The COIVD-19 pandemic has drawn an increasing level of attention to the role of online dispute resolution (ODR) in dispute resolution systems. As ODR becomes increasingly prevalent, unique characteristics of conducting text-based mediations via ODR platforms begin to surface, warranting discussion on modifying mediator practises to adapt to ODR platforms. This article shines a light on the advantages and disadvantages of text-based mediations through interviews with court administrators and mediators with text-based mediation experience. Accordingly, this article proposes recommendations on training mediators to use ODR platforms and modifying their practises to achieve the best outcomes in text-based mediations. Focusing on the qualitative data and information gathered from these conducted interviews, this article seeks to offer practical advice about preparing mediators to participate in text-based mediations.

The COVID-19 pandemic has forced courts around the world to embrace technology and other innovative measures in order to continue functioning. This article explores how Australian courts have approached this challenge. We show how adaptations in response to the pandemic have sometimes been in tension with principles of open justice, procedural fairness and access to justice, and consider how courts have attempted to resolve that tension.

This article will examine Online Dispute Resolution (ODR) from several perspectives to provide a comprehensive understanding of the global efforts to incorporate ODR in the e-commerce scope. Upon examining the nature and growth of both e-commercial activities and ODR, there will be an analysis from an international standpoint, where the article will discuss the relevant bodies and the progression of uniform standards in this regard. This is followed by an analysis of several jurisdictions, namely the United States, China, European Union and Australia. Finally, the essay will provide suggestions andrecommendations for the implementation of ODR.

What benefits do AI technologies introduce to the law and how can lawyers integrate AI tools into their everyday practice and dispute resolution? Can we teach robot mediators to understand human empathy and values to conduct a successful mediation? While the future of AI in the legal profession remains somewhat unknown, it is evident that it introduces valuable tools that enhance legal practice and support lawyers to better serve their clients. This paper discusses the practical ways in which AI is used in the legal profession, while exploring some of the major concerns and hesitation over value alignment, morality and legal formalism.

Some of the existential threats we currently face are global in the sense that they affect us all, and thus matter of global concern and trigger duties of moral global solidarity. But some of these global threats, such as the COVID-19 pandemic, are global in a second, additional, sense: discharging them requires joint, coordinated global action. For that reason, these twofold global threats trigger political – not merely moral – duties of global solidarity. This article explores the contrast between these two types of global threats with the purpose of clarifying the distinction between moral and political duties of global solidarity. And, in the absence of a fully developed global democratic institutional system, the article also explores some promising ways to fulfill our global political duties, especially those based on mechanisms of collective intelligence such as CrowdLaw, which might provide effective solutions to these global threats while enhancing the democratic legitimacy of public decision-making.

This study explores the spread of disinformation relating to the Covid-19 pandemic on the internet, dubbed by some as the pandemic’s accompanying “infodemic”, and the societal reactions to this development across different countries and platforms. The study’s focus is on the role of states and platforms in combatting online disinformation.
Through synthesizing answers to questions submitted by more than 40 researchers from 20 countries within the GDHR Network, this exploratory study provides a first overview of how states and platforms have dealt with Corona-related disinformation. This can also provide incentives for further rigorous studies of disinformation governance standards and their impact across different socio-cultural environments.
Regarding the platforms’ willingness and efficacy in removing (presumed) disinformation, a majority of submissions identifies a shift towards more intervention in pandemic times. Most submitters assess that this shift is widely welcomed in their respective countries and more often considered as taking place too slowly (rather than being perceived as entailing dangers for unjustified restrictions of freedom of expression). The picture is less clear when it comes to enforcing non-speech related infection prevention measures.
While the dominant platforms have been able to defend, or even solidify, their position during the pandemic, communicative practices on those platforms are changing. For officials, this includes an increasing reliance on platforms, especially social networks, for communicating infection prevention rules and recommendations. For civil society, the pandemic has brought an increasing readiness – and perceived need – to intervene against disinformation, especially through fact-checking initiatives.
National and local contexts show great variance at whether platform-driven disinformation is conceived as a societal problem. In countries where official sources are distrusted and/or seen as disseminating disinformation criticism against private information governance by platforms remains muted. In countries where official sources are trusted disinformation present on platforms is seen more negatively.
While Facebook, Twitter, and Instagram play important roles in the pandemic communication environment, some replies point towards an increasing importance of messaging apps for the circulation of Covid-19-related disinformation. These apps, like Telegram or WhatsApp, tend to fall under the radar of researchers, because visibility of content is limited and scraping is difficult, and because they are not covered by Network Enforcement Act-type laws that usually exclude one-to-one communication platforms (even if they offer one-to-many channels).
Vis-à-vis widespread calls for a (re)territorialization of their content governance standards and processes amid the pandemic, platform companies have maintained, by and large, global standards. Standardized, featured sections for national (health) authorities to distribute official information via platforms are exceptions thereto.

