In recent years, the deployment of artificial intelligence (AI) in customer-facing roles has seen a significant increase, particularly in the use of large language models (LLMs) which engage in natural language conversations. This article focuses on the usage of AI in travel companies to create and operate virtual travel agents. These AI-powered assistants can handle a high volume of queries whilst maintaining efficient customer satisfaction by personalising user experiences.
However, the introduction of AI into these roles can have negative implications such as harmful or biased outputs, exposure of sensitive data, or misuse for malicious purposes. In order to mitigate these risks, robust safeguards and validation mechanisms must be used. For instance, a set of tools called Guardrails for Amazon Bedrock is used to help secure generative AI applications in areas prone to AI misuse. The guardrails offer safety protection that significantly reduces harmful outputs, giving companies the ability to raise privacy and safety procedures within their systems.
A thorough solution for securing the operation of an AI-powered virtual travel agent is provided in the article. The solution describes how to implement prompt engineering techniques and various guardrails to ensure the assistant remains within predetermined boundaries. In addition, monitoring is suggested in order to track the deployment of safeguards for potential issues.
In order to tailor the virtual agent for the travel company’s specific needs, several steps are prescribed. For instance, the article suggests ensuring neutrality, constraining the application to the travel domain, and blocking controversial or harmful information. This can be achieved through the use of built-in guardrails and rules-based filters such as those that block the mention of competitors, protect users’ personal data, and flag inappropriate language.
To track these safeguards’ application, logging and monitoring mechanisms were set up that provide data on how often each rule is breached. This allows the company to proactively address potential issues and refine safeguards as needed.
Despite the precautions in place, the authors emphasize that responsible AI practices extend beyond technical safeguards. Human oversight and governance, transparency, privacy, ethical training, and collaboration are recommended alongside technical solutions.
The implementation of the solution outlined provides enhanced user experiences, mitigates risks, aligns with ethical AI principles, and allows proactive issue identification. It also can be scaled and adapted to different use cases or sectors.
