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Arising from the 2019 Darwin College Lectures, this book presents essays from seven prominent public intellectuals on the theme of vision. Each author examines this theme through the lens of their own particular area of expertise, making for a lively interdisciplinary volume including chapters on neuroscience, colour perception, biological evolution, astronomy, the future of technology, computer vision, and the visionary core of science. Featuring contributions by professors of neuroscience Paul Fletcher and Anya Hurlbert, professor of zoology Dan-Eric Nilsson, the futurist Sophie Hackford, Microsoft distinguished scientist Andrew Blake, theoretical physicist and author Carlo Rovelli, and Dr Carolin Crawford, the Public Astronomer at the University of Cambridge, this volume will be of interest to anybody curious about how we see the world.
Rapid technological change – the digitalization and automation of work – is challenging contemporary welfare states. Most of the existing research, however, focuses on its effect on labor market outcomes, such as employment or wage levels. In contrast, this paper studies the implications of technological change for welfare state attitudes and preferences. Compared to previous work on this topic, this paper adopts a much broader perspective regarding different kinds of social policy. Using data from the European Social Survey, we find that individual automation risk is positively associated with support for redistribution, but negatively with support for social investment policies (partly depending on the specific measure of automation risk that is used), while there is no statistically significant association with support for basic income. We also find a moderating effect of the overall size of the welfare state on the micro-level association between risk and preferences.
The present and past are insufficient guides for designing learning: we must also make wise use of futures thinking. Today, we have tools available that give clear indications of future trends. These trends are certainly not immutable; they will change but they also can be shaped. Educators need to consider how to prepare learners to understand and shape the direction and impacts of these trends. What it means to thrive has to be filtered through the awareness of emerging challenges for our planet, our societies and ourselves. Current scholarship and analysis suggest that humanity stands at the cusp of three great pivot points in its history. First, the planetary emergency, encompassing the climate crisis, consequences of the anthropocene, and the Sixth Great Extinction. Second, the apotheosis of technology, through artificial intelligence. And third, the possibilities for human evolution as multiple biomedical technologies converge. Never in human history have such profound, literally unprecedented changes been in prospect. But nothing is immutable. The future is not a straight line; it can and will be shaped by how and what young people learn in schools.
Thriving societies do not necessarily depend on high levels of wealth but on equality. First, access to employment is a key driver to create more equal societies; but the world of work is changing, becoming more automated, and less secure. Automation is likely to reduce employment opportunities, raising questions about the meaning of work in people's lives as well as how decent livable incomes can be guaranteed for all. To equip learners to navigate an uncertain and disrupted landscape of work must therefore be a central learning goal if societies are to thrive. Second, in a context where societies are becoming more not less unequal, the health of democracy must be central to education's purpose. Democracy as a driver towards equality is in trouble in many parts of the world. If it is to be renewed, learners need to understand its fundamentals and become committed to its renewal. Therefore a second learning goal in pursuit of thriving societies is to prepare young people to invent and inhabit a democracy which is participative, auhtentic and meaningful. The two levers for thriving societies – good work and democracy – must be nurtured in education's explicit purposes.
When some steps of a complex, multi-step task are automated, the demand for human work in the remaining complementary sub-tasks goes up. In contrast, when the task is fully automated, the demand for human work declines. Upon aggregation to the macroeconomic scale, partial automatability of complex tasks creates a bottleneck of development, where further growth is constrained by the scarcity of essential human work. This bottleneck is removed once the tasks become fully automatable. Theoretical analysis using a two-level nested constant elasticity of substitution production function specification demonstrates that the shift from partial to full automation generates a non-convexity: humans and machines switch from complementary to substitutable, and the share of output accruing to human workers switches from an upward to a downward trend. This process has implications for inequality, the risk of technological unemployment, and the likelihood of a secular stagnation.
