Cash

'Privacy as a Public Good: A Case for Electronic Cash' by Rodney Garratt and Maarten R.C. van Oordt comments

Privacy is a feature inherent to the use of cash for payments. With steadily increasing market shares of commercial digital payments platforms, privacy in payments may no longer be attainable in the future. In this paper, we explore the potential welfare impact of reductions in privacy in payments in a dynamic framework. In our framework, firms may use data collected through payments to price discriminate among future customers. A public good aspect of privacy in payments arises because individual customers do not bear the full costs of failing to protect their privacy. As a consequence, they may sub-optimally choose not to preserve their privacy in payments. When left to market forces alone, the use of privacy-preserving means of payments, such as cash, may decline faster than is optimal.

Health Justice

'When Law is Good for Your Health: Mitigating the social determinants of health through access to justice' by Hazel Genn in (2019) Current Legal Problems comments

Access to justice research over two decades has documented the health-harming effects of unmet legal needs. There is growing evidence of bidirectional links between law and health demonstrating that social and economic problems with a legal dimension can exacerbate or create ill health and, conversely that ill-health can create legal problems. Independently, social epidemiological research documents gross and widening inequalities in health, largely explained by social determinants such as income, housing, employment, and education. Although legal issues are embedded in most social determinants of health, law has been largely invisible in social determinants discourse, research and interventions. 

This article argues that legal services have an important role to play in mitigating many of the socio-economic determinants that disproportionately impact the health of low income and vulnerable groups. It describes the international practitioner-led movement of Health Justice Partnership through which lawyers work with healthcare teams to address the root causes of ill health rather than focusing on physical and psychological manifestations of negative social determinants. 

Finally, the article attempts to delineate the evolving field of health justice, advancing a transdisciplinary research agenda that could strengthen both public health and access to justice research by moving beyond the limitations of single discipline approaches. Noting the vigorous policy emphasis in law and health on prevention and partnership to address the twin challenges of access to justice and health inequalities, the article ends with a plea for policy coordination that acknowledges shared responsibility across government for improving the health of the public.

Minors

'Police perceptions of young people: a qualitative analysis' by Kelly Richards, Cassandra Cross and Angela Dwyer in (2019) 20(4) Police Practice and Research 360-375 comments

Police views of young people inform the way they exercise discretion over this group. However, few studies have sought to formally document and examine police views of young people. The limited existing research is also mostly dated. This article begins to address this gap in the literature by presenting the results of semi-structured qualitative interviews with 41 police officers from Queensland, Australia. Stemming from a larger study of Police-Citizens Youth Clubs and using a grounded theory approach to data analysis, the article demonstrates the key ways in which police conceptualised young people. It reveals that while police had varied views, they predominantly constructed young people as in need of intervention. The article concludes by arguing that such a conceptualisation of young people could be problematic, given that police intervention has been shown to be a strong predictor of future criminal justice involvement.

Entick

Timothy A.O. Endicott's 'Was Entick v Carrington a Landmark?' in Adam Tomkins and Paul Scott (eds), Entick v Carrington: 250 Years of the Rule of Law (Hart, 2015) 109-130 comments

Entick v Carrington (1765) 2 Wils KB 275 was a landmark not only in the development of the law of the constitution, but also in the development of a distinctively English mixture of judicial restraint and judicial creativity. Lord Camden’s decision was a model of the common law method of devising new ways of controlling public powers, while disclaiming any power to legislate and, in fact, claiming to abide by the ‘ancient venerable edifice’ of the constitution. The result was a practical reform that protected civil liberties, on the basis of a very conservative understanding of the constitution, according to which public authorities are limited by law, but have powers that are not specified by law. I defend that understanding against the twenty-first-century idea that public authorities may do nothing except what the law expressly or impliedly authorises.

