Human factors in technological change

1954 ◽  
Vol 33 (7) ◽  
pp. 421
Author(s):  
C.A. Mace
Keyword(s):  
Human Factors ◽  
Technological Change

Work in the Knowledge-Driven Economy

2001 ◽  
Vol 15 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Valerie Bayliss
Keyword(s):  
Human Factors ◽  
Technological Change ◽  
Knowledge Economy ◽  
New Economy ◽  
Working Life ◽  
New Challenges ◽  
The One ◽  
The Impact

The UK's development as a knowledge-driven economy has become a ‘given’. There are, however, differences of view about what such an economy comprises, and there is some risk that human factors will be neglected as government and business both revel in the excitement of technological change and struggle to keep pace with it. For a gifted science graduate or a born entrepreneur, the opportunities may be limitless. For the one in five people considered functionally illiterate, opportunities are closing down rapidly. But the knowledge economy will not succeed without people, and as the workforce ages employers will be faced with new challenges. It has been clear for some time that the new economy will have an enormous impact on work – indeed this has already started to happen – and that the impact will not be uniform. This paper examines some of the implications of these changes for individuals, business and government, from shifts in the pattern of work and attitudes to work, to the impact on the vast national infrastructures that support working life.

Automation and the Human Factors Race to Catch Up

2017 ◽  
Vol 12 (1) ◽  
pp. 83-85 ◽  
Author(s):  
Catherine M. Burns
Keyword(s):  
Data Collection ◽  
Human Factors ◽  
Technological Change ◽  
Data Driven ◽  
Massive Data ◽  
Laboratory Studies ◽  
Data Driven Approach ◽  
Catch Up

Automation has been rapidly developing into a pervasive part of our every day lives. Although I agree with Kaber’s original article, I argue that human factors as a discipline is not keeping up with the pace of technological change. Human factors researchers must rapidly embrace the development of richer automation models, more complex laboratory studies, and naturalistic studies in the field to generate relevant insights into human automation interaction. The corresponding development of massive data collection presents an opportunity for a more data-driven approach to understanding human automation interaction and human factors in general.

An Application of the HFACS Method to Aviation Accidents in Africa

2016 ◽  
Vol 6 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Isaac Munene
Keyword(s):  
Human Factors ◽  
Physical Environment ◽  
Human Factor ◽  
Flight Training ◽  
African Countries ◽  
Causal Factors ◽  
Aviation Accidents ◽  
Factors Analysis ◽  
Adverse Weather ◽  
Decision Errors

Abstract. The Human Factors Analysis and Classification System (HFACS) methodology was applied to accident reports from three African countries: Kenya, Nigeria, and South Africa. In all, 55 of 72 finalized reports for accidents occurring between 2000 and 2014 were analyzed. In most of the accidents, one or more human factors contributed to the accident. Skill-based errors (56.4%), the physical environment (36.4%), and violations (20%) were the most common causal factors in the accidents. Decision errors comprised 18.2%, while perceptual errors and crew resource management accounted for 10.9%. The results were consistent with previous industry observations: Over 70% of aviation accidents have human factor causes. Adverse weather was seen to be a common secondary casual factor. Changes in flight training and risk management methods may alleviate the high number of accidents in Africa.

Asiana Airlines Flight 214

2014 ◽  
Vol 4 (2) ◽  
pp. 113-121 ◽  
Author(s):  
Stephanie Chow ◽  
Stephen Yortsos ◽  
Najmedin Meshkati
Keyword(s):  
Human Factors ◽  
Aviation Safety ◽  
Cultural Factors ◽  
Vital Role ◽  
Cultural Issues ◽  
Flight Crew ◽  
Pilot Performance ◽  
Engineering Designs ◽  
Flight Deck

This article focuses on a major human factors–related issue that includes the undeniable role of cultural factors and cockpit automation and their serious impact on flight crew performance, communication, and aviation safety. The report concentrates on the flight crew performance of the Boeing 777–Asiana Airlines Flight 214 accident, by exploring issues concerning mode confusion and autothrottle systems. It also further reviews the vital role of cultural factors in aviation safety and provides a brief overview of past, related accidents. Automation progressions have been created in an attempt to design an error-free flight deck. However, to do that, the pilot must still thoroughly understand every component of the flight deck – most importantly, the automation. Otherwise, if pilots are not completely competent in terms of their automation, the slightest errors can lead to fatal accidents. As seen in the case of Asiana Flight 214, even though engineering designs and pilot training have greatly evolved over the years, there are many cultural, design, and communication factors that affect pilot performance. It is concluded that aviation systems designers, in cooperation with pilots and regulatory bodies, should lead the strategic effort of systematically addressing the serious issues of cockpit automation, human factors, and cultural issues, including their interactions, which will certainly lead to better solutions for safer flights.

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