Council of Europe HUDERIA Methodology and Model: COBRA — Interactive Tool

Kairan Zhao on the Limits of Machine Unlearning as a Privacy Method

Machine unlearning is a broad category encompassing a variety of techniques intended to remove - or lessen - the presence of sensitive information or concepts such as personal data, intellectual property like branded content and even artistic styles from machine learning models. In the privacy context, machine unlearning is often discussed in relation to the European Union's General Data Protection Regulation (GDPR) and its AI Act, as well as the California Consumer Privacy Act. But the chasm between what some in the policy world might believe machine unlearning can do and the actual technical capabilities of these methods is wide. 

Council of Europe HUDERIA Methodology and Model: COBRA — Interactive Tool

WPF has crafted a digital, interactive version of the Council of Europe's HUDERIA/COBRA assessment which allows for conducting a systematic AI risk analysis and exporting the results; session only, nothing saved. This tool is based on the CoE's official publication of the HUDERIA Methodology and HUDERIA Model: COBRA. WPF has created this tool as a digital public good.

Global Table of National AI Strategies

WPF's Global Table of National AI Strategies is a meticulously researched interactive data visualization. Researched and visualized to the UN M49 Standard, the data mapping includes filters for region, country, sectors, strategies with privacy initiatives, AI governance, date of launch, and more.

Privacy, Identity and Trust in C2PA

Global Table of Countries with Data Privacy Laws, Treaties, or Conventions

Risky Analysis: Assessing and Improving AI Governance Tools