AI minus UX: A Cautionary Tale

​Artificial Intelligence (AI) has rapidly evolved over the past few decades, transforming the way we interact with technology and each other. At its core, AI refers to the simulation of human intelligence in machines programmed to think and learn like humans. This includes recognizing patterns, understanding language, and even making decisions. 

​One notable example of AI's promise and challenges can be seen in the case of a company that aimed to revolutionize the title and escrow business using machine learning to automate part of the title search process. While they succeeded in implementing innovative solutions, they also faced significant hurdles that underscored the complexities of deploying AI in real-world scenarios. The company's ambition was to streamline the title search process, which traditionally involves extensive manual work and is often extremely time-consuming. 

​By leveraging machine learning algorithms, they sought to quickly analyze property records and identify potential issues that could affect ownership. The company was able to create exciting new technology and apply it to solving problems in an innovation-starved space.

​However, despite these achievements, the company did not prioritize the experience of the human operator as part of the process. Techniques that are critical to successful UX design, such as creating service design blueprints, detailed journey maps, and opportunity mapping would have helped the company to be more successful in implementing Machine Learning. 

​In this talk, we will dig deep into the use case so that we can help others in the technology industry more fully realize the promise of AI. Attendees will have an opportunity to discuss their own use cases and challenges as well.