Artificial Intelligence and Autonomy

The Artificial Intelligence Governance and Ethics: Global Perspectives report by Angela Daly, Thilo Hagendorff, Li Hui, Monique Mann, Vidushi Marda, Ben Wagner, Wei Wang and Saskia Witteborn comments

 Artificial intelligence (AI) is a technology which is increasingly being utilised in society and the economy worldwide, and its implementation is planned to become more prevalent in coming years. AI is increasingly being embedded in our lives, supplementing our pervasive use of digital technologies. But this is being accompanied by disquiet over problematic and dangerous implementations of AI, or indeed, even AI itself deciding to do dangerous and problematic actions, especially in fields such as the military, medicine and criminal justice. These developments have led to concerns about whether and how AI systems adhere, and will adhere to ethical standards. These concerns have stimulated a global conversation on AI ethics, and have resulted in various actors from different countries and sectors issuing ethics and governance initiatives and guidelines for AI. Such developments form the basis for our research in this report, combining our international and interdisciplinary expertise to give an insight into what is happening in Australia, China, Europe, India and the US. 

What is AI? 

Artificial Intelligence (AI) is an emerging area of computer science. There are numerous definitions and various terms used interchangeably to describe ‘AI’ within the academic literature (and also popular discourse) - these include, for example: algorithmic/profiling, automation, (supervised/unsupervised) machine learning, deep neural networks etc. 

In general terms, AI could be defined as technology that automatically detects patterns in data, and makes predictions on the basis of them. It is a method of inferential analysis that identifies correlations within datasets that can, in the case of profiling, be used as an indicator to classify a subject as a representative of a category or group (Hildebrandt 2008; Schreurs et al 2008). A broad distinction is made between ‘narrow’ and ‘general’ or ‘broad’ AI. Narrow AI is an AI application which is designed to deal with one particular task and reflects most currently existing applications of AI in daily life, while general or broad AI reflects human intelligence in its versatility to handle different or general tasks. In this report when we discuss AI we refer to AI in its narrow form. 

There are numerous applications of AI in a range of domains, perhaps contributing to definitional complexity, for example, predictive analytics (such as recidivism prediction in criminal justice contexts, predictive policing, forecasting risk in business and finance), automated identification via facial recognition etc. Indeed, AI has been deployed in a range of contexts and social domains, with mixed outcomes, including insurance, finance, education, employment, marketing, governance, security, and policing (see e.g., O’Neil 2016; Ferguson 2017). 

AI and Ethics 

At this relatively early stage in AI’s development and implementation, the issue has arisen of AI adhering to certain ethical principles (see e.g. Arkin 2009; Mason 2017), and the ability of existing laws to govern AI has emerged as key as to how future AI will be developed, deployed and implemented (see e.g. Leenes & Lucivero 2015; Calo 2015; Wachter et al. 2017a). 

While originally confined to theoretical, technical and academic debates, the issue of governing AI has recently entered the mainstream with both governments and private companies from major geopolitical powers including the US, China, European Union and India formulating statements and policies regarding AI and ethics (see e.g. European Commission 2018; Pichai 2018). 

A key issue here is precisely what are the ethical standards to which AI should adhere? Furthermore, the transnational nature of digitised technologies, the key role of private corporations in AI development and implementation and the globalised economy gives rise to questions about which jurisdictions/actors will decide on the legal and ethical standards to which AI may adhere, and whether we may end up with a ‘might is right’ approach where it is these large geopolitical players which set the agenda for AI regulation and ethics for the whole world. Further questions arise around the enforceability of ethics statements regarding AI, both in terms of whether they reflect existing fundamental legal principles and are legally enforceable in specific jurisdictions, and also the extent to which the principles can be operationalised and integrated into AI systems and application in practice. 

What does ‘ethics’ mean in AI? 

Ethics is seen as a reflection theory of morality or as the theory of the good life. A distinction can be made between fundamental ethics, which is concerned with abstract moral principles, and applied ethics (Höffe 2013). The latter also includes ethics of technology, which contains in turn AI ethics as a subcategory. Roughly speaking, AI ethics serves for the self-reflection of computer and engineering sciences, which are engaged in the research and development of AI or machine learning. In this context, dynamics such as individual technology development projects, or the development of new technologies as a whole, can be analyzed. Likewise, causal mechanisms and functions of certain technologies can be investigated using a more static analysis (Rahwan et al. 2019). Typical topics are self-driving cars, political manipulation by AI applications, autonomous weapon systems, facial recognition, algorithmic discrimination, conversational bots, social sorting by ranking algorithms, and many more (Hagendorff 2019). Key demands of AI ethics relate to aspects such as the reflection of research goals and purposes, the direction of research funding, the linkage between science and politics, the security of AI systems, the responsibility links underlying the development and use of AI technologies, the inscription of values in technical artefacts, the orientation of the technology sector towards the common good, and much more (Future of Life Institute 2017). 

