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Tatiane Silva de Paula | Linguist | everis Brasil

The technology for humanizing bots

The Natural Language Process, or NLP, is one of the most widely used technologies to develop bots. The NLP provides more natural dialogues and does not require the use of menus and buttons.

The NLP provides a more natural experience to the bot-user relationship. The user is able to have a dialogue with the robot by using cognitive processing provided by companies, such as IBM — IBM Watson, Microsoft — LUIS or Google — However, it is fundamental to marginalize expectations to deal with possible frustrations.

It is important to note the NLP is associated with extracting the user’s needs rather than understanding them, and there is a big difference between extracting and understating. To debunk the AI subject and the interpreting processes used by current robots, learning more about some terms is important.

Extracting. AI is currently related to written contexts. The most frequent terms lead to a statistic comparison and association, which is different from the “understanding” concept, often associated with robots.

Understanding. Understanding takes more than just reading. In order to understand something, one must realize, understand and interpret what is being said or written. In all these cases, such possibilities are beyond realizing intention and are often related to the context of the conversation and previous user experiences. Thus, the human language uses much more than algorithms.

In some cases, the user is directed to a human assistant to solve problems or work around expectations. There may be times when the bot has difficulty understanding or does not have the transactional capacity to perform the user request, regardless of how advanced the AI engine is, and even though the training is frequent and constant. Understanding natural language, analyzing feelings and mapping use cases are key to deciding when to transfer the conversation to a human assistant.

Robots may be one of the main channels of service and interaction with the user. However, needs and clients differ, which may surprise even the most technological mechanisms.

By: Tatiane Silva de Paula

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