The following ten principles can serve as a framework for creating AI policies in your organization:
Security of AI systems:
Security is paramount. AI systems should be developed and operated under strict security standards to minimize risks and ensure data protection
Expert review of AI-supported results:
Trust is good, control is better. All results provided by AI should be thoroughly reviewed and validated with employee expertise.
Respect copyright when using the code:
When integrating codes into AI tools, care must always be taken to ensure that no copyrights are infringed and that no trade secrets or property rights of third parties are affected.
Respect copyright when using the code:
The protection of sensitive and personal data is a top croatia phone number data priority. Such information must not be allowed to be entered into AI tools.
Commitment to transparency:
The functions and decisions of AI systems should be clear and understandable in order to gain the trust of users and regulators.
Application of ethical principles in AI:
Ethics must not be neglected. Ethical considerations should play a central role in the design and implementation of AI systems.
Labeling of AI-supported content:
Transparency is also crucial here. It should be clear to users when and how AI was used in the creation of content.
Ongoing training of employees:
An effective and expert use of AI can only be ensured through regular training and further education of employees. I also offer this with my AI workshops and lectures, for example.
Responsibility for AI decisions:
Responsibility for the decisions and actions made and carried out by AI systems must be clearly defined.
Promoting fairness and impartiality:
Fairness and impartiality should be central principles in the design and testing of AI tools and technologies.