Question 1
In which situation would it be most beneficial to ground a language model in first-party information?
- AOption A:
A customer asks a company ' s chatbot for specific details about their recent purchase history.
- BOption B:
A marketing team wants to use a language model to understand public sentiment surrounding their industry.
- COption C:
A user asks a general-purpose AI assistant for the definition of a common scientific term.
- DOption D:
An analyst wants to use a language model to summarize news articles from various global sources.
Show answer and explanation
Correct answer: A
First-party information is data owned or directly collected by an organization, such as customer transactions, account records, support history, and purchase details. A chatbot cannot reliably answer a question about a customer’s recent purchase history from a foundation model’s general training data. It must be grounded in the company’s current, authorized customer records to provide an accurate and personalized response. Appropriate identity verification and access controls must also be applied before retrieving the information. Public sentiment is generally evaluated using external public data, while definitions of common scientific terms can normally be answered from general model knowledge. Summarizing global news requires grounding in external news sources rather than proprietary first-party records. Therefore, retrieving specific purchase-history information is the clearest situation where first-party grounding provides essential factual context.