Both conflict resolution aid (CRA) and vertical situation display (VSD) systems may contribute to air traffic control (ATC) operations. However, their effectiveness still needs to be examined before being widely adopted in ATC facilities. This study aims to examine empirically the use of CRA and VSD as well as the systems’ interaction in ATC operations. It was found that CRA benefited conflict resolution performance by 13⋅7% and lowered workload by 46⋅4% compared with manually performing the task. The VSD could also reduce the air traffic controllers’ (ATCOs) workload and improve their situation awareness. Ultimately, when the first CRA failure occurred, the situation awareness supported by VSD offset the performance decrements by 30%. The findings from this study demonstrate that integrating VSD with CRA would benefit ATC operations, regardless of the CRA's imperfection.
The research footprint of Information Technology (IT) in a legal system has not grown with the same pace as it has penetrated other domains. More specifically, in developing countries such as India, where the digitalization revolution is underway, the growth of legal informatics (LI) is still premature and very limited traces of IT can be observed to assist and elevate the legal system, which still functions very much in an old school way. The faster growth of population and the diminishing proportion of judicial executives and the deteriorating law and order situation along with declining human rights demand the urgent evolution of LI to grow at a very rapid pace to attain its maturity. However, the human harassments are pretty prevailing across the nation, but its intensity increases manifold when it comes to the law-enforcement agencies tasked with responsible policing, more specifically, the state police, which often operates with compromised work ethics. The situation becomes more appalling with a vulnerable population, especially women. As a result, such a population often does not muster enough courage to go to a police station to file their complaints despite acute mental and emotional pain. This is to avoid further trauma by police harassment and ergo a large number of cases go unnoticed. An underprivileged rape victim, who tries to file a report by going to a police station is a classic example of such a situation; where she is not only denied, but also gets harassed by insensitive police official(s) at the station; consequently, a good number of such victims do not go and their cases are not reported.
In this research work, we have developed a computational framework, called eLegalls, an LI-enabled innovation, as an effective solution to the above stated issues. The eLegalls system facilitates users to file their reports to police in their geographic jurisdiction, through its efficient and secure interface without any in-person visit. The eLegalls will help the vulnerable population to avoid unwanted denial and impending harassment by the police official(s) at the police station. The system is also equipped with some secure and pertinent features for the lawyers or attorneys to efficiently advocate in assigned cases. The eLegalls is envisioned to eventually be a successful legal tech, effectively serving the community.
In an era of corporate surveillance, artificial intelligence, deep fakes, genetic modification, automation, and more, law often seems to take a back seat to rampant technological change. To listen to Silicon Valley barons, there's nothing any of us can do about it. In this riveting work, Joshua A. T. Fairfield calls their bluff. He provides a fresh look at law, at what it actually is, how it works, and how we can create the kind of laws that help humans thrive in the face of technological change. He shows that law can keep up with technology because law is a kind of technology - a social technology built by humans out of cooperative fictions like firms, nations, and money. However, to secure the benefits of changing technology for all of us, we need a new kind of law, one that reflects our evolving understanding of how humans use language to cooperate.
This chapter argues that the partial automation of managerial authority should not matter when determining whether platform workers are—or should be treated as—employees or independent contractors under the law. It offers a close reading of an end-user license agreement (EULA) between the on-demand transportation company Uber and its drivers. In particular, the chapter examines the relationship between the EULA and Uber’s use of algorithmic management to design, direct, monitor, evaluate, and compensate drivers’ work. By scrutinizing this relationship through a theory of the “self” implicit in contract law, the chapter shows that the EULA grants Uber rights to direct drivers’ work and determine the principal terms of the agreement as it goes along. This unilateral discretion is difficult to reconcile with what the law expects of an enforceable contract. Rather, it resembles the open-ended authority that the law permits an employer over its employees. Uber exercises its extra-contractual discretion through the App. Algorithmic management enables Uber continually to recalibrate its putative bargain with drivers to the company’s advantage. One lesson of this analysis is that decision makers tasked with evaluating the employment status of platform workers should take more seriously the contractual component of being an “independent contractor.”
