*The Research Roundup is a semi-regular list of outside research we have found interesting and think is worth sharing. The views and conclusions of the papers’ authors do not necessarily reflect the opinions of anyone affiliated with TPI. The information below includes edited author abstracts*
Wherever we look, emerging technologies are changing some aspect of our day-to-day, be it how we absorb media or how we navigate traffic or how we manufacture and disseminate consumer goods. This month’s research roundup highlights the diversity and ubiquity of emerging tech. It features articles that evaluate the practical uses of technology, like Ariel Rosenfeld’s assessment of expectations around use of drones in traffic enforcement and Brent Skorup’s intriguing idea of auctioning airspace for drones and anything else that can fly. It also presents assessments of more abstract tech-related trends, like recent work by Daron Acemoglu and Pacual Restrepo, which argues that worker displacement by artificial intelligence will not be equal-opportunity. Other research touches upon big-picture concerns associated with technology applications like privacy and data security. Click through to read this month’s selected articles.
Descriptions of papers below are edited abstracts from authors
Daron Acemoglu & Pascual Restrepo
The authors argue theoretically and document empirically that aging leads to greater (industrial) automation, and in particular, to more intensive use and development of robots. Using US data, they document that robots substitute for middle-aged workers (those between the ages of (36 and 55) and then show that an increasing ratio of older to middle-aged workers is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across US commuting zones. The authors also provide evidence of more rapid development of automation technologies in countries undergoing greater demographic change, in particular an aging workforce. They present a directed technological change model that predicts that the induced adoption of automation technology should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation. Both of these predictions receive support from country industry variation in the adoption of robots. The model also implies that the productivity implications of aging are ambiguous when technology responds to demographic change, but that we should expect productivity to increase and labor share to decline relatively in industries that are most amenable to automation.
Karthik Muralidharan, Paul Niehaus, Sandip Sukhtankar, and Jeffrey Weaver
Improving “last mile” public-service delivery is a recurring challenge in developing countries. Could the rapid adoption of mobile phones provide a simple, cost-effective means to do so? The authors evaluate the impact of a phone-based monitoring system on improving the delivery of a program that transferred nearly a billion dollars to farmers in the Indian state of Telangana, using an at-scale experiment randomized across 5.7 million farmers. A randomly selected sample of officials were told that a representative sample of beneficiaries in their jurisdiction would be called to measure the quality of program implementation. This simple announcement led to a 1.5% increase in the number of farmers receiving their benefits, with a 3.3% increase among farmers in the bottom quartile of landholdings. The program was highly cost-effective, with a cost of 3.6 cents for each additional dollar delivered.
Merlinda Andoni, Valentin Robu, David Flynn, Simone Abram, Dale Geach, David Jenkins, Peter McCallum, and Andrew Peacock
Blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. Numerous sources coming from these backgrounds identify blockchains as having the potential to bring significant benefits and innovation. Blockchains promise transparent, tamper-proof and secure systems that can enable novel business solutions, especially when combined with smart contracts. This work provides a comprehensive overview of fundamental principles that underpin blockchain technologies, such as system architectures and distributed consensus algorithms. The authors focus on blockchain solutions for the energy industry and inform the state-of-the-art by thoroughly reviewing the literature and current business cases and highlighting both the potential benefits and limitations. It also includes a discussion of challenges and market barriers the technology needs to overcome to get past the hype phase, prove its commercial viability and finally be adopted in the mainstream.
Traffic enforcement drones reduce high-risk driving behavior which often leads to traffic crashes. However, the introduction of drones may face a public acceptance challenge which may severely hinder their potential impact. In this paper, the author reports and discusses the results of a drivers’ survey, administered both in the US and Israel, regarding the benefits, concerns and policy considerations for the deployment of traffic enforcement drones. The results show that drivers perceive traffic enforcement drones as significantly more efficient and deterring compared to current aerial traffic enforcement resources (i.e., police helicopters) and comparable in quality to speed cameras. Privacy and safety are the main concerns expressed with regards to such technology, yet these concerns have been shown to be significantly relieved if traffic enforcement drones are restricted to interurban spaces. Interestingly, only a few Israeli participants object to the introduction of traffic enforcement drones to the traffic police’s arsenal compared to about half of American participants. These results combine to suggest several practical guidelines for decision-makers which can facilitate the deployment of this potentially life-saving technology in the field.
