New Tasks in Old Jobs: Drivers of Change and Implications for Job Quality

This overview report summarises the findings of 20 case studies looking at recent changes in the task content of five manufacturing occupations (car assemblers, meat processing workers, hand-packers, chemical products plant and machine operators and inspection engineers) as a result of factors such as digital transformations, globalisation and offshoring, increasing demand for high quality standards and sustainability. It also discusses some implications in terms of job quality and working life. The study reveals that the importance of physical tasks in manufacturing is generally declining due to automation; that more intensive use of digitally controlled equipment, together with increasing importance of quality standards, involve instead a growing amount of intellectual tasks for manual industrial workers; and that the amount of routine task content is still high in the four manual occupations studied. Overall, the report highlights how qualitative contextual information can complement existing quantitative data, offering a richer understanding of changes in the content and nature of jobs

Structuring information work: Ferranti and Martins Bank, 1952-1968

The adoption of large-scale computers by the British retail banks in the 1960s required a first-time dislocation of customer accounting from its confines in the branches, where it had been dealt with by paper-based and mechanized information systems, to a new collective space: the bank computer center. While historians have rightly stressed the continuities between centralized office work, punched-card tabulation and computerization, the shift from decentralized to centralized information work by means of a computer has received little attention. In this article, I examine the case of Ferranti and Martins Bank and employ elements of Anthony Giddens’s structuration theory to highlight the difficulties of transposing old information practices directly onto new computerized information work

“Automation” of manufacturing in the late nineteenth century: the hand and machine labor study

Recent advances in artificial intelligence and robotics have generated a robust debate about the future of work. An analogous debate occurred in the late nineteenth century when mechanization first transformed manufacturing. We analyze an extraordinary dataset from the late nineteenth century, the Hand and Machine Labor study carried out by the US Department of Labor in the mid-1890s. We focus on transitions at the task level from hand to machine production, and on the impact of inanimate power, especially of steam power, on labor productivity. Our analysis sheds light on the ability of modern task-based models to account for the effects of historical mechanization.Published versio

The Future of Work In Cities

The latest report in our City of the Future series examines societal shifts and advancements in technology that are impacting the rapidly changing American workforce. The report outlines solutions to help city leaders plan for the fast-approaching future, while forecasting the economic viability of two distinct sectors – retail and office administration – in which a quarter of Americans are currently employed

Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty

This work proposes a robust visual odometry method for structured environments that combines point features with line and plane segments, extracted through an RGB-D camera. Noisy depth maps are processed by a probabilistic depth fusion framework based on Mixtures of Gaussians to denoise and derive the depth uncertainty, which is then propagated throughout the visual odometry pipeline. Probabilistic 3D plane and line fitting solutions are used to model the uncertainties of the feature parameters and pose is estimated by combining the three types of primitives based on their uncertainties. Performance evaluation on RGB-D sequences collected in this work and two public RGB-D datasets: TUM and ICL-NUIM show the benefit of using the proposed depth fusion framework and combining the three feature-types, particularly in scenes with low-textured surfaces, dynamic objects and missing depth measurements.Comment: Major update: more results, depth filter released as opensource, 34 page

A semantic web service-based architecture for the interoperability of e-government services

We propose a semantically-enhanced architecture to address the issues of interoperability and service integration in e-government web information systems. An architecture for a life event portal based on Semantic Web Services (SWS) is described. The architecture includes loosely-coupled modules organized in three distinct layers: User Interaction, Middleware and Web Services. The Middleware provides the semantic infrastructure for ontologies and SWS. In particular a conceptual model for integrating domain knowledge (Life Event Ontology), application knowledge (E-government Ontology) and service description (Service Ontology) is defined. The model has been applied to a use case scenario in e-government and the results of a system prototype have been reported to demonstrate some relevant features of the proposed approach