Government and nonprofit organizations are accustomed to making the most of limited resources. Improving outreach effectiveness is key to better serving communities. Which is where chatbots enter the conversation.
Chatbots can improve community engagement, enhance accessibility, and streamline processes. But, developing a dependable chatbot is essential to achieving these goals. To better understand what it takes to create a reliable and beneficial chatbot, you must understand the AI and machine learning powering them: NLP (Natural Language Processing) and LLMs (Large Language Models).
What is NLP (Natural Language Processing)?
NLP is a machine learning technology that allows computers to interpret, manipulate, and comprehend human language. It combines computational linguistics, machine learning, and deep learning models to process human language. The software can automatically process data, analyze the intent or sentiment in the message, and respond in real time to human communication. Generally, this means that a computer can use NLP to understand what you are saying over a range of different ways of phrasing the same thing (e.g. food stamps and SNAP benefits).
NLP-chatbots exhibit high accuracy and reliability within specialized domains, though they may face challenges in tasks that require a rich understanding of context.
What are LLMs (Large Language Models)?
LLMs are a type of AI program that can recognize and generate text. It’s trained on huge data sets and uses deep learning to understand how characters, words, and sentences function together – mirroring human language.
LLM-powered chatbots can achieve reliability in producing coherent language output, but they may also generate inaccurate or biased content influenced by its training data.
Why are NLP-powered chatbots the safer pick?
While LLMs are trained on large data sets and can thus respond convincingly to a wide range of topics, NLP technologies rely on intentional training via developing algorithms designed to generate human language for its specific purpose. In this way, NLP-powered chatbots are optimal for performing domain-specific applications and avoiding risk of hallucinations and bias. Unlike LLMs, NLP-powered chatbots will never make up an answer.
CommunityConnect Labs uses NLP-powered chatbots for our government and non-profit clients. With intentional programming, we’ve had success tailoring our chatbots to unique needs and incorporating conversational capabilities in multiple languages. Our NLP-powered chatbots are supported by a team of content and subject matter experts with vast experience in designing digital outreach strategies and campaigns that aim to engage with niche populations, difficult to reach audiences, and vulnerable communities. Using NLP, as opposed to LLMs, we can ensure our chatbots provide accurate information in a field where trust is crucial.