Lifting the Cage of Consent: A Techno-Legal Perspective on Evolvable Trust Relationships

TL;DR

This paper advocates for evolvable trust systems supported by personalized legal processes to foster sustainable data exchange, addressing the limitations of traditional consent and aligning economic incentives with societal values.

Contribution

It introduces a novel framework for scalable, trust-based data relationships through technology-assisted legal processes, moving beyond punitive privacy legislation.

Findings

Evolvable trust systems can enhance long-term data relationships.

Legal processes can be personalized to support trust evolution.

Aligning economic incentives with societal goals improves data practices.

Abstract

Those concerned about privacy worry that personal data changes hands too easily. We argue that the actual challenge is the exact opposite: our data does not flow well enough, cultivating a reliance on questionable and often unlawful shortcuts in a desperate bid to survive within today's data-driven economy. Exclusively punitive interpretations of protective legislation such as the GDPR throw out the baby with the bathwater through barriers that equally hinder "doing the right thing" and "doing the wrong thing", in an abject mistranslation of how ethical choices correspond to financial cost. As long as privacy-friendly data treatment proves more expensive or complicated than readily available alternatives, economic imperatives will continue to outrank their legal counterparts. We examined existing legislation with the aim of facilitating mutually beneficial interactions, rather than more narrowly focusing on the prevention of undesired behaviors. In this article, we propose the implementation of evolvable trust systems as a scalable alternative to the omnipresent yet deeply broken delusion of ill-informed consent. We describe personalized, technology-assisted legal processes for initiating and maintaining long-term trust relationships, which enable parties to reliably and sustainably exchange data, goods, and services. Our proposal encourages a redirection of additional efforts towards the techno-legal alignment of economical incentives with societal ones, reminding us that - while trust remains an inherently human concept - technology can support people in evolving and scaling their relationships to meet the increasingly complex demands of current and future data landscapes.