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Recipe - what I can do

Well seasoned instead of blindly trusting - using AI responsibly

Ingredients

* 1 well-trained AI model (not to be confused with omniscience!)

* 2-3 portions critical thinking

* 1 clear pinch Ethical guidelines in the company

* 1 shot Transparency about data sources & models

* 1 good piece Sensitivity to discrimination & bias

* Optional: AI governance team or external consulting

* A lot Education and training for employees

Results in: Productive, fair and responsible human-machine collaboration


👩‍🍳 PREPARATION:

1. Define responsibility:
Anyone using AI in a company needs clear rules: Where can AI provide support? Where not? Who is responsible for decisions? Ethical guidelines and an internal AI Code of Conduct can help here.

    2. Classify AI correctly:
    AI is not a search engine - it hallucinates, invents, simplifies. What sounds plausible is not necessarily correct. Always cross-check - especially with critical topics.

    3. Make people aware of bias:
    Every AI model bears traces of its training data - and therefore cultural, gender-specific or social distortions (bias). Therefore: question content, promote a variety of perspectives and examine sensitive areas of application particularly closely.

    4. Create transparency:
    Employees and stakeholders should know, where and how AI is used in the company - and which decisions are made on a machine basis.

    5. Serving education & training:
    Employees need tools for classification: training on the opportunities, risks and ethical use of AI is part of every company that takes responsibility seriously.

    6. Do not leave AI alone:
    Good AI applications are hybrid - the machine provides suggestions, the human decides. Responsibility always remains with the human being.


      🍽️ SERVING SUGGESTION:

      Ethically deployed AI can speed up processes, promote new ideas and make everyday working life easier. But only if it not as a path of truthbut as a tool with limits.

      📌 Tip from the chef

      Regular reflection in the team - for example in the form of "AI check-ins" - helps to keep the deployment up-to-date, fair and responsible.

      Have fun cooking!

      Anyone who has tried or modified the recipe, feel free to comment!





      This recipe is from
      Frank Brown


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