AI: Data, Privacy, and Terms of Use

Working with AI tools raises new questions about data and its protection. This module explains how to approach the topic practically, without unnecessary legalese, but with a clear awareness of the risks.
Participants will learn what they should not enter into publicly available AI tools and understand the difference between public and corporately managed tools, which fundamentally affects how the tool further handles the entered data. The module distinguishes between internal, personal, client and commercially sensitive data and shows why it is important to approach them differently.
The module also includes the basic principles of governance and responsible use of AI in an organization, ethical issues associated with the creation and use of outputs, and working with content that can affect people, decisions or the reputation of the company. The module emphasizes the principle of transparency and human responsibility for the result, regardless of how large a role the AI ​​tool played in its creation. The participant leaves the module with a clear idea of ​​when the use of AI is safe, when caution is appropriate, and when it is appropriate to involve internal rules or a responsible person.

• employees and managers who come into contact with internal or client data when working with AI tools,
• companies that want to implement clear rules for the safe use of AI,
• people who are not sure what is and is not appropriate to enter into AI tools,
• participants following previous AI Academy modules.

• What not to put into AI tools
• The difference between public and corporate-managed tools
• Internal, personal, client and commercially sensitive data
• Basic principles of governance and responsible use
• Ethical issues in creating and using outputs
• Working with content that can influence people, decisions or reputations
• Rules for transparency and human responsibility

• Recognize what information is risky to input into public AI tools.
• Distinguish between public and corporate-managed tools.
• Work differently with internal, personal, client, and commercially sensitive data.
• Understand the basic principles of governance and responsible use of AI.
• Understand the principle of transparency and human accountability for output.

What should not be fed into public AI tools?
Typically sensitive personal, client, or business-critical data where it is unclear how the tool will handle it.

What is the difference between public and enterprise-managed AI tools?
Enterprise-managed tools typically offer greater control over data and its processing than publicly available versions.

What does governance mean when using AI?
It is about setting rules and responsibilities in an organization, who and how can use AI tools and what information can be put into them.

Who is responsible for the output created with the help of AI?
It is always the person who uses or transmits the output - the AI ​​tool does not take responsibility.

Is the module suitable for even for companies without internal rules for AI?
Yes, the module helps to create a basic awareness on which internal rules can subsequently be built.