The most important issue to consider when creating a chatbot is its purpose and function. The range of topics that chatbots can handle increases every day, as do chatbot levels of comprehension and communication. Algorithms that aid in the teaching of chatbots, through machine learning, are continuously advancing in terms of scope and complexity, which means that chatbots, as they acquire more and more skills, can be trained to support and enhance more and more varied branches of industry and commerce.
Despite these veritable leaps in progress, chatbots are, currently at least, unable to completely replicate natural human discourse. Chatbots can solve users’ problems to a degree but are not yet equipped to register the subtleties of language, such as shifts in tone, sarcasm and emotional distance. Therefore, the presence of people in business or trade will not be made completely obsolete by chatbots.
Different types of chatbot interactions can be divided into three categories:
- Conversational – demonstrating the highest degree of life-like conversational ability and accuracy in imitating natural human language
- Scenario – consisting of rigidly set questions and responses, in the style of forms and official enquires
- Mixed – deriving strategies from both approaches
The strides that have occurred over the last number of years in chatbot development are staggering, as chatbots can perform highly complicated tasks while delivering meaningful customer service and world-class security. While current technology is not yet advanced enough to recognize every intention of the writer, the pursuit of such high-functioning technology means that the world of chatbot production is dynamic and evolving. Creating a chatbot is not as predictable as traditional software production, regardless of the model of work. Designing and building a chatbot not only requires considerable commitment from a diverse, interdisciplinary team of creators, but also patience. The process of creating a chatbot can be broken down into several stages:
- Conception: Identifying the aims and target area of chatbot automation (what duties, tasks and processes the chatbot will be responsible for)
- Brainstorming: Presenting possible scenarios, queries and answers, as well as a combination of queries and answers – this stage is most effective if there is access to an organization’s internal materials (FAQs, call centre logs, customer feedback)
- Activation: Initiating programming work
- Content Creation: Generating conversations with the appropriate content of expressions – in accordance with the designed scenarios
- Testing: Chatbot tests
- Automatic tests – verifying the effectiveness of categorizing the introduced phrases and tests of the learned context (possible recognition of variables)
- Call tests
- Beta tests (e.g. conducted by potential users)
- Implementation: Chatbot integration with a database or an IT system
- Reporting and Evaluation: Creating a framework that allows gathering feedback, compiling reports and analysing statistics and other data
The age of artificial and emotional intelligence has arrived, and it is evident that our world is experiencing a digital revolution. The automation of processes has grown exponentially and shows no signs of abating. Chatbots are at the forefront of this transformation and thus a focus on this burgeoning field is not only advantageous, but essential.
Read other articles in the series: Technically Speaking:
- Part I Reading Between the Lines: Checking the Accuracy of Chatbot Phrases
- Part III Reflections on Testing Natural Language, Natural Language Processing and Dealing with Language Peculiarities
- Part IV: The Education of a Chatbot: Developing a Chatbot’s Comprehension Skills and Testing the Correct Classification of Categories