Skip to main content

Researching the Darkside of Internet Filtering

The OpenNet Initiative (ONI) is a collaborative partnership of four leading academic institutions -- the Citizen Lab at the Munk Centre for International Studies, University of Toronto; the Berkman Center for Internet & Society at Harvard Law School; the Advanced Network Research Group at the Cambridge Security Programme, University of Cambridge; and the Oxford Internet Institute, Oxford University.

Their aim is to investigate, expose and analyze Internet filtering and surveillance practices in a credible and non-partisan fashion. They intend to uncover the potential pitfalls and unintended consequences of these practices, and thus help to inform better public policy and advocacy work in this area. To achieve these aims, the ONI employs a unique multi-disciplinary approach that includes:

- Development and deployment of a suite of technical enumeration tools and core methodologies for the study of Internet filtering and survellance;

- Capacity-building among networks of local advocates and researchers;

- Advanced studies exploring the consequences of current and future trends and trajectories in filtering and surveillance practices, and their implications for domestic and international law and governance regimes.

Popular posts from this blog

The AI Application Integration Challenge

Artificial intelligence (AI) has rapidly become the defining force in business technology development, but integrating AI into applications remains a formidable challenge. According to a recent Gartner survey, 77 percent of engineering leaders identify AI integration in apps as a major hurdle for their organizations. As demand for AI-powered solutions accelerates across every industry, understanding the tools, the barriers, and the opportunities is essential for business and technology leaders seeking to evolve. The Gartner survey highlights a key trend: while AI’s potential is widely recognized, the path to useful integration is anything but straightforward. IT leaders cite complexities in embedding AI models into existing software, managing data pipelines, ensuring security, and maintaining compliance as persistent obstacles. These challenges are compounded by a shortage of skilled AI engineers and the rapid evolution of AI technologies, which can outpace organizational readiness and...