The latest publication co-authored by Mark Findlay, one of the founding partners of the International Network for Digital Self-Determination, is set to redefine the discourse on AI and Big Data governance. 

Titled "AI and Big Data: Disruptive Regulation," the book provides an alternative narrative that challenges conventional frameworks surrounding technology regulation. Nowadays AI technologies and big data are seen as the drivers for disruptive innovation, and therefore there is a requirement of strict regulatory oversight to mitigate their potential negative risks. Findlay's work turns this idea about AI and Big Data, by proposing that instead they can be harnessed for social good, especially in the governance of digital transformation. Therefore, the purpose of the book is to “investigate and establish AI and big data as the solution and not the problem when responsible regulatory disruption is envisaged”

The book underscores the critical importance of trust and ethics in the digital age, by showcasing diverse case studies where technology companies have monopolized data, often at the expense of underserved communities. Findlay suggests a disruptive approach, one where digital self-determination is the cornerstone for equitable data arrangements and empowered data subjects.

The book has garnered praise from leading scholars. Urs Gasser from the Technical University of Munich states that the book offers a "compelling reframing of the orthodox tech-and-regulation relationship", thanks for its "wisely selected case studies."  Similarly, Stefaan G. Verhulst from New York University affirms the work is a "must-read," applauding its practical pathways to advance digital self-determination and promote fairness and non-discrimination.

The book ultimately is a relevant resource for students, policymakers, and professionals in the fields of data, regulation and governance since it serves as a critical milestone in the quest for more responsible and inclusive digital regulation. Its challenge to conventional thinking enriches the literature on data governance and provides evidence-based perspectives on regulation that empowers people and promotes trust and data responsibility.