In this position paper, we argue that users' online consents to terms of services and privacy notices is naturally impaired by the unbalanced powers between online service providers and their users. We argue that a full fledged legal document management system relying on semantic representation is key to resolving this conflict and facilitating transparency of Online Legal Documents, and we give a quick overview of the LegiCrowd project, a crowdsourced approach to legal documents annotation, which paves the way towards such solution.
As AI technology and automation permeate society horizontally, the law and the subsequent enforcement mechanism prove incapable of keeping pace. Concepts originating from the past like consent tend to maintain their static properties in an increasingly complex and dynamic space, thus resulting in a state of obsolescence. The law and its design and implementation properties are in need of radical update. The present paper argues that such update requires a transition from plain legal text to a full-fledged Legal Document Management Systems.
World Wide Web today is the outcome of a three stage
evolution. Web 1.0 refers to the so called static Web of documents in a
unidirectional broadcasting format. Web 2.0 introduced the web
of people, by allowing the sharing of user generated content and
further social networking. Web 3.0 or the Web of data, is currently
evolving under the idea of defining and linking structured data [
The rest of the paper is organised as follows: In Section 2 we provide a brief description of the information technology advancements to date and key characteristics thereof. Section 3 discusses inconsistencies and loopholes of the modern legal design. This Section also expands on that ground we argue that legal representation and modelling could be the solution for a radical update of the modern legal properties and enforcement mechanism, if put in the appropriate ethical context. Section 4 introduces the LegiCrowd platform, a crowdsourced legal document annotation system. Finally, Section 5 concludes the paper and provides some thoughts for future work. 2
Ubiquitous automation does not support the static format of the
online legal documents and the linked consent models. Terms of
services and privacy policies in their present form constitute an iconic
proof of inadequacy of the digital design. Complicated legal and
technical documents that no one reads, no one understands, and no
one cares about, govern the emerging data lifecycles for the benefit
of data driven business operations by extending their unhealthy
operational patterns. A piece of information of such magnitude
turns into an irrelevant node in the data value chain, hindering the
unfolding and systemic assertion of the evolving human centric
patterns. On top of that, modern businesses increasingly use consent
as a de facto standard for demonstrating privacy commitments and
wider legal compliance claiming consent provisions as proxies of
informed choice. This evolution has given rise to a situation where
many technology giants, on the pretext of providing improved
services, have begun to track every action of every user with little or
no transparency [
Such a formatting reality and the imposed data dispossession from the technology and digital service supply side, brings into the surface the need for dynamic, data-driven, and data-relevant legal and ethical enforcement. In the environment of Web 3.0, such an enforcement requires a data driven solution shaped with mathematical reasoning. It requires the transition to a ubiquitous legal representation and modelling apparatus; an extended Legal Document Management System comprised by structured legal data, methods, and tools for suficient syntactic and semantic representation, capable of generating documented, machine readable legal knowledge, using very diferent logic, norms, and languages.
The ethical starting point lies on the axiom expressed by [
The LegiCrowd project could be an answer for such a need for transparency, as it aims at creating a platform to render Online Legal Documents (OLDs), namely Privacy Notices and Terms of services, in a quick and easy to read format, such as icons, dataviz or simplified language through a crowdsourced approach. This requires first to design a semantically sound annotation tag set, as an ontology of descriptors. This is the goal of the current LegiCrowd Onto project, which relies on a number of competencies particularly related to natural knowledge modelling, law and corresponding visualisations thereof gathered in an international consortium. Such a platform aims at truly putting end users in the driver’s seat as it a) provides an ethical building block in the overall design, b) empowers end users to extract accurate legal information in context, to assess the levels of legal compliance and the ethics standards in place and c) provide or reject a consent on a truly informed basis. 5
No doubt, the practice and assertion of law in the Web 3.0 era is a combination of numerous language data inputs and outputs from multiple workflows. In the said legal workflows, the extraction, formulation, and exploitation of related metadata and provenance constitute a basic processing component towards Machine Learning models or Natural Language Processing applications, capable for more eficient legal enforcement. With high awareness of its potential societal impact, any decisions about legal data, methods, and tools tend to tie up with their impact on people and the society in a practical way thus bringing ethics in the automation foreground.
The LegiCrowd Onto consortium is lead by the French Non Profit
Organisation Association des Professionnels des Industries de la
Langue (APIL), and includes the National Technical University
of Athens (NTUA) and the Research, Consultant & Training firm
‘Future Now’, backed by MyData Greece, the Greek node of MyData
Global. It has received funding from the European Union’s Horizon
2020 research and innovation programme under the NGI TRUST
grant agreement no 825618. This project has been made possible
thanks to Short Term Scientific Missions conducted within the
framework of the enet collect Cost Action ([