Our Mission

The Challenge

Trust in information and media continues to decline rapidly, threatening our social cohesion, democratic institutions, and economic resilience. The proliferation of generative AI has the potential to exacerbate the erosion of trust in our media, education, science, business, and political process.

Mission

We formed Trust in Media Cooperative (TIM) to democratize trusted data, content, and news in a transparent and scalable manner. Our mission is more critical than ever as AI is increasingly shaping how we generate and consume information. Our commitment is to empower people to demand and use quality information and work together to achieve it. This will bring transparency and reliability to AI and information.

Through extensive and intense stakeholder engagements, we have learned that directing more attention to information that meets quality standards can greatly mitigate the consumption of inauthentic or misleading content. People who demand quality information can make better and faster decisions to provide value to their constituents. AI companies can leverage data integrity standards ensured by TIM’s metrics, measurements, and protocols to train better, safer, and more aligned models without being subject to costly and disruptive arbitrations. Reporters and journalists can build sustainable business models by directing more traffic to content that meets TIM’s standards and metrics. Tech policy bodies can utilize TIM to safeguard critical public goods such as election integrity, trusted media and science, respect for diversity, and trust in public institutions.

The demand for quality information is even more acute when AI is generating an increasing portion of digital content. For the feedback between quality and demand to scale in the information environment, we must develop a common language and agreed-upon standards that people and organizations can trust and count on. This is why TIM is a multi-disciplinary, cross-sector network focused on building a standard framework and language for trusted AI and information quality (InQ) and building a platform through which people and organizations can access information that is authentic, reliable, and accurate.