Last but not least, AI ethics is also reflected within the framework of metaethics, in which questions about the effectiveness of normative demands are investigated. Ethical discourses can either be held with close proximity to their designated object, or it can be the opposite. The advantage of a close proximity is that those ethical discourses can have a concrete impact on the course of action in a particular organization dealing with AI. The downside is that this kind of ethical reflection has to be quite narrow and pragmatic. Uttering more radical demands only makes only sense when ethical discourses have a certain distance to their designated object. Nevertheless, those ethical discourses are typically rather inefficient and have hardly any effect in practice. 

Another dimension of AI ethics concerns the degree of its normativity. Here, ethics can oscillate between irritation and orientation. Irritation equals weak normativity. This means an abstinence from strong normative claims. Instead, ethics just uncovers blind spots or describes hitherto underrepresented issues. Orientation, on the other hand, means strong normativity. The downside of making strong normative claims is that they provoke backfire- or boomerang-effects, meaning that people tend to react to perceived external constraints on action with that kind of behaviour they are supposed to refrain from. 

Therefore, AI ethics must satisfy two traits in order to be effective. First, it should use weak normativity and should not universally determine what is right and what is wrong. Second, AI ethics should seek close proximity to its designated object. This implies that ethics is understood as an inter- or transdisciplinary field of study, that is directly linked to the adjacent computer sciences or industry organizations, and that is active within these fields. 

This Report 

In this Report we combine our interdisciplinary and international expertise as researchers working on AI policy, ethics and governance to give an overview of some of our countries and regions’ approaches to the topic of AI and ethics. We do not claim to present an exhaustive account of approaches to this issue internationally, but we do aim to give a snapshot of how some countries and regions, especially ‘large’ ones like China, Europe, India and the United States are, or are not, addressing the topic. We also include some initiatives at national level of EU Member States (Germany, Austria and the United Kingdom) and initiatives in Australia, all of which can be considered ‘smaller’. The selection of these countries and regions has been driven by our own familiarity with them from prior experience. 

We acknowledge the limitations of our approach, that we do not have contributions regarding this issue from Africa, Latin America, the Middle East, Russia, Indigenous views of AI and AI and ethics approaches informed by religious beliefs (see e.g. Cisse 2018; ELRC 2019; Indigenous AI n.d.). In future work we hope to be able to cover more countries and approaches to AI ethics. 

We have specifically looked to government, corporate and some other initiatives which frame and situate themselves in the realm of ‘AI governance’ or ‘AI ethics’. We acknowledge that other initiatives, such as those relevant to ‘big data’ and the ‘Internet of Things’ may also be relevant to AI governance and ethics; but with a few exceptions, these are beyond the scope of this report. Further work should be done on ‘connecting the dots’ between some predecessor digital technology governance initiatives and the current drive for AI ethics and governance. The fast-moving nature of this topic and field is our reason for publishing this report in this current form. We hope the report is useful and illuminating for readers.

'Are Autonomous Entities Possible?' by Shawn Bayern in (2019) 114 Northwestern University Law Review Online 23 comments

Over the last few years, I have demonstrated how modern business-entity statutes, particularly LLC statutes, can give software the basic capabilities of legal personhood, such as the ability to enter contracts or own property. Not surprisingly, this idea has been met with some resistance. This Essay responds to one kind of descriptive objection to my arguments: that courts will find some way to prevent the results I describe either because my reading of the business-entity statutes would take us too far outside our legal experience, or because courts will be afraid that robots will take over the world, or because law is meant to promote human (versus nonhuman) rights. As I demonstrate in this essay, such objections are not correct as a descriptive matter. These arguments make moral and policy assumptions that are probably incorrect, face intractable line-drawing problems, and dramatically overestimate the ease of challenging statutorily valid business structures. Business-entity law has always accommodated change, and the extensions to conventional law that I have identified are not as radical as they seem. Moreover, the transactional techniques I advocate for would likely just need to succeed in one jurisdiction, and regardless, there are many alternative techniques that, practically speaking, would achieve the same results.

