligated to protect the data in an AI system, and privacy and security are an integral part of this system. Personal needs to be secured, and it should be accessed in a way that doesn't compromise an individual's privacy.
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-aiThe correct answer is A. transparency.
The guiding principle of transparency in responsible AI refers to designing and implementing AI systems in a way that enables humans to understand the decision-making process. Transparency involves providing explanations for how and why an AI model arrived at a particular decision or recommendation.
In the context of designing an AI system to assess loan applications, transparency would mean ensuring that the factors used to make the decision are clearly defined and understandable. This would allow borrowers to understand why their loan applications were approved or rejected and enable them to make more informed decisions about their finances. Additionally, transparency in AI can help to prevent bias or discrimination by allowing humans to detect and address any problematic factors or patterns in the decision-making process.
In contrast, inclusiveness refers to designing AI systems that are accessible to a diverse range of users, including those with disabilities. Fairness refers to ensuring that AI systems do not discriminate against individuals based on factors such as race, gender, or age. Finally, privacy and security refer to protecting the confidentiality and security of personal data used in AI systems.