Artificial Intelligence has moved its way comfortably into our homes with the growth in chatbot technologies and devices. Names like Siri, Cortana, and Alexa are taught to our children who are taught at an early age to interact with the bot. The chatbots are able to answer simple questions or assist with homework, tell corny jokes, provide recipes, provide driving directions, make grocery lists, and order items or services. Chatbots have become a way of life.
Eliza was the first chatbot to be developed in 1964 (Coheur, 2020) and could mimic an understanding of natural language. As I am currently in the process of understanding as part of the chatbot development project at work, many researchers do not realize the complexities of natural language. Language is complex and packed with variable responses to any conversational prompt, and it is impossible to predict the ongoing path of a conversation (Coheur, 2020).
One of the projects I am leading at work is a chatbot designed to teach medical students how to practice empathetic statements when interacting with a patient. The chatbot will represent the virtual patient, and the student must navigate a conversation with the chatbot while displaying the five stages of empathy. This is an active and ongoing project, set to be completed in December 2022.
The project is using Google Dialogflow as the main program for the Natural Language Processor (NLP). I am in the phase of developing the conversational script and intents for the chatbot to follow. Intents are the various intentions a user might present when interacting with the chatbot (Greyling, 2020). Response intents are prompts that should respond to the user’s statement or query (Chiusano, 2021).
I am currently struggling to find an intent worksheet template to share with the faculty Subject Matter Expert (SME) to help expedite the development of the conversational intents and response statements, so if anyone has worked on a chatbot project I would love to hear about your experience!
Resources
Chiusano, F. (2021, November 24). Suggestions on how to structure intent in Chatbots and gather useful feedback. Medium. Retrieved October 8, 2022, from https://towardsdatascience.com/suggestions-on-how-to-structure-intents-in-chatbots-and-gather-useful-feedbacks-f72f7e552090
Coheur, L. (2020). From Eliza to Siri and beyond. Information Processing and Management of Uncertainty in Knowledge-Based Systems, 29–41. https://doi.org/10.1007/978-3-030-50146-4_3
Greyling, C. (2020, July 2). Creating intent recommendations for your chatbot. Medium. Retrieved October 8, 2022, from https://cobusgreyling.medium.com/creating-intent-recommendations-for-your-chatbot-b149cf6b8282
