Non-generative government domain-specific AI chatbots have revolutionized the way governments interact with their citizens. By leveraging their deep knowledge of government domains, such as transportation, tax filing, and social services. These AI chatbots streamline interactions, improve accessibility, promote inclusivity, ensure prompt and accurate responses to their inquiries, and enhance the overall efficiency of government services – ultimately leading to enhanced public engagement and satisfaction.
On November 30, 2022, OpenAI, an AI research company launched ChatGPT to the public. ChatGPT quickly became the talk of the internet – the Swiss bank, UBS, estimated that ChatGPT had 100 million active users by January 2022, making it the fastest growing app of all time.
Before large language models (LLMs) like ChatGPT, chatbots were mostly non-generative domain-specific. While both aim to imitate human-like conversations, their underlying methodologies and capabilities differ significantly. While ChatGPT is exciting technology, there must be caution in using it – especially in government. Let’s discuss these different chatbots at a high level to help understand them more.
Government domain-specific AI chatbots are trained with supervised learning to meet the unique needs of governments. They are designed to handle structured inquiries and respond with predefined and carefully curated responses. Their specialization in government information enables them to quickly navigate through vast amounts of information and retrieve relevant details for citizens efficiently and accurately – saving them valuable time and effort in their interactions with government services.
An example of a government domain-specific AI chatbot is the Ask MA chatbot on Mass.gov developed on the Specto AI platform for the Executive Office of Technology Services and Security (EOTSS).
Government domain-specific AI chatbots excel in understanding the government domain and its wide variety of services, functions, terminology and jargon. These AI chatbots streamline government communication, delivering highly efficient, predictable, and accurate information to the public. By saving time, providing accessibility, instant support, and reducing staff workload, they improve government operational efficiency and service delivery effectiveness.
These AI chatbots are completely transparent as they undergo supervised training using trusted and verified information sources within government agencies. Moreover, there is full control over rules, patterns, and the knowledge base, allowing customization and refinement of chatbot behavior to meet government requirements.
Most importantly, these chatbots guarantee the absence of misinformation, as all responses are rigorously verified for accuracy and reliability.
Government domain-specific AI chatbots, with their narrower training, may face challenges in understanding and generating distinct responses or handling complex citizen inquiries beyond their scope. Furthermore, they are limited to predefined responses and conversational flows, which can result in a less fluid experience.
These AI chatbots have certain limitations when it comes to independently accessing and learning from the internet. Since they rely on supervised learning, manual intervention is often required to incorporate new knowledge into their systems.
Government domain-specific AI chatbots offer efficiency and speed in providing predefined responses within the government agencies they serve. They are suitable for applications where structured and specific interactions are required – such as FAQs, information retrieval, and live chat integration. Additionally, they are valuable tools for enhancing customer service, and improving efficiency.
LLM chatbots have a broad knowledge base which allows it to generate in-depth responses to a wide variety of domains – including science, history, technology and more.
Moreover, these chatbots are trained extensively to understand human language, including common phrases, idiomatic expressions, grammar rules, and semantic relationships. Consequently, this enables them to generate responses that are seemingly creative, original, and closely resemble human-generated text. Their capability to provide contextually relevant responses contributes to more natural and engaging conversations.
However, LLM chatbots lack transparency because their internal decision-making processes can be difficult to interpret or understand. They operate as complex neural networks with millions – or billions of parameters – making it challenging to trace how a specific output or response is generated – it is Blackbox AI.
Due to their generative nature, these chatbots can also be unpredictable with different and random responses. Furthermore, the sources of training data are diverse, but are not disclosed. This can result in training data that is potentially biased, misleading or discriminatory.
LLMs excel at generating text; however, they can struggle with lack of real-world understanding or from training data limitations. As a result, they can “hallucinate,” or generate responses that are coherent but inaccurate. In a recent testimony, Sam Altman, OpenAI’s CEO, expressed concerns about generative AI having great potential to spread misinformation. Organizations, like the government, must be extra cautious when using generative AI models like LLMs, as the spread of misinformation can lead to legal issues, erosion of public trust, and damage to reputation.
While they must be used with caution, LLMs are currently used to assist in a wide range of applications, including chatbots, generating code, summarizing text, language translation, and aiding in content creation. Their versatility and potential have opened new possibilities for natural language understanding and generation.
As previously mentioned with LLMs, there is often limited visibility into the decision-making process and underlying algorithms that generate responses. This lack of transparency can raise concerns about bias, discrimination, and the potential for misinformation. Moreover, this can have serious implications, particularly in government interactions where fairness, impartiality, and equal treatment are crucial.
In contrast, government domain-specific chatbots are designed with transparent AI, enabling governments to have a clear understanding of how the chatbot operates and the information it provides. This control allows for the dissemination of accurate and reliable information to the public, promoting trust and confidence in the government’s communication channels.
Transparency also facilitates accountability. Governments can ensure that the chatbot operates ethically and responsibly, upholding principles of fairness, accuracy, and compliance. They can address any potential biases or inaccuracies quickly, ensuring that the chatbot remains a reliable source of information for the public.
While LLMs hold promising potential, much work needs to be done before we are likely to see governments deploying ChatGPT-like services to their citizens.
Using NeuroSoph’s proprietary, secure, and cutting-edge Specto AI platform, we help streamline government communication delivering information that is trusted and reliable. NeuroSoph partners with the Commonwealth of Massachusetts to build chatbots. For more information about our products and services, please contact us today – let’s extend intelligence in your organization.