A look into conversational design for chatbots – a complex system that helps makes AI chatbots intelligent.
The age of the chatbot is upon us – OpenAI’s ChatGPT had everyone racing to talk to it. ChatGPT is a large language model trained by OpenAI, an AI research and deployment company. It offered a glimpse into the future of AI chatbots. While not perfect, this highly intelligent chatbot mimics human conversation to “answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”
ChatGPT is the culmination of years of research and development in multiple fields, including artificial intelligence (AI), machine learning (ML), natural language processing (NLP), and conversational design. Many chatbots in the market today use similar technologies and techniques as ChatGPT with the goal of a seamless digital user experience.
Imagine an organization using intelligent chatbots to support everyday operations, like customer service. They could provide excellent customer service to customers while having natural and intuitive conversations. In addition, they may not need to involve a live agent, or only need them a small percentage of the time. Sounds like a truly transformative way to use technology!
A chatbot like ChatGPT is not simple – it involves investing significant hours researching, modelling, implementing, training, and re-training a chatbot. Moreover, it means engineering the right conversational design for chatbots, which helps make interacting with them feel natural, intuitive, and efficient. Let’s explore the concept of conversational design for chatbots.
Conversational design is a concept of developing human-centric interactions with AI-powered digital systems. For chatbots, it’s about teaching them how to communicate like humans to accomplish a goal. In addition, it involves learning about human conversation and using it as a model to predict what humans might say and then teaching chatbots how to react to make them easy and intuitive to interact with.
If chatbots were unable to follow, understand, and resemble human conversation it can lead to unintelligible and difficult experiences. Consequently, conversational design is important for making AI chatbots efficient and helpful.
AI (artificial intelligence) chatbots combine data, machine learning (ML), natural language processing (NLP), and conversational design to understand voice and text and communicate in a human-like manner.
Organizations use chatbots for many different purposes such as customer service, automation, request routing and information gathering. To put it simply, they are used to support humans and processes within organizations.
According to the Conversation Design Institute (CDI), conversation design “combines an understanding of technology, psychology, and language to create human-centric experiences for chatbots and voice assistants.” Conversational design for chatbots helps guide their interactions with humans to make their experiences as pleasant and as seamless as possible.
Like many other fields of research, conversational design is constantly evolving with new discoveries. Here, we only highlight some considerations of conversational design for chatbots; however, this list is not exhaustive:
Remember, one of the main goals of conversational design is to create systems that can communicate like humans to accomplish a goal. Therefore, whether the user wants to book an appointment, a trip, or ask for help; the design must have a clear goal.
For chatbots to help humans accomplish their goals, there must be a cooperative conversation. Meaning, each side takes turns interacting and responding appropriately. Chatbots that create natural and intuitive conversation flow require less effort to communicate with and are more efficient at actively supporting the user.
Satisfactory and cooperative interactions offer clear and concise information to help each party achieve its goals. Chatbots should be using dialogue that is familiar and easy to understand as it helps guide users in a logical sequence. Language that is too complex or technical only increases confusion and frustration as users become unsure what to do next.
Being clear and concise also means being respectful and considerate of a user’s limited time and attention. Speed and responsiveness are vital. Effective conversational design for chatbots helps people make easier decisions with less effort so they can complete their interaction and achieve their goals faster.
The more context-aware an AI chatbot is, the better it will be at having natural conversations. For instance, if you are in Boston and are looking for restaurants to dine at, you do not want to see restaurants anywhere other than Boston.
Having contextually aware chatbots also means being flexible so they can respond and adapt to a variety of user inputs and situations as the conversation progresses. Generic automated messages or recommendations that do not add value to users can lead to frustrating experiences.
Intelligent chatbots can be designed and programmed by humans to be error tolerant. This means being able to understand a user’s intended response even if there is an input error. A simple example is Google Search – which is very good at understanding search intent. If you are googling something and it is spelt incorrectly, you will still get relevant results. It also shows you the corrected spelling even if it’s still not quite what you meant. Revising the query feels effortless.
Consequently, if there is an error in a conversational system, it can be adaptive and flexible by providing a clear and helpful error message or suggesting a correction that helps guide them towards a resolution. This helps improve the user experience, minimizes frustrations, and allows users to continue using the system.
An effective conversational design for chatbots improve the user experience by helping chatbots be flexible, adaptable, and error tolerant. Moreover, it enables them to mimic human conversation – creating an easy-to-follow conversation flow that helps users achieve their needs quickly and efficiently.
Conversational design is an ever-expanding field that helps make digital systems easier and more intuitive to interact with. If you are interested in learning more there are some notable experts in the field include John Maeda, Jason Mars, and Erika Hall. If you are staying updated with AI, NLP, and ML – don’t forget about conversational design!
NeuroSoph is an end-to-end AI software and services company that has over 30 years of combined experience in the public sector. We are highly skilled and knowledgeable experts in AI, data science, strategy, and software.
Using NeuroSoph’s proprietary, secure, and cutting-edge Specto AI platform, we empower organizations with enterprise-level conversational AI chatbot solutions, enabling more efficient and meaningful engagements.
NeuroSoph partners with the Commonwealth of Massachusetts to build chatbots for customer service. For more information about our product and services, please contact us today – lets extend intelligence in your organization.