'First Steps Towards an Ethics of Robots and Artificial Intelligence' by John Tasioulas in (2019) 7(1) Journal of Practical Ethics comments

 This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition to exploring some illustrative issues arising under each rubric, the article also emphasizes a number of more general themes. These include: the multiplicity of interacting levels on which ethical questions about RAIs arise, the need to recognise that RAIs potentially implicate the full gamut of human values (rather than exclusively or primarily some readily identifiable sub-set of ethical or legal principles), and the need for practically salient ethical reflection on RAIs to be informed by a realistic appreciation of their existing and foreseeable capacities.

Trade Mark Cluttering and the DNS

'Does trade mark cluttering exist in Australia?' (IP Australia Economic Research Paper 07) comments

When cluttering of the trade mark register becomes significant, it has the potential to undermine competition and stifle innovative entrepreneurship. The Productivity Commission’s 2016 Inquiry Report, Intellectual Property Arrangements (PC 2016), identified trade mark cluttering as a possible problem to be addressed in order to ensure the effectiveness of the trade mark system in Australia. However, the PC report did not provide sufficient evidence in support of this claim. This paper explores more extensively whether there is any evidence indicating trade mark cluttering in Australia and assesses how significantly it has been affecting the register. We find that overall the extent of trade mark cluttering in Australia is not unduly serious on the evidence of two key indicators: less than 0.1 per cent of registered trade marks have been removed annually by a third party via the non-use removal procedures; while about 0.5 per cent of trade marks in force may be blocking other applications while they are not in use. Relative to the total number of trade marks on the register, these small proportions do not seem to be cause for concern. 

Nevertheless, potential sources of trade mark cluttering have been increasing in Australia: the first renewal rate has decreased from about 70 per cent in the 1980s to 50 per cent in the 2000s, and an increasing number of trade marks remain on the register for an average of an extra four to five years after their owners deregister their businesses. A comparison of the average number of classes per trade mark between Australia and some countries and priority pairs between Australia and the United States indicates that the per-class-based fee system and proof-of-use requirement have played a positive role in reducing the extent to which non-use trade marks and overly broad non-use classes remain on a register.

IP Australia states

Trade marks identify a unique product and serve to distinguish a business’s goods and services from those of competitors. The mark can be a symbol, letter, number, word, phrase, sound, smell, shape, logo, picture and/or an aspect of packaging. In the case of word marks, studies have found that the most competitively effective trade marks for businesses are unique and concise, with short common words generally working better than neologisms (Beebe and Fromer, 2018). 

Consumers often know little about the characteristics of the goods or services they are considering purchasing and there are numerous unobservable differences in the quality of goods and services. Trade marks therefore play an important role in bridging the information asymmetries between producers and consumers. For consumers, a unique trade mark helps them to identify their desired product by associating it with various attributes that serve to establish its quality and reputation. For producers, a registered trade mark gives the owner the exclusive right to use and authorise other people to use the trade mark. 

With clarity in trade marks, producers and sellers can create concise identifiers for specific goods and services, thereby facilitating market transactions. Therefore, clarity in the Trade Marks Register serves to provide transparency to other potential traders and enable them to easily identify where market opportunities do, or do not, exist and enabling them to target gaps in the market. 

Trade marks are by far the most widely used intellectual property (IP) right because they are not specific to an invention, like patents or design rights, but to the broader identity of a business. Trade marks are the legal underpinning of a business’s brand and the two concepts are closely related but often confused. A brand is an intangible asset that makes up a significant share of a company’s value, and branding is a key arm of a company’s business strategy.  Branding is also integral to a business’s innovation strategy, as it reflects the business’s attempts to define and position itself in the marketplace. Maintaining a business’s brand reputation is an ongoing work that involves continual refinement of its strategy and investment in response to the dynamics of changing markets and consumer tastes. A strong brand helps a business build customer loyalty and obtain a price premium for its products, increasing its revenues and profits. Trade marks are important for the protection of a business’s brand reputation.   

