02 · 2 hours

What to Give AI, and What Not To

Data classification, anonymisation and open data.

Goal: Participants assess the risk of a piece of content before giving it to AI, anonymise it where needed and work safely with open data.

Who it is for

  • All employees who use AI in their work processes
  • Especially legal, human resources, information security and customer-facing teams

What participants gain

  • Assessing the risk of content before giving it to AI
  • The habit of anonymising and of finding open data
  • A data check skill run every time

Content

  1. 01Which data goes where?Public, internal, personal and confidential data; live classification on sample documents.
  2. 02Reviewing the settings of the toolsChecking the privacy and data retention settings of the AI tools in use together; the risk under KVKK.
  3. 03Anonymising dataRemoving names, phone numbers and ID details so the content can be used safely.
  4. 04Working with open dataFinding data from sources such as TÜİK, the World Bank, Kaggle and Hugging Face; licences and attribution.
  5. 05The hidden instruction trapA live demonstration of how an instruction hidden in a web page steers AI, and how to protect against it.
  6. 06Ethics and reliabilityBias, copyright and transparency; disclosing AI-generated content.
WHAT YOU KEEP
A data check skill
Duration
2 hours. Can be taken on its own; two programmes back to back make a half day.
Participants
Up to 10 people, each with their own laptop.
Data
No company data is used. Exercises use open data and non-sensitive content.
Prerequisites
No coding is required. The installation list is shared in advance and approved by IT.
LET’S START

For most organisations, training is the first step.

Once your team has learned, if you want to turn ideas into a pilot, we continue with AI transformation and roadmapping.