Data collection
Data use
CSAM
Image-based data
Until recently, the Internet Watch Foundation (IWF) recorded only the youngest child depicted in images of child sexual abuse material (CSAM). But this approach risked undercounting children in multi-victim content and skewing important data on the age, sex and skin tone of child victims.
In 2023, IWF began recording how many CSAM images depicted more than one child. They found that 10% of images had two or more children. This led to the development of the MultiChild format, where each child is individually tagged with age, sex, and skin tone.
The shift had a significant impact. In 2024, MultiChild tagging identified an additional 70,898 children, representing 11% of the total. It also changed the demographic picture: the number of identified 14–17-year-olds increased markedly, and in the case of 14–15-year-olds, even doubled—highlighting a systematic underrepresentation in earlier data.
This new methodology also validated the trends that earlier data was showing, which is important as it increased confidence in the accuracy, granularity, and robustness of the dataset. IWF’s internal assessment confirmed that the overall patterns had held, but now with greater clarity and credibility.
Why does this matter? Because IWF knows that their data is used by governments, law enforcement, and tech platforms to shape real-world responses. The more robust and trustworthy the dataset, the more confidently stakeholders can act on it. In this way, improving data quality directly increases its utility and impact.
“One of the main reasons we’re doing this is data improvement. We know that the data IWF produces and shares is impactful. We know that it is used by others to inform and understand child sexual abuse on the internet, so it’s really important for us to make sure that our data is robust. Our analysts are doing incredibly difficult work assessing and tagging millions of images and videos of children being sexually abused, we want to make sure that data is as accurate as it can be to have the best possible impact”
Dan Sexton, IWF
At the same time, IWF confronted the trade-offs of expansion. When they tried MultiChild tagging for videos, the emotional toll on analysts and time demands proved too high. As a result, they chose to limit MultiChild analysis to images and focus on assessing severity in videos, balancing comprehensiveness with care.
Data collection should be driven by purpose, not just possibility. More isn’t always better, and good practice means making informed trade-offs, balancing data quality with human impacts.
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