Individuals, corporations, and governments are brimming with data, but often struggle with verifying and maintaining accuracy. Without the means to easily check the provenance, authenticity, and integrity of data, how can anyone trust the information they receive? How can systems comply with the regulations governing the collection, use, and management of such data?

The benefits of living in the information society vanish if information is untrustworthy. Disinformation campaigns and fake news rely precisely on the historical separation of information from its provenance, that is, on our inability to have assurance of the sources and processes that produce a piece of information. In business, the cost of using bad data is known, even quantifiable1. In society, the increasing difficulty of distinguishing good from bad information makes people sceptical of our capacity to collectively make sound decisions. If information becomes toxic, neither public debate nor democracy can work.

Confidence in the quality of data can be established by providing a transparent mechanism, called data provenance, to check a datum's origin and history of modifications. Although data provenance has been motivated in multiple domains for decades, including scientific workflow, cyber security, healthcare, and forensics, its application to media content (content provenance) has only been made a top priority by government and industry recently, pushed by crises that were fuelled by disinformation, such as the 2020 elections in the United States, the COVID-19 pandemic, and the war in Ukraine.

The imperative of restoring trust in information distributed online, notably by major news sources, has led to the first technical standard for Content Provenance and Authenticity (C2PA), released in June 2022.