Using Formal Verification to Evaluate Human-Automation Interaction: A Review

Bolton, Matthew L.; Bass, Ellen J.; Siminiceanu, Radu

doi:10.1109/tsmca.2012.2210406

Cited by 148 publications

(93 citation statements)

References 151 publications

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“…The contribution that failures in humanautomation interaction have made to aviation accidents [15], has led to innovation in a variety of different user methods for observing and analysing how users carry out tasks to achieve their goals, together with methods for modelling the outcomes of this research [16]. Although the task analysis carried out by designers to create such models can be time consuming, task analysis and modelling are still frequently used by human factors researchers, particularly those working in regulated domains like aviation and maritime.…”

Section: Modelling and Analysing Users And Systems With Formal Methodsmentioning

confidence: 99%

Gulfs of expectation: eliciting and verifying differences in trust expectations using personas

2016

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Personas are a common tool used in Human Computer Interaction to represent the needs and expectations of a system's stakeholders, but they are also grounded in large amounts of qualitative data. Our aim is to make use of this data to anticipate the differences between a user persona's expectations of a system, and the expectations held by its developers. This paper introduces the idea of gulfs of expectation -the gap between the expectations held by a user about a system and its developers, and the expectations held by a developer about the system and its users. By evaluating these differences in expectation against a formal representation of a system, we demonstrate how differences between the anticipated user and developer mental models of the system can be verified. We illustrate this using a case study where persona characteristics were analysed to identify divergent behaviour and potential security breaches as a result of differing trust expectations.

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Section: Modelling and Analysing Users And Systems With Formal Methodsmentioning

confidence: 99%

Gulfs of expectation: eliciting and verifying differences in trust expectations using personas

2016

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“…Substantial research also exists which applies formal verification to agents and to user interface designs. In [2], Bolton et al review the large body of research applying formal verification to systems which include "human-automation interaction," including systems containing cognitive models. To our knowledge, however, no current research is applying formal methods, agents, and cognitive modeling to obtain high assurance of the human-centric decision systems introduced in this paper.…”

Section: Agentsmentioning

confidence: 99%

High assurance human-centric decision systems

Heitmeyer¹,

Pickett

Breslow

et al. 2013

2013 2nd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE)

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Abstract-Many future decision support systems will be human-centric, i.e., require substantial human oversight and control. Because these systems often provide critical services, high assurance will be needed that they satisfy their requirements. How to develop "high assurance human-centric decision systems" is unknown: while significant research has been conducted in areas such as agents, cognitive science, and formal methods, how to apply and integrate the design principles and disparate models in each area is unclear. This paper proposes a novel process for developing human-centric decision systems where AI (artificial intelligence) methods-namely, cognitive models to predict human behavior and agents to assist the humanare used to achieve adequate system performance, and software engineering methods, namely, formal modeling and analysis, to obtain high assurance. To support this process, the paper introduces a software engineering technique-formal model synthesis from scenarios-and two AI techniques-a model for predicting human overload and user model synthesis from participant studies data. To illustrate the process and techniques, the paper describes a decision system controlling unmanned air vehicles.

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“…the number entry systems found on medical devices [Thimbleby 2015]. Readers are referred to [Bolton et al 2013] which provides a broad overview of the formal approaches to modelling interaction with automation.…”

Section: Introductionmentioning

confidence: 99%

On Lions, Impala, and Bigraphs

Benford

Calder

Rodden

et al. 2016

ACM Trans. Comput.-Hum. Interact.

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While HCI has a long tradition of formally modelling task-based interactions with graphical user interfaces, there has been less progress in modelling emerging ubiquitous computing systems due in large part to their highly contextual nature and dependence on unreliable sensing systems. We present an exploration of modelling an example ubiquitous system, the Savannah game, using the mathematical formalism of bigraphs, which are based on a universal process algebra that encapsulates both dynamic and spatial behaviour of autonomous agents that interact and move among each other, or within each other. We establish a modelling approach based on four perspectives on ubiquitous systems -Computational, Physical, Human and Technology -and explore how these interact with one another. We show how our model explains observed inconsistencies in user trials of Savannah, and then how formal analysis reveals an incompleteness in design and guides extensions of the model and/or possible system re-design to resolve this.

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Using Formal Verification to Evaluate Human-Automation Interaction: A Review

Cited by 148 publications

References 151 publications

Gulfs of expectation: eliciting and verifying differences in trust expectations using personas

Gulfs of expectation: eliciting and verifying differences in trust expectations using personas

High assurance human-centric decision systems

On Lions, Impala, and Bigraphs

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