Trade mark cluttering refers to a phenomenon suspected to be a problem for many trade mark registers around the world: it occurs when a large number of unused trade marks or overly broad trade marks (including unused classes) remain on a register that block others’ use of the same or similar marks. This clutter substantially increases the costs to other applicants of creating and registering new trade marks (Graevenitz et al. 2012). These costs are an obvious burden for new entrants to a market, but they can also affect existing businesses trying to create new trade marks. Trade mark cluttering can undermine the effectiveness and the efficiency of the trade mark system by making it more difficult and expensive for new applicants to establish their brands, resulting in unfair advantages for incumbent firms over new entrants (Greenhalgh and Webster 2015). Consequently, it weakens the role of the trade mark system in promoting fair competition (Carter 1990) and increases the cost to consumers of searching and identifying their desired products in the market. Trade mark cluttering also has a negative impact on trade mark offices in terms of their wasted efforts administering unused trade marks and searching inflated trade mark registers. 

Closely related to trade mark cluttering are problems of trade mark depletion and congestion; these have been closely examined in the US by Beebe and Fromer (2018). Trade mark depletion occurs when a decreasing number of available words, signs, or their combinations remain unclaimed by any trade mark owner. Implicitly, depletion assumes the supply of trade marks is finite, contrary to an assumption that has long prevailed in economic thinking about trade marks (c.f. Posner and Landes, 1989) and governed policymaking. By contrast, trade mark congestion happens when, for any given mark that has already been claimed, that mark is claimed by an increasing number of trade mark owners. This can occur when a trade mark is assigned to multiple owners but in different classes of goods and services, as allowed under the Nice classification system administered by the World Intellectual Property Organization (WIPO). 

The problems associated with trade mark cluttering may be exacerbated and become systemic if growing numbers of applicants try to register trade marks but with no intention of future use, whether for defensive or other reasons (Graevenitz et al. 2012). 

The Productivity Commission’s 2016 Inquiry Report, Intellectual Property Arrangements (PC 2016), identified trade mark cluttering as a potential problem that needs to be addressed in order to ensure the effectiveness of the trade mark system in Australia. The Commission’s assessment was based on two main indicators of trade mark cluttering:

i. Rapid growth in the number of applications and registrations of trade marks in Australia in recent decades. 

ii. An increasing success rate of oppositions to trade mark applications on the grounds that the provisions of a mark were too similar to an existing mark (s. 44 of the Trade Marks Act (1995)) or that another similar mark already has achieved a reputation in Australia (s. 60). 

The Commission’s report largely attributed the cluttering to the introduction of the presumption of registrability in the Act, and suggested that this has swung the balance too far in favour of trade mark owners. IP Australia observed that the presumption of registrability was introduced in response to concerns that the previous legislation was too strict and prevented registration of marks that should have been registrable. It argued that “the increased likelihood of a trade mark application being registered is not in itself evidence that the register is cluttered” (IP Australia 2016). While the Commission’s report suggested Australia’s trade mark system is “lax” in encouraging businesses to seek rights as broadly as possible, it did not conclusively demonstrate the existence of significant cluttering in Australia as it did not provide evidence on non-use of trade marks on the register. 

In its submission to the Commission’s inquiry, IP Australia agreed that the trade mark system should not encourage applicants to seek registration of their trade marks without any intention to use them or for more goods or services than they need. IP Australia also suggested that this is an area in which more work should be done in order to identify the nature and extent of the problem (IP Australia 2016). It is against this policy background that the Office of the Chief Economist at IP Australia initiated its own investigation into the potential existence of trade mark cluttering in Australia, with the aim of providing an evidence base to support IP policymaking by the Australian Government.

