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Context-awareness

As explained in Effective Conversational AI

Semantic understanding is the computational interpretation of the meaning conveyed by language.

A chatbot can answer a question correctly yet still make the user work too hard. After a customer reports a lost card, a generic menu may ask them to start over. A context-aware assistant uses that recent event to offer relevant next steps, such as tracking a replacement card or reviewing transactions. section 9.1.1

Context-awareness means using relevant details about the user and the current conversation when choosing what to say or do. Those details may include recent activity, past interactions, preferences, and account information. The aim is a timely response that fits the user’s situation rather than a standard reply. section 9.1 section 9.1.1

The same question, different advice

For “How should I manage my expenses this month?”, generic advice says to track spending and keep a budget. Knowing that the user travels frequently can make travel spending and rewards relevant; knowing they have just started a job can make new income and one-time expenses relevant. The question stays the same, but useful advice changes with the circumstances. section 9.1.1

Keeping an assistant context-aware requires more than storing an earlier message:

  • Carry relevant details across exchanges so users need not repeat themselves. section 9.1.1 section 9.3.3
  • Revise the assistant’s understanding when new information changes the user’s intent—for example, when a request for budget travel becomes a preference for luxury accommodations. section 9.3.3
  • Pair retrieved information with contextual interpretation when an accurate fact alone will not resolve the user’s request. section 9.3.2
Table 9.2 Example interactions with non-contextual, contextual, and personalized responses
User query: How should I manage my expenses this month?
Non-contextualized response
Ensure you track your expenses and stay within a budget. Consider using financial tracking tools to help manage your spending.
Contextualized response for a frequent traveler
Since you travel frequently, consider investing in a credit card that offers travel rewards. You should also look into travel budgets for each trip and explore saving options on frequent flyer programs to optimize your travel-related expenses this month.
Contextualized response for a recent graduate starting a new job
Congratulations on your new job! As you transition into financial independence, it’s important to set up a budget, considering your new income. You might want to allocate funds for upcoming one-time expenses, such as professional attire or a commuting pass, while also starting an emergency fund.

Compare how one expense question receives generic advice versus responses tailored to different user circumstances. section 9.1.1

How Effective Conversational AI covers it

How deep it goes
Explains context through contrasting interactions and outlines ongoing context updates, without specifying implementation code.
Examples
Contrasts lost-card menu options and expense advice, then illustrates a travel preference changing during a conversation.
What you can do after
Evaluate/understand whether an assistant uses current and past context to reduce repetition and adjust responses when user needs change.
How it connects
Links context-awareness to intent classification, natural language processing, retrieval-augmented generation, and conversation state.

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This explainer was generated by Manning's knowledge graph from the text of Effective Conversational AI. The section links point to the parts of the book it draws on.