Terms-of-service based actions against political and state actors as both key subjects and objects of political opinion formation have become a focal point of the ongoing debates over who should set and enforce the rules for speech on online platforms.
With minor differences depending on national contexts, state regulation of platforms creating obligations to disseminate such actors’ information is considered dangerous for the free and unhindered discursive process that leads to the formation of public opinions.
Reactions to the suspension of Trump as not the first, but the most widely discussed action of platform companies against a politician (and incumbent president) provide a glimpse on the state of platform governance debates across participating countries.
Across the countries surveyed politicians tend to see the exercise of content moderation policies of large platform companies very critically
The majority of politicians in European countries seem to be critical of the deplatforming of Trump, emphasizing fundamental rights and calling for such decisions to be made by states, not private companies
These political standpoints stand in an unresolved conflict with the constitutional realities of participating countries, where incumbents usually cannot invoke fundamental rights when acting in their official capacities and where laws with “must carry” requirements for official information do not exist for social media and would likely only be constitutional for narrowly defined, special circumstances such as disaster prevention.
Facebooks’ referral of the Trump-decision to its Oversight Board sparked a larger debate about institutional structures for improving content governance. The majority of participating countries has experience with self- or co-regulatory press-, media- or broadcasting councils to which comparisons can be drawn, foreshadowing the possible (co-regulatory) future of governing online speech.
Media commentators in participating countries interpreted the deplatforming of Trump as a signal that far-right parties and politicians around the world may face increasing scrutiny, while conservative politicians and governments in multiple participating countries instrumentalized the actions against Trump as supposed proof of platform’s bias against conservative opinions.
Even without specific legal requirements on content moderation, submissions from several countries refer to a general – often: constitutional – privileging of speech of politicians and office holders. This could potentially support or even compel the decisions of platforms to leave content of political actors up even if it violates their terms of service.

In the new digital era as it is formed by the European digital strategy, the explosion of e-commerce and related technologies has led to the formation of tremendous volumes of customer data that could be exploited in a variety of ways. Customer relationship management (CRM) systems can now exploit these data sets to map consumers’ behaviour more effectively. As social media and artificial intelligence widened their penetration, firms’ interest shifted to chatbots in order to serve their customers’ needs. Nowadays, CRM and bots are developed in a parallel way. With the help of these virtual personal assistants, CRM establishes a virtual relationship with consumers. However, the extended collection and use of personal data under this scope may give rise to ethical and legal issues. In this article, the term CRM is defined, followed by an analysis of the way chatbots support CRM systems. In the second part, the legal context of chatbot use will be highlighted in an attempt to investigate whether there are personal data protection issues and whether certain rights or ethical rules are somehow violated. The draft AI Regulation, in combination with the provisions of GDPR and e-Privacy Directive, offers a significant background for our study. The article concludes by demonstrating the use of chatbots as an inherent part of the new digital era and lays special emphasis on the term ‘transparency’, which seems to penetrate the lawfulness of their use and guarantee our privacy.

Recent developments in artificial intelligence (AI) and robotics point to a close future collaboration between humans and machines. Even though the use of personal robots is not yet a phenomenon, findings in technical and legal literature highlight several possible risks inherent in the processing of personal data by such robots. This article contributes to the current discussions on the applicability of the GDPR to AI technologies from three aspects: (i) first, it encourages the use of a scenario method to predict possible future legal problems related to new technologies; (ii) second, it analyzes considerations with the support of the relevant case-law and present comparative expert opinions for overcoming the weak points of the GDPR relevant to AI; (iii) and finally, proposals made in the recommendations part aim to contribute to a better application of the GDPR to AI technologies in personal use.

