Brussels / Washington – Committed to promoting transparency in the development of general-purpose artificial intelligence (GPAI) models, the Computer & Communications Industry Association (CCIA) is spearheading a groundbreaking initiative that introduces a new global industry template for transparency reporting on data used for training AI.
Today, the Association launches its Template for Transparency in AI Model Training Data with a view to increasing trust and improving understanding of AI training data.
Using the template, companies would disclose what types of data are used for training a particular GPAI model (ranging from podcasts to books), the main data sources concerned (such as open-access archives, large public datasets, or the scraping of public websites), and explain how that data is subsequently selected and employed for model training.
The new transparency template builds on eight core principles endorsed by CCIA’s Members, which include some of the world’s leading AI developers. The first principle underscores that “transparency measures may not compromise AI model safety, trade secrets, or confidential business information of both model providers and third parties.”
This CCIA-led initiative seeks to feed into the template that the European Commission is currently developing as part of the AI Act’s implementation. At the same time, the template also accounts for ongoing global developments. Indeed, CCIA stresses that the EU must seek alignment with international approaches and avoid setting standards in isolation.
The following can be attributed to CCIA Europe’s Senior Policy Manager, Boniface de Champris:
“CCIA wants to foster the responsible public disclosure of AI training data. Our transparency template provides a concise and effective way to report on training data, while safeguarding the security of AI models, companies’ valuable trade secrets and confidential information.”
The following can be attributed to CCIA Senior Counsel for Innovation Policy, Joshua Landau:
“Transparency measures can be helpful in maximizing the potential of AI, but these measures must be technically reasonable and proportionate. Striking the right balance is crucial to build trust and ensure compliance with legal and ethical standards, while still encouraging innovation in artificial intelligence.”