Our society in the twenty-first century is being shaped evermore by sets of instructions running at data centers spread around the world, commonly known as “algorithms.” Although algorithms are not a recent invention, they have become widely used to support decision systems, arguably triggering the emergence of an algorithmic society.1 These algorithmic decision systems (ADS) are deployed for purposes as disparate as pricing in online marketplaces,2 flying planes,3 generating credit scores,4 and predicting demand for electricity.5 Advanced ADS are characterized by two key features. First, they rely on the analysis of large amounts of data to make predictive inferences, such as the likelihood of a default for a potential borrower or an increase in demand for electricity consumption. Second, they automate in whole or in part the execution of decisions, such as refusing a loan to a high-risk borrower or increasing energy prices during peak hours, respectively. ADS may also refer to less advanced systems implementing only one of these features. Although ADS generally have proven to be beneficial in improving the efficiency of making decisions, the underlying algorithms remain controversial, among other issues, because they are susceptible to discrimination, bias, and a loss of privacy – with the potential to even be used to manipulate the democratic processes and structures underpinning our society6 – alongside lacking effective means of control and accountability.
How does unemployment risk affect workers’ support for demanding active labour market policies (ALMPs)? There may be a substantial number of workers who experience unemployment risk from labour market disruptions. Yet, we know less about its impact on demanding ALMP support than the impact of unemployment status. Here, I explore the impact of unemployment risk through automation. Automation-threatened workers’ support for demanding ALMPs may be influenced by two opposing considerations that are linked to their potential reliance on welfare. First, they may worry about barriers to welfare access. Second, they may worry about welfare competition, especially under austerity. Their support for demanding ALMPs would hence depend on which consideration they find to be most salient. Based on the European Social Survey (2016) data on West European countries, I find that automation-threatened workers significantly support such policies. This may indicate that they find welfare competition concerns more salient than welfare access ones.
This chapter reviews the transformative effects of technology on dictionary-making, focusing on four main areas: the use of databases for storing and organising dictionary text; the creation and exploitation of corpora for use as the dictionary’s evidence base; the enhancement of the value and usability of corpus data through the application of software tools developed in the NLP (natural language processing) community; and the migration of dictionaries from print to online media. During the last half-century, activity in all these areas has brought fundamental changes to the way dictionaries are created and made available to their users. We trace the development of corpus-based lexicography in English, from the early work of John Sinclair and his colleagues in the 1980s to the present day. Lexicographers working in English and other widely used languages now have access to resources which would scarcely have been imaginable thirty years ago: very large corpora (measured in tens of billions of words) and sophisticated corpus-querying tools are routinely available. The move from print to digital publication is a more recent development, but no less significant. The far-reaching implications of these changes – for dictionary-makers and dictionary-users alike – are explored at every stage.
New ideas for diagnostics in clinical parasitology are needed to overcome some of the difficulties experienced in the widespread adoption of detection methods for gastrointestinal parasites in livestock. Here we provide an initial evaluation of the performance of a newly developed automated device (Telenostic) to identify and quantify parasitic elements in fecal samples. This study compared the Telenostic device with the McMaster and Mini-FLOTAC for counting of strongyle eggs in a fecal sample. Three bovine fecal samples were examined, in triplicate, on each of the three fecal egg-counting devices. In addition, both manual (laboratory technician) and automated analysis (image analysis algorithm) were performed on the Telenostic device to calculate fecal egg counts (FEC). Overall, there were consistent egg counts reported across the three devices and calculation methods. The Telenostic device compared very favourably to the Mini-FLOTAC and McMaster. Only in sample C, a significant difference (P < 0.05) was observed between the egg counts obtained by Mini-FLOTAC and by the other methods. From this limited dataset it can be concluded that the Telenostic-automated test is comparable to currently used benchmark FEC methods, while improving the workflow, test turn-around time and not requiring trained laboratory personnel to operate or interpret the results.
