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Privacy

As explained in Effective Conversational AI

Privacy is the protection and appropriate handling of information about identifiable individuals.

A chatbot may begin as a simple Q&A service but later schedule vaccine appointments, collect personal information, and require stronger privacy and security safeguards. section 3.3.1

Privacy means protecting and appropriately handling information about identifiable people. For conversational AI, treat submitted data as potentially confidential and choose systems that fit its handling requirements. section 7.1.2

Evaluate privacy before using an LLM to augment conversational AI:

  • Check whether the provider may retain submitted data or train on it later. section 7.1.2
  • Treat confidential corporate data as unsuitable for any LLM that lacks acceptable handling terms, and involve legal reviewers when needed. section 7.1.2
  • Reassess privacy when expanding from informational answers to workflows connected to scheduling systems and databases. section 3.3.1

How Effective Conversational AI covers it

How deep it goes
Checks data retention and training permissions, but stops short of detailing privacy controls or implementation.
Examples
Uses confidential corporate conversational data and vaccine-appointment flows involving personal information.
What it assumes
Assumes awareness that conversational data may be confidential and that legal review may be necessary.
What you can do after
Evaluate LLM choices and conversational-AI changes for data-retention, security, and regulatory risks.
How it connects
Connects privacy with data confidentiality, security, healthcare regulations, and secure transactions.

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Related concepts

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.