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AI-900: Navigating Responsible AI: Microsoft’s Principle in Triage Bot for Insurance Claims

Explore the alignment of Microsoft’s reliability and safety principle in AI through a triage bot prioritizing insurance claims based on injuries. Uncover how this commitment enhances the responsible use of artificial intelligence in critical decision-making processes.

Question

A triage bot that prioritize insurance claims based on injuries is an example of the Microsoft reliability and safety principle for responsible AI.

A. Yes
B. No

Answer

A. Yes

Explanation

The correct answer is A. Yes.

A triage bot that prioritizes insurance claims based on injuries is an example of the Microsoft reliability and safety principle for responsible AI. This principle states that AI systems should perform reliably and safely under normal and unexpected conditions, and that they should not cause harm or damage to people, property, or the environment.

A triage bot that can accurately assess the severity of injuries and allocate resources accordingly can help reduce the risk of human error, bias, or negligence in the insurance claim process. It can also improve the efficiency and quality of service for the customers and the insurance company. However, to ensure that the triage bot is reliable and safe, it needs to be designed, tested, and monitored with rigorous standards and best practices.

For example, the triage bot should have clear and consistent criteria for prioritizing claims, and it should be able to explain its decisions and handle feedback or complaints. It should also have mechanisms to prevent or detect data breaches, cyberattacks, or manipulation by malicious actors. Moreover, the triage bot should be respectful of the privacy and security of the customers’ personal and medical data, and it should comply with the relevant laws and regulations.

Therefore, a triage bot that prioritizes insurance claims based on injuries is an example of the Microsoft reliability and safety principle for responsible AI, but it also needs to adhere to the other principles of fairness, privacy and security, inclusiveness, transparency, and accountability.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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