Synthetic data is artificial data made to look like real data. It follows the same overall patterns, such as typical ages, gift sizes or visit dates, but the rows do not belong to real people. For example, a food bank could create a file of 500 made-up clients that behaves like its real client list. Staff could then use that file to try out new software without showing anyone’s actual details.
Why it matters
Synthetic data gives you a way to test an AI tool before you hand it real donor or client records. You can see how the tool handles your kind of information while keeping real people out of the trial. It can lower privacy risk, but it does not guarantee privacy. Poorly made synthetic data can still leak details of the real records it was based on. If a vendor offers to make synthetic data from your records, ask how they check that no real person can be picked out, and whether they use methods such as differential privacy. Treat synthetic data as one protection among several, alongside steps like de-identification, not as a replacement for them.
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