The Funda Five™
Every learner leaves with one framework they can apply to any AI encounter at work — in 2 minutes, without technical knowledge. Select any step to see what it means in practice.
Not every task benefits from AI. Some are well-suited — drafting, summarising, generating options. Others carry risks that outweigh the convenience — anything involving verification of facts, high-stakes decisions with individual consequences, or tasks where the thinking is itself the value.
When you paste text into a public AI tool, it may be used to train the model, stored, or accessed by third parties. Under Ghana’s Data Protection Act, 2012 (Act 843), your organisation stays the data controller — responsible for personal data no matter which AI tool processes it.
Different tools are built for different jobs. A language model is strong at generating and summarising text, weak at arithmetic and factual citation. Matching the tool to the task is basic professional judgment — the same way you wouldn’t use a spreadsheet to write a contract.
Trust should be calibrated — higher where errors are easy to spot, lower where they’re invisible until they cause harm. The key question isn’t “is this AI reliable?” — it’s “how would I detect an error in this specific output?”
When AI output affects a real person — their job application, their loan, their treatment — someone at the institution that deployed it is accountable. “The algorithm decided” is not a defence, and Ghana’s incoming Data Protection Bill makes rights over automated decisions explicit.