Search

Purpose: The purpose of this paper is to identify workforce skills that protect an occupation from elimination due to automation technology. Design/methodology/approach: The authors apply a Gaussian process (GP) classifier, based on the level of non-automatable work activities in an occupation, to USA and Colombian occupational datasets. Findings: The authors find that communication, interpersonal relationship management and decision-making skills are most important in occupations that are resistant to automation. Research limitations/implications: The results are based on work activities data from the Occupational Information Network (O*NET) database developed for the USA labor market. This dataset does not capture significant differences in work activities, where they exist, for the same occupation between the two countries. The findings are also limited to Colombia. Readers should be careful to extrapolate the findings outside of this geography. Originality/value: The authors discover that automation is likely to be a global phenomenon that can only be slightly mitigated by cultural and political factors.

Wage gaps between "skilled" and "unskilled" earners in the United States are conventionally attributed to U.S. workers' "skill deficits," or lack of skills necessary to deal with technological change, particularly automation. This paper argues instead that skills deficit/automation claims have always been a weak explanation for post-1979 trends. Since the mid-1990s all indications are that there is no basis for considering automation to be a significant factor in wage suppression or the growth of wage inequality. Rather, inequality growth has been an outgrowth of developments in the labor market rather than product markets. The key dynamic undercutting the typical worker's wage growth has been the strengthening of employers' power relative to their white-collar and blue-collar workers. The cause has not been monopoly firms exercising their power in product markets by charging higher prices to consumers. Monopolization has indeed contributed to wage suppression, but even this factor has largely run through the labor market, as monopoly firms squeezed supplier chain firms which in turn undercut their own workers' wages while seeing a profit squeeze as well. The paper concludes that what is needed is a better balancing of power in the labor market rather than a perfecting of competition. [ABSTRACT FROM AUTHOR]

With emerging Automated Driving Systems (ADS) representing Automated Vehicles (AVs) of Level 3 or higher as classified by the Society of Automotive Engineers, several AV manufacturers are testing their vehicles on public roadways in the U.S. The safety performance of AVs has become a major concern for the transportation industry. Several ADS-equipped vehicle crashes have been reported to the National Highway Traffic Safety Administration (NHTSA) in recent years. Scrutinizing these crashes can reveal rare or complex scenarios beyond the normal capabilities of AV technologies called "edge cases." Investigating edge-case crashes helps AV companies prepare vehicles to handle these unusual scenarios and, as such, improves traffic safety. Through analyzing the NHTSA data from July 2021 to February 2023, this study utilizes an unsupervised machine learning technique, hierarchical clustering, to identify edge cases in ADS-equipped vehicle crashes. Fifteen out of 189 observations are identified as edge cases, representing 8 % of the population. Injuries occurred in 10 % of all crashes (19 out of 189), but the proportion rose to 27 % for edge cases (4 out of 15 edge cases). Based on the results, edge cases could be initiated by AVs, humans, infrastructure/environment, or their combination. Humans can be identified as one of the contributors to the onset of edge-case crashes in 60 % of the edge cases (9 out of 15 edge cases). The main scenarios for edge cases include unlawful behaviors of crash partners, absence of a safety driver within the AV, precrash disengagement, and complex events challenging for ADS, e.g., unexpected obstacles, unclear road markings, and sudden and unexpected changes in traffic flow, such as abrupt road congestion or sudden stopped traffic from a crash. Identifying and investigating edge cases is crucial for improving transportation safety and building public trust in AVs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The article presents commentary from Ananth Madhavan about a paper written by Kumar Venkataraman entitled "Automated Versus Floor Trading: An Analysis of Execution Costs on the Paris and New York Exchanges," which appeared in the August, 2001 issue of the "Journal of Finance." In that paper Venkataraman concluded that automated stock exchanges could not yet match the benefits afforded by floor traders on traditional exchanges. The author of the current paper raises questions about some of Venkataraman's interpretations.

