Made with AI

Partly by what they believe went into it. Across many experiments, the same painting, poem or message is rated lower when people are told AI made it, mainly because they assume less effort and creativity. Without a label, people spot machine made content at about chance, and the discount softens when the human part of the work is shown.

What the report found

1. Machine made content is now part of everyday life. In a 2025 survey in six countries, weekly use of generative AI nearly doubled in a year, to about a third of people. Most were comfortable with AI helping with spelling or translation, and far fewer with news made entirely by AI.
2. Older research explains much of the reaction. People judge work partly by what they believe went into it: the effort, the care, the original creative act and the mind behind it. A label alone can change how good something looks.
3. Told that a machine made it, people tend to rate the same work lower. Across many experiments with paintings, poems and persuasive messages, an AI label lowered liking, perceived creativity and value. Without a label, people often cannot tell the difference, and sometimes prefer the machine's work.
4. People read an AI label as meaning no human was involved. Labelling headlines as made by AI lowered trust in them even when they were true or written by people, because readers assumed full automation. Showing the human part of the work softens the discount.
5. The long run is open. Nobody yet knows whether the discount fades as people get used to AI, whether content grows more alike, or whether provenance marks build trust. Clear disclosure of what the machine did and what people did is the best current guide.

What is inside

1. What is new
2. What older research tells us
3. What early studies suggest
4. What nobody knows yet
5. Questions worth watching

Plus an evidence maturity map, the range from work made by people to work made by AI, a chart of how often people spot machine made content, a scenario grid, a list of signals to watch and five tests for publishing content made with AI.

Who it is for

For writers, artists, editors, marketers and publishers who use AI, designers of AI tools, and anyone curious about how they judge what they read, see and hear.

How we work

Frontier Reports separate what is established from what is emerging and what remains untested. Every claim is graded, and where researchers disagree, as they do on whether people prefer work made by people, both sides are set out before we say where we stand.

Cite this report

The Why We Project (2026) Made with AI: How people judge machine made content. Frontier Report No. 23. Dubai: Why We Tech Ltd. Available at: thewhyweproject.com