'Confusing the Similarity of Trademark Law in Domain Name Disputes' by Christine Haight Farley in  (2019) 52 Akron Law Review 657 comments

This article anticipates doctrinal disorder in domain name disputes as a result of the new generic top-level domains (gTLDs). In the course of the intense and prolonged debate over the possibility of new gTLDs, no one seems to have focused on the conspicuous fact that domain name disputes incorporating new gTLDs will be markedly different from the first-generation domain name disputes under previous gTLDs. Now second-generation disputes will have the added feature of the domain name having a suffix that will likely be a generic word, geographic term, or trademark. This addition is significant. Rather than disputes over mcdonalds.com, we will have disputes over mcdonalds.ancestry. Before these new gTLDs, Uniform Dispute Resolution Procedure (UDRP) panels have routinely ignored the gTLD portion of the domain concluding that the suffix is inconsequential to their determinations of confusing similarity. This approach has already changed. While this change may seem trivial especially in a non-precedential system, the consequence of this change may be profound for trademark owners’ rights on the internet and portend a fundamental shift in how trademarks will be called upon to pick winners and losers in this new land grab. Farley,  

Designs

An IPRIA and IP Australia study of Designs Law and Practice  comments

Design capability is increasingly recognised as a source of competitive advantage among countries, and as central to how firms in a diverse range of industries strive to outperform their rivals (Gruber et al., 2015). Australia’s design workforce is small, compared to those of our competitor countries, though productive (Figure 1). However, Australia lags its global peers in the rate at which its design workforce is growing, and in its rate of growth in design intellectual property (IP) generation.

Recognising the importance of design for Australia’s future, IP Australia initiated a collaboration with the Intellectual Property Research Institute of Australia (IPRIA) at The University of Melbourne to produce a comparative study of designs law and practice. This study explores both design across industries within Australia, and how Australia compares for design with its international peers, including several major trading partners.

Recent studies have assessed the suitability of registered design rights as a source of potential information about design innovation (Filitz, Henkel and Tether, 2015; Tucci and Peters, 2015). Yet, there is a lack of research connecting design registrations with design inputs or investments (de Rassenfosse, 2017). 

Our study brings together two well-established approaches for measuring design activity: 

Design IP intensity is a measure of the number of designs registered in a country or industry. 

Design labour intensity is a measure of the number of persons employed in design related occupations, either at the country or industry level.

Both these intensity measures are normalised to account for country or industry level differences. 

This study is the first to our knowledge that brings together these methods to explore, simultaneously, the relative size of design labour forces, and their productivity in design IP generation. 

The report is divided into seven sections inclusive of this introduction.

• Section 2 provides an overview of the designs legal system in Australia and the international context • Section3brieflysetsoutthestudy’smethodology 

• Section 4 explores how Australia compares to its international peers for design labour intensity and the intensity with which Australians use design IP 

• Section 5 explores how industries within Australia vary in design labour intensity and design IP intensity 

• Section 6 presents analysis of the design intensity of industries across national contexts 

• Section 7 discusses potential factors that may affect registrations patterns and offers concluding remarks.

A central finding of this study is that the intensity with which a country makes use of the designs system increases with the design labour intensity of its workforce. Our findings also suggest that a country’s design IP intensity is positively associated with the degree to which design labour is concentrated across its industries. The question this raises is how extensively the designs system encourages investment across the design community at large. To gain greater understanding of Australia’s position, we explored the industries and products in which design filers focus (by “design filers” we refer to applicants of registered designs). Within Australia, residents and non-residents focus in contrasting sectors when registering designs. Australians typically focus in furniture, building materials and clothing manufacturing. By contrast, non-resident applicants maintain a focus in industries such as computer and telecommunications equipment manufacturing. 

We identify those product classes in which there is the greatest imbalance between residents and non- residents in terms of their shares of a class’s total design filings. Of those product classes in which the focus of Australian and non-resident filers is most divergent, non-residents dominate within a large share. We find this to be the case also for certifications and renewals of registered designs. A potential implication is that non-residents focus more strongly on product classes with longer design lifecycles. 

This research was conceived to generate inputs into IP Australia’s Designs Review Program. As such, our focus in studying design IP intensity is on registered design rights. Those design artefacts which are protected by other forms of IP or which are not protected at all fall outside the scope of this study. 

Taking a narrow view of design, we identify from among our global peers several countries that are worthy of emulation as design leaders. We identify, as well, several followers with strengthening design economies. Denmark and Sweden are examples of countries that are low in design IP intensity and low in design labour intensity also, but which are growing at a high rate on both measures.

In the Australian context, we identify industries which appear to underutilise the designs system, given their design labour intensity. This lays ground for further research to address the strengths and weaknesses of Australia’s designs system.