Background: Teachers often rely on the use of open‐ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through more close‐ended problem types. While these types of problems are valuable to teachers, the variation in student responses to these questions makes it difficult, and time‐consuming, to evaluate and provide directed feedback. It is a well‐studied concept that feedback, both in terms of a numeric score but more importantly in the form of teacher‐authored comments, can help guide students as to how to improve, leading to increased learning. It is for this reason that teachers need better support not only for assessing students' work but also in providing meaningful and directed feedback to students. Objectives: In this paper, we seek to develop, evaluate, and examine machine learning models that support automated open response assessment and feedback. Methods: We build upon the prior research in the automatic assessment of student responses to open‐ended problems and introduce a novel approach that leverages student log data combined with machine learning and natural language processing methods. Utilizing sentence‐level semantic representations of student responses to open‐ended questions, we propose a collaborative filtering‐based approach to both predict student scores as well as recommend appropriate feedback messages for teachers to send to their students. Results and Conclusion: We find that our method outperforms previously published benchmarks across three different metrics for the task of predicting student performance. Through an error analysis, we identify several areas where future works may be able to improve upon our approach. Lay Description: What is already known about this topic: Open‐ended questions are used by teachers in the domain of mathematics to assess their students understanding but automated support for these types of questions are limited in online learning platforms. Recent advancements in areas of machine learning and natural language processing have led to promising results in a range of domains and applications. What this paper adds: Emulating how teachers identify similar student answers can be used to build tools that support teachers in assessing and providing feedback to student open‐ended work. Implications for practice: Developing better automated supports can increase the amount of direct feedback students receive to guide their learning. [ABSTRACT FROM AUTHOR]

Presents abstracts presented at the 1999 Pittsburgh Conference on automated methods and management in chemistry in Pennsylvania. 'Microfabrication as a Route to Nanovolume Separation Systems,' by Fred Regnier, Brian Burke and Bing He; 'Fast FTIR Imaging of Multicomponent Polymer Systems,' by J.L. Koenig and C.M. Snively; 'The Emergence of PC-based Measurement and Automation at Pittcon,' by Dudley Baker.

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever‑growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi‑society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools. [ABSTRACT FROM AUTHOR]

Reviews computer applications in judicial, legal, and legislative information activities being used to support litigation and court administration, assist in searching for legislation and laws, aid criminal justice information systems, and provide appropriate bibliographic and reference assistance. Management issues in automating systems are noted. (EJS)

The article comments on a paper published within the issue. "Technology, Communication and the Performance of Financial Markets: 1840-1975," by Kenneth D. Garbade and William L. Silber, investigates the effects of innovations in information technology on security markets. The author discusses two points of criticism regarding the paper in question. He feels that the authors exaggerate the policy significance of their findings. He also believes they overstate their case regarding the importance of the consolidated ticker tape, noting that no impact on inter-market price differentials could be observed. The author feels that the automation of the trading processes is the next logical step for market integration, which is currently under active consideration by the U.S. Securities and Exchange Commission.

In the United States of America, the Census Bureau (USCB) is implementing four major areas of innovation in preparation for the 2020 Census. The first area focuses on the maintenance of our frame of addresses using satellite imagery. The USCB will compare old and new satellite images to identify geographic areas that are stable and will not require in-person field staff updating. The second uses the Internet, including Identified (ID) and Non-Identified (Non-ID) processing, and cloud services to make it easier for people to self-respond. This Non-ID methodology has significant impacts on the way USCB staff execute our advertising campaign and promises to increase our self-response rates. The third uses existing administrative data to reduce cost. USCB will use existing data in many components of the 2020 Census including identification of vacant, non-existent, and occupied living quarters for non-respondents. The last area of innovation leverages technology to make field staff more efficient. Much of the field tasks will be automated including recruiting people, hiring staff, training staff, payroll and expense reporting, case assignments, case management, route optimization, quality control, and communications. The 2020 Census promises to be innovative, and improve over past censuses that relied heavily on paper questionnaires. [ABSTRACT FROM AUTHOR]

A global trend towards automated trading systems raises the important question of whether execution costs are, in fact, lower than on trading floors. This paper compares the trade execution costs of similar stocks in an automated trading structure (Paris Bourse) and a floor-based trading structure (NYSE). Results indicate that execution costs are higher in Paris than in New York after controlling for differences in adverse selection, relative tick size, and economic attributes across samples. These results suggest that the present form of the automated trading system may not be able to fully replicate the benefits of human intermediation on a trading floor. [ABSTRACT FROM AUTHOR]

Reports on the recipients of the 2002 K.S. Fu transactions on Robotics and Automation Best Paper Award in the U.S. Awards received by Ezio Malis, INRIA-Sophia Antipolis, and Francois Chaumette, IRISA/INRIA-Rennes; Title of the winning paper; Presentation of the award by the T-RA editor-in-chief.

