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An Iterative Approach to AI Exploration

Yale Information Technology Services has embarked upon an ambitious exploration of how artificial intelligence can enhance the digital experience of the Yale community by creating “askYale,” a retrieval augmented generation (RAG) question-answering application connected with an initial data set from Yale Hospitality.

After a successful and informative initial deployment, we are drawing upon data, valuable feedback, and the latest practices in the field of AI to enter the next phase of AI-search implementation.

Advancing AI-Search through Yale Hospitality Data

Incorporating AI into our systems is a process that demands thoughtful planning and responsible management of information. As we move forward, we will continue to focus on the Yale Hospitality dataset to refine, improve, and enhance the AI-search information retrieval process.

During this phase, we seek to explore and establish the core foundational processes required to ensure Yale’s implementation of AI-Search upholds our values of reliability and trustworthiness.

  • Determine the steps required to prepare datasets and YaleSites content for efficient and effective AI-powered information retrieval
  • Apply SEO best practices to RAG to ensure AI-search results are precise, current, and reflect Yale’s commitment to quality
  • Evaluate the scalability and performance of AI-search to ensure it delivers fast and reliable results without negatively impacting site speed or overall user experience
  • Develop the tools necessary to empower YaleSites users to customize and configure the AI-search experience to meet their specific needs and audiences

By prioritizing reliability, trustworthiness, and frictionless scalability, we aim to create a service that makes Yale more accessible, inclusive, and navigable.

Help us build reliable and trustworthy AI services

As Yale ITS continues to explore AI, we invite the University to engage with us as we evolve our use of generative AI technologies.

To be an active participant in this initiative, try out the “askYale” application and share your experience with us. Your feedback is crucial—it will help us continue to refine askYale and tailor it to your needs.

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Fox Trot B, with Black, Red, Blue, and Yellow

Image attribution: Untitled, Jean-Michel Basquiat, Image from Yale University, Richard Brown Baker, B.A. 1935, Collection. | School of Art Graduate Program 1989-1990, Paul Rand. | Fox Trot B, with Black, Red, Blue, and Yellow, Piet Mondrian, Gift of Collection Société Anonyme.

Centering data privacy and security

In alignment with Yale’s values, we ensured rigorous privacy standards and data governance in deploying askYale. All data is handled with strict protocols, segregating personal information and securely storing it within environments managed and maintained by Yale ITS Cloud Services.

For a detailed understanding of our privacy policies and data handling procedures, we provide transparent access to our governance documentation and the University resources that guide our processes.

Additional insights

In response to the Provost’s Guidelines for the Use of Generative AI Tools, Yale Information Technology Services set out to explore how artificial intelligence can enhance the digital experience of the Yale community. 

Embracing the spirit of the “skateboard concept,” our team experimented with the creation of a retrieval augmented generation (RAG) question-answering application. RAG understands your questions and can guide you through Yale’s online information—that’s the promise of askYale. 

For our first version of askYale, we augmented our RAG application with an initial data set from Yale Hospitality. But incorporating AI into our systems isn’t as simple as turning on a light. It’s a process that demands thoughtful planning and responsible management of information. 

Now, by continuing to focus on our initial Yale Hospitality dataset, we seek to learn how to ensure that the data askYale uses is precise, current, and reflects Yale’s commitment to quality.

askYale is a Retrieval Augmented Generation (RAG) tool that answers your questions using generative Artificial Intelligence (AI) and large language models (LLMs). While these LLMs are trained on a vast amount of human-generated text, the RAG architecture allows askYale to understand your questions and answer them based on Yale-specific information.

All questions and user-generated data are handled in accordance with strict privacy standards. Identifying information and user queries are separated and securely stored within environments managed and maintained by Yale ITS Cloud Services

Conversations with askYale are not used to train or improve AI systems. By utilizing Retrieval Augmented Generation (RAG), askYale separates the retrieval of existing information from the generation of responses, eliminating the need to learn from or store individual user interactions. 

For a detailed understanding of our data handling procedures, you can access our governance documentation and the University resources that guide us.

AI-powered question answering is a step up from typing keywords into a search box. It works to understand the meaning behind your words, drawing from diverse sources to bring you information that’s not just accurate but also relevant. This means when you ask a question of askYale, you’re more likely to get the answer you need, enhancing your experience with Yale.

Yale is using AI to critically engage with this cutting-edge technology and to enhance the user experience of our web presence by making information more navigable and accessible. This technology supports our commitment to innovation and knowledge dissemination.

Yale is committed to responsible AI use, and is taking precautions to address and mitigate biases inherent in AI systems. We are building upon established responsible AI practices and working to ensure that our AI tools recognize and address implicit biases within the training data and responses to minimize harm.

This is an ongoing process of learning and refinement. We remain committed to adapting our strategies as they are informed by real-world usage, feedback from the community, and emerging best practices in AI.

askYale is a collaborative effort led by Yale ITS along with technology and data governance experts, web development engineers, and content and user experience specialists. The askYale site is proudly built on YaleSites.

Responsible AI use starts with an understanding of its ethical implications and a critical approach to data governance. Contact Yale’s Administrative Data Governance Committee for more information. The committee has published guidelines for working with AI to get you started.

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