Many questions facing legal scholars and practitioners can be answered only by analysing and interrogating large collections of legal documents: statutes, treaties, judicial decisions and law review articles. I survey a range of novel techniques in machine learning and natural language processing – including topic modelling, word embeddings and transfer learning – that can be applied to the large-scale investigation of legal texts

The article offers a reflection on how applications of computer technology (including data analytics) are and may be taught to (future) lawyers and what are the benefits and limitations of the different approaches. There is a growing sense among legal professionals and law teachers that the technological changes in the practice of law are likely to promote the kind of knowledge and skills that law graduates often do not possess today. Teaching computer technology can be done in various ways and at various depths, and those different ways and levels have different cost and benefit considerations. The article discusses four models of teaching technology: (1) teaching basic technological literacy, (2) more advanced but general technology teaching, (3) teaching computer programming and quantitative methods and (4) teaching a particular aspect of technology – other than programming (e.g. cybersecurity). I suggest that there are strong reasons for all current and future lawyers to acquire proficiency in effective uses of office and legal research software and standard means of online communication and basic cybersecurity. This can be combined with teaching of numerical and informational literacy. I also claim that advanced technology topics, like computer programming, should be taught only to the extent that this is justified by the direct need for such skills and knowledge in students’ future careers, which I predict to be true for only a minority of current lawyers and law students.

The adoption of big data analysis in the legal domain is a recent but growing trend that highlights ethical concerns not just with big data analysis, as such, but also with its deployment in the legal domain. This article systematically analyses five big data use cases from the legal domain utilising a pluralistic and pragmatic mode of ethical reasoning. In each case we analyse what happens with data from its creation to its eventual archival or deletion, for which we utilise the concept of ‘data life cycle’. Despite the exploratory nature of this article and some limitations of our approach, the systematic summary we deliver depicts the five cases in detail, reinforces the idea that ethically significant issues exist across the entire big data life cycle, and facilitates understanding of how various ethical considerations interact with one another throughout the big data life cycle. Furthermore, owing to its pragmatic and pluralist nature, the approach is potentially useful for practitioners aiming to interrogate big data use cases.

Computational analysis can be seen as the most recent innovation in the field of Empirical Legal Studies (ELS). It concerns the use of computer science and big data tools to collect, analyse and understand the large and unstructured data, such as for instance (legal) text. Given that the text is now the object of analysis, but the methods are (largely) quantitative, it lies in the intersection between doctrinal analysis and ELS. It brings with it not only a great potential to scale up research and answer old research questions, but also to reveal uncovered patterns and address new questions. Despite a slowly growing number of legal scholars who are already applying such methods, it is underutilised in the field of law. Furthermore, given that this method comes from social and computer sciences, many legal scholars are not even aware of its existence and potential. Therefore, the purpose of this special issue is not only to introduce these methods to lawyers and discuss possibilities of their application, but also to pay special attention to the challenges, with a specific emphasis on the ethical issues arising from using ‘big data’ and the challenge of building capacity to use such methods in law schools. This editorial briefly explains some of the methods which belong to the new movement of Computational Legal Analysis and provides examples of their application. It then introduces those articles included in this special issue. Finally, it provides a personal note on the way forward for lawyers within the movement of Computational Legal Analysis

The Civil Code of the People’s Republic of China (Civil Code) came into force on 1 January 2021. Book III on Contracts of the Civil Code has adopted significant changes compared to the old Chinese Contract Law (Contract Law). This article provides a comprehensive and systemic analysis of those changes from structure to content, from legislative technics to values underpinning the Civil Code. It evaluates all the factors in the context of the development of Chinese society, Chinese culture and Chinese legal system.
This article first outlines the historical background of the development of the Contract Law and the Civil Code. It then moves on to compare the Civil Code and the Contract Law, highlighting the changes in structure, the incorporation of new provisions and the amendments to old provisions in light of contemporary Chinese society and culture. Finally, it argues that the Civil Code is a significant milestone in China’s legislative history; that it reflects the legislative experience and judicial practice in China; that it adds provisions which are innovative and of Chinese characteristics to meet the needs of China’s changing society and legal system; and that it keeps pace with the development of the global law reform and harmonization.

For the past 20 years, NCTDR has hosted a series of ODR Forums in locations around the world. For 2021, the Forum was held virtually, with live presentation over a web video platform, and recorded presentations available to participants. A full recording of the sessions can be found through http://odr.info/2021-virtual-odr-forum-now-live/. The following items are narrative notes from some of the presentations:

• David Allen Larson – ODR Accessibility

• Noam Ebner – Human Touch

• Jan Martinez & Amy Schmitz – ODR and Innovation

• Frank Fowlie – Online Sport Dispute Resolution

• Larry Bridgesmith – AI Introductory Notes

• Julie Sobowale – AI and Systemic Bias

• Clare Fowler – DEODRISE

• Michael Wolf – ODR 2.0 System Design

• Chris Draper – Algorithmic ODR

• Zbynek Loebl – Open ODR