Conversational interfaces, also known as CUI (Conversational User Interfaces), represent a crucial component in the evolution of communication between human beings and machines. These intelligent systems are designed to make interaction more natural and fluid, allowing people to communicate with machines using natural language.
These interfaces are based onconversational artificial intelligence, ever closer to the way in which people communicate. This makes it possible to better meet the needs of the user, who can contact the machines with questions in their natural language and receive equally fluid answers.
Conversational interfaces, in fact, are based on colloquial artificial intelligence, increasingly close to the user's way of communicating. This ensures that these interfaces are always closer to the needs of the user, who can ask the machine questions in his natural language and obtain relevant answers from it in the same language.
The interaction between the human being and the machine can take place through written or spoken language. Here are some examples of conversational interfaces: i Chatbot and voice assistants. These intelligent agents are equipped with artificial intelligence trained to understand human language.
Conversational interfaces are widely adopted by companies to facilitate communication with their customers. To create customized interfaces, it is advisable to contact experts in the design of artificial intelligence solutions, such as indigo.ai, the customizable and scalable AI platform that allows you to design conversational interfaces to meet different business needs.
The intelligence of conversational interfaces
In the landscape of conversational interfaces, technological evolution has played a crucial role. In the past, machines were able to process natural language, but over the years there has been a transformation that has led them to understand not only language, but also the context and human intentions. This progress has been made possible by the application of the principles of machine learning and Natural Language Processing (NLP) to artificial intelligence systems.
In particular, Machine Learning is used during the design phase of conversational interfaces for the construction of algorithms that allow technology to provide relevant answers. Natural Language Processing, on the other hand, ensures that technology learns natural human language patterns and is then able to replicate them. This means that the artificial intelligence with which conversational interfaces are equipped starts from a knowledge base that is continuously expanded — and becomes increasingly sophisticated and precise — precisely through human-machine interactions.
The result of this evolution is a richer and more personalized experience for the user. Thanks to the use of artificial intelligence and the lower amount of input required from the user, the interaction with conversational interfaces becomes increasingly natural. Information is provided gradually, with specific answers, creating a more fluid and engaging conversation.
Already in 2016, a report on network trends drawn up by KPCB anticipated that the expansion of artificial intelligence would be a real paradigm break. Since then, artificial intelligence has continued to evolve, achieving extraordinary levels of accuracy, the creation of cutting-edge technologies such as ChatGPT and GPT-4, which have revolutionized the AI landscape.
Conversational interfaces are versatile and can be integrated into a variety of services. This flexibility is one of the main reasons why these interfaces have spread so quickly. Companies can implement them to improve communication with customers in different contexts.
Types of conversational interfaces
Conversational interfaces fit into business processes on different levels. They can be used in basic level customer care services, for example in providing answers to frequently asked questions, or they can be applied in more complex contexts to provide increasingly articulated and detailed answers. This is why conversational interfaces can be of a different type depending on the preferred communication channel and the processing and response complexity they can provide.
Rule-based conversational interfaces
These interfaces follow strict, well-defined pre-set rules. A common example is Q&A chatbots, designed to answer pre-established questions and follow a specific conversation flow. These interfaces are limited to answers based on predefined paths and cannot handle “out of the box” questions. They are particularly useful in first-level assistance, optimizing time and costs in managing customer care, especially for frequent and repetitive questions.
Text-based conversational interfaces
These interfaces use writing as their primary communication channel. Examples include chatbots, live chats, website widgets, and other technologies based on textual input and output. One of the main advantageous features of these solutions is the ability to learn and cluster information, such as keywords and attributes, directly from conversations between machines and users. This helps improve the effectiveness and relevance of responses over time.
Conversational voice interfaces (voice-based)
These interfaces favor the use of voice as a communication channel. Users can interact with these interfaces by providing voice commands. Voice assistants represent a widespread example in sectors such as home automation and electronic commerce. However, unlike text-based interfaces, voice interfaces have a limitation: they don't allow you to add detailed information or guide users through complex conversation flows.
Hybrid Solutions
There are also hybrid solutions that combine elements from different types of interfaces. These solutions offer a mixed-type human-machine interaction, allowing greater flexibility and adaptability to the specific needs of the company and the user.
Examples of conversational interfaces
Telegram
Telegram, a messaging app, offers its users the opportunity to receive automatic messages based on personal interests, thanks to the creation of specialized bots. For example, @trackbot allows you to receive notifications about the status of shipments, while @pricetrackbot monitors changes in the price of products on Amazon.
Amazon Alexa
Amazon Alexa, the intelligent personal assistant created by Amazon, uses the Echo speaker as an interface. This technology is also available in Italian and allows users to issue voice commands, including rather complex ones, such as ordering a pizza or skipping songs in a playlist.
Typeform
Typeform, specialized in creating interactive forms and questionnaires, has created an article that combines traditional content with conversational elements. This approach makes it possible to provide insights on the topics covered, offering an interactive experience. We recommend that you try it to experience this new form of interaction.
Google Home
The Mountain View giant has demonstrated how easy it is to interact with a machine through Google Home. Even if the number of Google Home devices in circulation is lower than Amazon's Echo, Google is gaining ground thanks to integration with external services. It is possible to communicate with any brand that has developed its chatbot for Google Home. For example, you can say, “Hey Google, can I talk to KLM?” and interact with the KLM chatbot. This conversational experience stands out for the attention that Google devotes to users.
While the goal is to make the interaction as smooth as possible, it's important to note that it's currently not possible to completely replace the human interaction experience. However, conversational interfaces are constantly progressing, opening up new possibilities for interaction between human beings and computers. This evolution aims to make machines better understand the human being, making the communication experience more natural and effective.
The future of conversational AI-based interfaces
We are experiencing a revolution in the way we interact with our devices, a significant change of course. In the past, we have adapted to modes of interaction that were often foreign to our nature. An emblematic example of this challenge is the QR Code, which, in part, failed because it required people to conform to the language of machines, rather than the other way around. This forced us to sacrifice part of our innate way of interacting with the world to learn how to communicate with devices.
However, conversational interfaces, and even touch screens, represent a fundamental breakthrough. They allow us to preserve our natural way of communicating, through gestures and words, in a simple and intuitive way. We are finally teaching machines to understand the human being instead of imposing an artificial interaction model.
AI-based conversational interfaces are evolving rapidly, becoming increasingly intuitive and effective in interpreting our needs. However, the path to a completely natural and human interaction with machines is still ongoing. The future holds for us further innovations and improvements that will bring us closer and closer to the goal of creating a digital environment in which AI adapts to our language and needs, making interaction with devices a natural part of our daily lives.