Ahmed M. Shahat Osman
The emergence of smart cities may mitigate the challenges associated with continued urbanization and increasing population density in cities. Smart city projects target sustainable economic growth and better quality of life for both inhabitants and visitors. Information and Communications Technologies (ICT) are crucial to city smartening: they yield massive volumes of data known as big data. Extracting insights and hidden correlations from big data is a growing trend in information systems to provide better services to citizens and support the decision making processes. However, to extract valuable insights for developing city level smart information services, the generated datasets from various city domains need to be integrated and analyzed, processes known as big data analytics or big data value chain. Existing literature reveals an increasing interest in harnessing big data analytics applications in general and in the area of smart cities in particular. Yet, comprehensive discussions on the essential characteristics of big data analytics frameworks fitting smart cities requirements are still needed. This paper presents a novel big data analytics framework for smart cities called “Smart City Data Analytics Panel — SCDAP”. The design of SCDAP is based on answering the following research questions: what are the characteristics of big data analytics frameworks applied in smart cities in literature and what are the essential design principles that should guide the design of big data analytics frameworks have to serve smart cities purposes?
While securing personal data from privacy violations, the new General Data Protection Regulation (GDPR) explicitly challenges policymakers to exploit evidence from social data-mining in order to build better policies. Against this backdrop, two issues become relevant: the impact of Big Data on social research, and the potential intersection between social data mining, rule-making and policy modeling. The work aims to contribute to the reflection on some of the implications of the ‘knowledge-based’ policy recommended by the GDPR. The paper is thus split into two parts: the first describes the data-driven evolution of social sciences, raising methodological and epistemological issues; the second focuses on the interplay between data-driven social research, rule-making and policy modeling, in the light of the policy model fostered by GDPR. Some theoretical reflections about the role of evidence in rule-making will be considered to introduce a discussion on the intersection between data-driven social research and policy modeling and to sketch hypotheses on its future evolutions.
Razvan Nicolescu, Michael Huth, Petar Radanliev, and David De Roure
The authors investigate the emerging meanings of “value” associated with the Internet of Things. Given the current political economy, they argue that the multiple meanings of “value” cannot be reduced to a single domain or discipline, but rather they are invariably articulated at the juxtaposition of three domains: social, economic, and technical. The authors analyze each of these domains and present domain challenges and cross-domain implications – drawing from an interdisciplinary literature review and gap analysis across sources from academia, business, and governments. They then propose a functional model that aggregates these findings into a value-driven logic of the emerging global political economy enabled by digital technology in general and IoT in particular. These conceptual contributions highlight the critical need for an interdisciplinary understanding of the meaning of “value”, so that IoT services and products will create and sustain such concurrent meanings during their entire lifecycle, from design to consumption and retirement or recycling.
The commercialization of air taxis and autonomous passenger drones will one day congest urban airspace. Operators expect that, once flights are autonomous and the cost of service falls, high traffic urban “vertiports” could see hundreds of air taxi takeoffs and landings per hour. Low altitude airspace—between 200 feet and 5000 feet above ground level—offers a relatively blank slate to explore new regulatory models for air traffic management and avoid command-and-control mistakes made in the past in aviation. Regulators’ current proposals would centralize air taxi traffic management into a single system to coordinate air taxi traffic, but this approach likely creates technology lock-in and unduly benefits the initial operators at the expense of later innovators. To facilitate the development of this transportation market, regulators should consider demarcating aerial travel corridors and auctioning exclusive use licenses to operators for use of those corridors, much as regulators auction radio spectrum licenses and offshore wind energy sites. Exclusive rights to routes would allow transfer and sale to more efficient operators and would also give operators the certainty they need to finance the substantial capital investments.