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A SmartSpace is an integrated, intelligent, environment that facilitates new dimensions of human interaction with computing and physical environments by leveraging emerging trends in pervasive computing. The SmartSpace for automation (SSA) proposed here facilitates interactions between humans and an automation system. Current human‐computer interaction (HCI) approaches for automation are based on a state‐transition paradigm using splintered devices that are attached locally to controllers. Such approaches are unlikely to extend to future generations of automation systems because of the fundamental limitations they impose on the tasks that can be accomplished, the lack of support for holistic system‐wide decision‐making, and the lack of a systematic framework that can guide the adoption of emerging pervasive devices for HCI activities. The approach we describe for developing an SSA is based on a goal‐seeking paradigm and emphasizes the explicit representation and resolution of uncertainties.

The history, successes, failures and future needs that relate to the allocation of functions to humans and/ or machines in manufacturing environments are presented. The various methodologies that have been proposed for performing function allocation are discussed. The basic process involves matching the capabilities and limitations of the particular human or automated system with the requirements imposed by the manufacturing operation. This process can range from a global, systems approach down to the delineation of specific capabilities of humans and automated systems. Both recent advances and obstacles to the effective allocation of tasks to humans or machines based on the capabilities of each are presented. The current status and the areas where future research and development are needed are discussed.

With the increase in the adoption of artificial intelligence (AI)-based decision-making, organizations are facilitating human–AI collaboration. This collaboration can occur in a variety of configurations with the division of labor, with differences in the nature of interdependence being parallel or sequential, along with or without the presence of specialization. This study intends to explore the extent to which humans express comfort with different models human–AI collaboration.

Situational response surveys were adopted to identify configurations where humans experience the greatest trust, role clarity and preferred feedback style. Regression analysis was used to analyze the results.

Some configurations contribute to greater trust and role clarity with AI as a colleague. There is no configuration in which AI as a colleague produces lower trust than humans. At the same time, the human distrust in AI may be less about human vs AI and more about the division of labor in which human–AI work.

The study explores the extent to which humans express comfort with different models of an algorithm as partners. It focuses on work design and the division of labor between humans and AI. The finding of the study emphasizes the role of work design in human–AI collaboration. There is human–AI work design that should be avoided as they reduce trust. Organizations need to be cautious in considering the impact of design on building trust and gaining acceptance with technology.

The paper's originality lies in focusing on the design of collaboration rather than on performance of the team.

This paper aims to show the current situation and additional requirements for the aircraft automation systems based on the lessons learned from the two 737 MAX crashes.

In this study, the Swiss cheese model was used to find the real root causes of the 737 MAX accidents. Then, the results have been compared with the actions taken by the manufacturers and authorities. Based on the comparison, the necessary improvements to prevent such accidents are defined. Regarding the faulty sensor that forms the accidents, a synthetic sensor was developed using an aerodynamic model.

It has been proven that the safety-critical automation systems should not be designed by relying on a single set of sensor data. Automation levels should be defined in a standard way. Depending on the defined automation level, the system must be designed as either fail-safe or fail-operational system. When designing backup systems, it should be decided by looking at not only whether it has power but also the accuracy of the incoming signals.

Aviation certification requirements related to automation systems need to be revised and improved. With this context, it was revealed that the certification processes for automation systems should be re-evaluated and updated by aviation authorities, especially Federal Aviation Administration and European Union Aviation Safety Agency.

Task sharing between automation system and pilot based on the classification of automation levels and determining certification requirements accordingly has been brought to the agenda. A synthetic Angle of Attack sensor was developed by using an aerodynamic model for fault detection and diagnosis.

Cooperation of a pilot with an automated aircraft control and monitoring systems is a problem which should be solved designing the whole system. The method of design, which creates an assistant of a pilot, is the purpose of this study.

An analysis of human factors shows demands for working environment. An integration method for various technological systems and algorithms is searched.

It is possible to make the whole system to become a pilot assistant, which has ability to exchange information with pilot by a dialogue. Structural flexibility is obtained in multi-agent system structure.

Proposed approach is a solution of how to integrate increasing amount of aircraft systems. It is expected that new form of cooperation fits to human features. Proposed methodology solves problem of simultaneous control by two controllers and cooperative making decisions.

Dialogue between human and the system proposed in this solution will change perception of machines.

New abilities of machines and proposition of their realisation are presented. Presented solution of simultaneous control and decision-making during aircraft control is a novel approach to human–machine cooperation.

Industry 4.0 emerged as the Fourth Industrial Revolution aiming at achieving higher levels of operational efficiency, productivity and automation. In this context, manual assembly systems are still characterized by high flexibility and low productivity, if compared to fully automated systems. Therefore, the purpose of this paper is to propose the design, engineering and testing of a prototypal adaptive automation assembly system, including greater levels of automation to complement the skills and capabilities of human workers.

A lab experimental field-test is presented comparing the assembly process of a full-scale industrial chiller with traditional and adaptive assembly system.

The analysis shows relevant benefits coming from the adoption of the adaptive automation assembly system. In particular, the main findings highlight improvements in the assembly cycle time and productivity, as well as reduction of the operator’s body movements.

The prototype is applied in an Italian mid-size industrial company, confirming its impact in terms of upgrades of the assembly system flexibility and productivity. Thus, the research study proposed in this paper provides valuable knowledge to support companies and industrial practitioners in the shift from traditional to advanced assembly systems matching current industrial and market features.

This paper expands the lacking research on adaptive automation assembly systems design proposing an innovative prototype able to real-time reconfigure its structure according to the product to work, e.g. work cycle, and the operator features.

Fig. 1 presents the interface used by our pilots to fly the UAV simulation.

When we take a top-down approach to understanding issues surrounding ROV implementation, we can employ the metaphor either literally or as a form of abstraction hierarchy (Rasmussen, 1986). Literally, the military's necessity for moment-to-moment information mandates a suite of context-specific technological capabilities for sensor and effector systems. This suite includes but is not limited to systems in outer space (such as geo-synchronized orbiting platforms), high altitude atmospheric systems (such as Global Hawk) and other craft which operate less than hundreds of feet from earth down to almost ground level itself.

Technological advances and the adaption of higher levels of automation serve as a potential cause of aviation incidents and accidents. This study aims to investigate the effect of automated systems on the operator’s performance total load (work, task, information, communication and mental) in highly advanced systems.

A questionnaire was designed for aviation operators (Pilots, ATCOs) to understand the intensity to which automation has affected their working environment and personal behavior. In total, 115 responses were received from 44 countries worldwide. Approximately, 66% of respondents were pilots, 27% Air traffic controllers and 7% were both pilots and ATCOs with various experience levels.

Based on the results of this questionnaire, this study suggests the following: creating a total load management model to understand the best load balance an operator could perform at providing rapidly updated aviation training methods and approaches investigating the influence and consequences of adding new tools to the operator’s working station and redesigning it to achieve top operator-machine equilibrium redesigning information and alerting systems.

Intrinsic limitations include an implicit expression of bias in the way questions are phrased, ambiguity in question phrasing that leads to incorrect conclusions and challenges regarding articulating complex concepts.

In this paper, the authors aimed to assess and investigate factors leading to current and future incidents and accidents resulting from human factors, specifically caused or developed because of highly automated systems.