A series of articles looks at computerization and unions in Australia, France, and India; bargaining agreements about technological innovation in India, the United Kingdom, and the United States; and the effects of technology on the labor force in the Federal Republic of Germany, Japan, and the United States. (SK)

Seven articles by members of the Bureau of the Census discuss various aspects of the census process and uses of census figures. Areas which are discussed include the historical basis of the census; automation of the census process; access to census information and confidentiality; and census taking in developing nations. (CLB)

This article cites a variety of sources and synthesizes a number of studies on the social implications of technological innovations (microelectronics). These studies were related to six European and Asian countries and were also concerned with the international division of labor. (SSH)

This paper explores how professional engineers recognize and make sense of product defects in their everyday work. Such activities form a crucial, if often overlooked, part of professional engineering practice. By detecting, recognizing and repairing defects, engineers contribute to the creation of value and the optimization of production processes. Focusing on early-career engineers in an advanced steel mill in the United States, we demonstrate how learning specific ways of seeing and attending to defects take shape around the increasing automation of certain aspects of engineering work. Practices of sensing defects are embodied, necessitating disciplined eyes, ears, and hands, but they are also distributed across human and non-human actors. We argue that such an approach to technical work provides texture to the stark opposition between human and machine work that has emerged in debates around automation. Our approach to sensing defects suggests that such an opposition, with its focus on job loss or retention, misses the more nuanced ways in which humans and machines are conjoined in perceptual tasks. The effects of automation should be understood through such shifting configurations and the ways that they variously incorporate the perceptual practices of humans and machines. [ABSTRACT FROM AUTHOR]

Occupational Applications This paper provides a historical overview of the rise of Work-Related Musculoskeletal Disorders (WMSDs) in the U.S. from the 1980s to the present, with a special focus on the two industries with the highest recorded rates: Meatpacking and Auto Assembly. The activities underlying this account amount to a major occupational health success story (although still incomplete) in the recognition of these disorders and the development of a nation-wide effort for prevention. An obstacle in creating the data presented here was that the system of recordkeeping changed in multiple ways, making it difficult to compare WMSD rates over time. The work summarized here evaluated the effect of these changes and combined temporal segments that were judged to be the most accurate to create an overall trend line. These results can aid in: 1) showing the overall history of the recognition and prevention of WMSDs, 2) understanding the effects of the recordkeeping changes, and 3) allowing international comparisons of the trends.

Aims: The primary aim of this paper was to outline the processes involved in building the Partners Arthroplasty Registry (PAR), established in April 2016 to capture baseline and outcome data for patients undergoing arthroplasty in a regional healthcare system. A secondary aim was to determine the quality of PAR's data. A tertiary aim was to report preliminary findings from the registry and contributions to quality improvement initiatives and research up to March 2019., Methods: Structured Query Language was used to obtain data relating to patients who underwent total hip or knee arthroplasty (THA and TKA) from the hospital network's electronic medical record (EMR) system to be included in the PAR. Data were stored in a secure database and visualized in dashboards. Quality assurance of PAR data was performed by review of the medical records. Capture rate was determined by comparing two months of PAR data with operating room schedules. Linear and binary logistic regression models were constructed to determine if length of stay (LOS), discharge to a care home, and readmission rates improved between 2016 and 2019., Results: The PAR captured 16,163 THAs and TKAs between April 2016 and March 2019, performed in seven hospitals by 110 surgeons. Manual comparison to operating schedules showed a 100% capture rate. Review of the records was performed for 2,603 random operations; 2,298 (88.3%) had complete and accurate data. The PAR provided the data for three abstracts presented at international conferences and has led to preoperative mental health treatment as a quality improvement initiative in the participating institutions. For primary THA and TKA surgeries, the LOS decreased significantly (p < 0.001) and the rate of home discharge increased significantly (p < 0.001) between 2016 and 2019. Readmission rates did not correlated with the date of surgery (p = 0.953)., Conclusion: The PAR has high rates of coverage (the number of patients treated within the Partners healthcare network) and data completion and can be used for both research purposes and quality improvement. The same method of creating a registry that was used in the PAR can be applied to hospitals using similar EMR systems. Cite this article: Bone Joint J 2020;102-B(7 Supple B):90-98.

Today's power utilities, around the world, own multiple substations that are connected together to form a complex energy network. The functions within and between these substations are being automated according to globally accepted power utility automation standard IEC 61850. This automation results in efficient operation and enhanced protection of power network with the aid of the communication system. Implementing the protection schemes modeled using communication configurations of standardized information exchange will lead to digital power grid. Designing an IEC-61850-based protection scheme to take care of the faults outside the substations is a challenge, as the typical local-area-network-based generic-object-oriented substation events and sampled-value messages need to be transmitted over a wide-area network. This paper presents communication configuration for line current differential protection schemes applied between two automated substations. It presents the simulation results of communication configuration network between two substations. Its performance is evaluated using a network simulator tool. This study intends to guide the development of a robust protection scheme with IEC-61850-based communication configuration. [ABSTRACT FROM PUBLISHER]