Luis Enriquez recently wrote a blog post for us calling FAIR a “Swiss Army Knife” for its flexibility in handling analysis of different types of risks.
Luis is something of a Swiss Army Knife of the FAIR movement himself: Professor of Machine Learning at the Universidad Andina Simón Bolívar (Quito, Ecuador), Professor of Ethical Hacking, University of Lille, France, and General Director of Data Security at Ecuador’s data privacy protection agency.
He has been a valued contributor to our blog and FAIR Conferences, speaking at the 2023 conference on Using the FAIR Model for AI Risk-Based Accountability.
Watch my Meet a Member interview with Luis to learn how he came to FAIR and the creative new purposes he finds for the model, such as AI and data privacy analysis.
Trained as a lawyer and an information security practitioner, Luis was naturally drawn to cyber-privacy issues, but found the state of the art was compliance-focussed, just filling out checklists according to ISO or other standards. “Nobody was actually taking seriously how to put values” on data privacy for individuals, even though GDPR and other laws were backed up by fines.
Searching for a better approach, he found FAIR four years ago – and realized that it could be adapted to quantify privacy. “The FAIR ontology is very valuable,” he says. “I never try to change it.” He does, however, repurpose the FAIR factors while keeping them in relationship. Read his “Swiss Army Knife” blog post for the details.
In his job with Ecuador’s government “we are publishing guidelines for the country focusing on data protection. And part of that is how to actually have a risk-based compliance program…The first thing is working with my team on using FAIR as a tool.”
