Thinking about using a chatbot in your next intervention? If you've never integrated a chatbot into an intervention before - or if you have but it didn't work out as well as you'd hoped - here are my recommendations.
Chatbots often do a great job at appearing as if they can do lots of magical things. Maybe it's the syllable "bot" that makes us believe that they are somehow endowed with special power. As a result, some researchers expect a chatbot to do too much.
Chatbots are actually not a form of artificial intelligence or machine learning.
They are simply a fancy form of user input, much like any other input you've used on a website or on your phone.
Chatbots can be useful for acquiring information in a simplified format:
When most of us think of chatbots, we imagine something more conversational. Most commerical chatbot platforms are geared at business solutions, such as customer service, technical support, or sales automation. The goal of these platforms is to offload the most commonly asked questions away from human personnel, freeing them up to focus on the more difficult situations.
To make these advanced platforms work in a research context would require a a significant cost in terms of both labor and money. Chatbots only understand natural language input after a significant amount of "training" to understand incoming vocabulary and grammar. And while a few platforms are emerging as low-cost options, such as Google's DialogFlow, they still require integration into a custom software solution. Those integration costs must be borne by your devshop or (more likely) passed on to you.
Before you decide on a chatbot for your intervention, try to answer these questions for yourself:
Chatbots are finding their niche in more and more places, and undoubtedly can be helpful in many research areas. Before you invest any time or money in a chatbot-based intervention, be sure to think through the details of how to get the best outcome.