We introduce the concept of social sustainability, intertwined with ecological and economic aspects, to the field of service robots and comparable automation technology. It takes a first step towards a comprehensive guideline that operationalizes and applies social sustainability. By applying this guideline to the project MURMEL we offer a concept that collects and rates social key issues to visualize their individual importance. Social sustainability is an important and often overlooked aspect of sustainable technology development which should be considered in the early development phase.
With technologies advancing at a rapid pace, research exploring the potential impact of technologies on work (see Frey & Osborne, 2013, 2017) sparked widespread interest in the topic. This chapter reviews the emerging future-of-work domain with a focus on research efforts and key trends. This includes an overview of key future-of-work concepts, a brief review of historical examples of technological job disruption concerns, an exploration of the technological forces driving current work changes, a review of studies exploring the potential for automation, and an overview of opportunities for understanding and shaping the future of work.
For nearly 30 years, the business and scientific press has featured a constant stream of stories about the changing nature of work. While some organizations and occupations have changed substantially in recent years, the belief that such changes are relatively recent or relatively widespread is not well founded. First, the nature and organization of work has evolved continuously over time and the current changes are especially large. Second, there are very large sectors of the economy in which the changes in technology and the organization of work have been minimal. The belief that the nature of work is changing is in large part rooted in the tendency to mistake the brief period of economic stability and highly valued employment in the United Stats that followed the Second World War as the normal state rather than an anomaly. The nature of work is changing and will continue to change, but these changes are part of a long-term set of evolutionary changes, not a sudden or recent innovation.
This chapter accomplishes three primary goals. First, we review the history of technologies that have been influential in the world of work, from the abacus to innovations of the present day. We then identify eight characteristics that describe modern technologies: power, portability, usability, networking, encryption, ubiquity, immersion, and predictiveness. Finally, we present a SWOT analysis that identifies the implications of these characteristics for the future of work. In doing so, we demonstrate that although technological change is a constant, so too is humans’ ability to adapt to change.
We assess the long-run growth effects of automation in the overlapping generations framework. Although automation implies constant returns to capital and, thus, an AK production side of the economy, positive long-run growth does not emerge. The reason is that automation suppresses wage income, which is the only source of investment in the overlapping generations model. Our result stands in sharp contrast to the representative agent setting with automation, where sustained long-run growth is possible even without technological progress. Our analysis therefore provides a cautionary tale that the underlying modeling structure of saving/investment decisions matters for the derived economic impact of automation. In addition, we show that a robot tax has the potential to raise per capita output and welfare at the steady state. However, it cannot induce a takeoff toward positive long-run growth.
The authors summarize the main dynamic balancing methods of robotic mechanisms in this paper. The majority of dynamic balancing methods have been presented, and there may be other dynamic balancing methods that are not included in this paper. Each of the balancing methods is reviewed and discussed. The advantages and disadvantages of each method are presented and compared. The goal of this paper is to provide an overview of recent research in balancing. The authors hope that this study can provide an informative reference for future research in the direction of dynamic balancing of robotic mechanisms.
In this book, Sander Van der Leeuw examines how the modern world has been caught in a socio-economic dynamic that has generated the conundrum of sustainability. Combining the methods of social science and complex systems science, he explores how western, developed nations have globalized their world view and how that view has led to the sustainability challenges we are now facing. Its central theme is the co-evolution of cognition, demography, social organization, technology and environmental impact. Beginning with the earliest human societies, Van der Leeuw links the distant past with the present in order to demonstrate how the information and communications technology revolution is undermining many of the institutional pillars on which contemporary societies have been constructed. An original view of social evolution as the history of human information-processing, his book shows how the past offers insight into the present, and can help us deal with the future. This title is also available as Open Access.