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AI Agent - Schedules appointment for a service. Scenario: A customer trying to book an appointment past one month, the system shows no availability for next two weeks. AI agent detect that he/she is a regular customer book for the service and also cant able to get the appointment in all the past bookings. Conflict: According to the rules, Scheduling agent strictly shows the available slots and inform the customer that there are no slots available. In this case customer can feel frustrated, especially if they have an urgent need. Approach: Scheduling agent should identify the High value or Loyal customers and prioritize interactions with them. Agent can be pre programmed to allocate the slots by checking for cancellation slots or any other special slots (limited duration slot) which may help for the loyal customer. In case of no slots are available, AI agent can add the loyal customer to the priority waiting list and inform them that you are in priority waiting list, if slot opens up they will get prioritized. Limitation: Scheduling agent should not able to overbook the appointment or scheduling conflicts for a loyal customers. Scheduling agent should not guarantee for the appointment, it can only offer to check for possibilities.

Ethical Dilemma Situation: A Customer Service BPO has its existing customers categorized as VVIP, VIP, Important, Regular and Blacklisted. They use an AI agent which is modelled to prioritize incoming calls / text messages of VVIP and VIP customer category and record their queries / complaints while other category customers are subject to long waiting queues. Dilemma: VVIP / VIP: This category is kept happy with an intent to maximize revenues and achieve SLA KPI’s. Others: Unethical as they are subject to long waiting periods even if the nature of the call could be to address an emergency. As the AI agent follows the applied logic of prioritization, such dilemma situations could arise leading to dissatisfied customer base, reputational damage to the company or even legal disputes. Approach for guided decision: 1. Define ethical principles in KB Create a list of ethical principles aligned to the organizational objectives, add to the internal knowledge base and train the AI model to adhere to the principles. This will make the agent strike a balance between guiding principles and rigid rules. 2. Weighted priority: Build in weightages of priorities between customer category and query urgency. This will help allocate a reasonable balance between category and urgency. 3. Human in the loop (HITL) system: In case of conflicting situations which the agent is not able to handle, create a mechanism to escalate to human agents for intervention and decision making. The AI agent must be capable of learning and improving referring to the human decision. 4. Compliance audits: Conduct periodic compliance audits to review the agent’s decision compliance in accordance with the guiding principles. Drawing the line: What should AI do? Preliminary prioritization, escalate in case of conflict, follow guiding principles, provide explanation for decision and continuously learn & improve. What should AI not do? Decision in conflicting situations, override guiding principles.

Scenario: A patient has just completed his critical surgery and chemotherapy sessions. He has 10 unopened vials, but they are from the open carton. These vials are highly costly, and his overall treatment cost is also high. But he does not need these medicines anymore and asks the manufacturing company to take them back so they can be given to another financially weak patient. For this, he contacted to the company's patient helpdesk chatbot. Patient request: These are expensive medicines, and he feels that throwing them away is wrong, as well as he wants some refunds from the manufacturing company. Company Law: Sold medicines cannot be returned or reused, as there is no data on handling at the patient's premises. Also, there is no policy for a refund. Risk: If the company makes a refund or supplies returned medicine to another patient, then the company may face legal issues if reused meds cause harm. Conflict: Accept patient request: If the company accepts the patient request and supplies medicine to another patient, then there is a risk of safety violation and which may also lead to legal issues. Chatbot follows policy: In this case, the patient will not receive money, lose trust, and waste these life-saving medicines. Approach to guide the AI’s decision: AI’s Immediate Response: "Hello, Mr. ABC, thank you for connecting. We understand your issue, but due to patient safety, we can’t reuse these medicines. We appreciate your effort in the use of medicines for needy people. Let me suggest that you to connect with a donation program at external NGOs." Workaround: AI does not approve this return request, but guides him to connect with NGOs that help to supply sealed vials to needy people. Additionally, as a goodwill gesture, the chatbot can offer him a discount voucher. Human Escalation: If the patient still insists, then AI transfers this communication to an employee who can explain why the medicine can not be returned. Summary: AI should help patients, but not at the cost of safety, even if the rules seem to be unfair for the patient.