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Privacy

As explained in Build Applications with Local AI Models on a Mac

Privacy is the protection of a person's information from unauthorized collection, retention, use, or disclosure.

A cloud AI service receives the words you send it. The company may retain them or use them to improve its models. Running AI locally changes where that information goes: a voice-enabled assistant can transcribe speech and generate replies on your Mac, without sending the conversation to a cloud service. section 1.1 section 1.0

The difference matters most when a conversation contains information you would not normally share with a third party:

  • Personal conversations, such as journal entries or discussions about emotions. section 14.2.3
  • Workplace information, such as customer data, source code, financial details, or internal plans. section 14.2.3
  • Client, patient, or student information that may be subject to confidentiality rules or restrictions on sharing. section 14.2.3
Table 14.1 Comparing the privacy characteristics of cloud and local AI

Aspect

Cloud AI

Local AI (Ollama)

Data location

Company servers (often in US)

Your device only

Data in transit

Encrypted but transmitted

Never transmitted

Data retention

May be stored for 30+ days

Not stored (unless you choose)

Training use

May be used to improve models

Never used by anyone

Staff access

Support staff may review chats

No external access

Breach risk

Subject to server breaches

Only if device is compromised

Regulatory compliance

Varies; often unclear

Full user control

Terms of service

Company can change terms

No third-party terms

Compare where cloud and local AI place data, whether they transmit or retain it, and who may be able to access it. These are architectural differences, not a guarantee that every local application is private. section 14.2.3 section 14.6

Try an offline check

Put your Mac in airplane mode and try the Ollama-based chatbot. If it still works with full capability, you have verified that this chatbot does not need an internet connection for that interaction. Privacy also depends on the surrounding application, operating system, and network configuration. section 14.0 section 14.6

Local processing gives you more control over sensitive conversations, but it is not an accusation that cloud providers are careless: sending data to another server necessarily gives up some control. A practical choice is to use local AI for sensitive tasks and cloud AI when you need its greater capability. section 14.2.3 section 14.6

How Build Applications with Local AI Models on a Mac covers it

How deep it goes
Explains privacy through a cloud/local comparison and sensitive-data scenarios, while qualifying protection by application, operating-system, and network configuration.
Examples
Uses personal journaling, business documents, legal files, medical information, student data, and an airplane-mode chatbot test.
What it assumes
Introduces local AI for beginners; basic Python helps later when building the application.
What you can do after
Evaluate/understand it by testing the Ollama chatbot offline and assessing whether its supporting components keep information on-device.
How it connects
Connects privacy to offline operation, speech recognition, large language models, and regulatory compliance.

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This explainer was generated by Manning's knowledge graph from the text of Build Applications with Local AI Models on a Mac. The section links point to the parts of the book it draws on.