The role of trust in automation reliance

A recent and dramatic increase in the use of automation has not yielded comparable improvements in performance. Researchers have found human operators often underutilize (disuse) and overly rely on (misuse) automated aids (Parasuraman and Riley, 1997). Three studies were performed with Cameron University students to explore the relationship among automation reliability, trust, and reliance. With the assistance of an automated decision aid, participants viewed slides of Fort Sill terrain and indicated the presence or absence of a camouflaged soldier. Results from the three studies indicate that trust is an important factor in understanding automation reliance decisions. Participants initially considered the automated decision aid trustworthy and reliable. After observing the automated aid make errors, participants distrusted even reliable aids, unless an explanation was provided regarding why the aid might err. Knowing why the aid might err increased trust in the decision aid and increased automation reliance, even when the trust was unwarranted. Our studies suggest a need for future research focused on understanding automation use, examining individual differences in automation reliance, and developing valid and reliable self-report measures of trust in automation.     

Reliance,trust and heuristics in judgmental forecasting

Judgmental forecasting gives light to the use of computers in human decision making. This paper reviews studies in judgmental forecasting focusing on what has been learned from human judgment and human–computer interaction. Available information was analyzed in the framework of three dimensions: reliance and trust on computer suggestions and heuristics employed by forecasters to produce forecasts. Results show that computer’s advice disuse is pervasive in forecasting; and the disuse increases with higher task complexity and lower perceived system performance. Explanations and past performance are good candidates to increase trust in computer’s advice, but the appropriate format to deliver this information is still controversial. Forecasters usually overforecast but report to prefer underforecast, which can lead to a cognitive dissonance and in turn to conflicting goals in the task. Heuristics research in time series forecasting indicates that forecasters heavily assess their own judgment, which in turn tend to be grounded in last outcomes and an overall evaluation of features like mean, trend and autocorrelation. It appears that heuristics not always lead to harmful biases for the forecast.     

Age differences in trust and reliance of a medication management system

The present study examined age differences in trust and reliance of an automated decision aid. In Experiment 1, older and younger participants performed a simple mathematical task concurrent with a simulated medication management task. The decision aid was designed to facilitate medication management, but with varying reliability. Trust, self-confidence and usage of the aid were measured. The results indicated that older adults had greater trust in the aid and were less confident in their performance, but they did not calibrate trust differently than younger adults. In Experiment 2, a variant of the same task was used to investigate whether older adults are subject to over-reliance on the automation. Differences in omission and commission errors were examined. The results indicated that older adults were more reliant on the decision aid and committed more automation-related errors. A signal detection analyses indicated that older adults were less sensitive to automation failures. Results are discussed with respect to the perceptual and cognitive factors that influence age differences in the use of fallible automation.     

The effect of individual and task characteristics on decision aid reliance

This research explores reliance behaviours of decision-makers using a decision aid. Objective and subjective task characteristics in the form of task complexity and task difficulty, respectively, are examined, along with the effect of the individual characteristic of expertise. A total of 130 subjects (65 novices and 65 experienced practitioners) completed a lab experiment using a decision aid (Insolve-DG) to help them make decisions for two insolvency tasks with differing levels of complexity. The research finds that the objective task characteristic (task complexity) and individual characteristic (expertise) both affect reliance behaviours; however, their effects are fully mediated by the subjective task characteristic (task difficulty). Expertise and task complexity are both associated with the degree of task difficulty experienced by an individual user: increasing task complexity increases task difficulty, and increasing expertise reduces task difficulty. Task difficulty and task complexity are established as different constructs; and importantly it is task difficulty, not task complexity, that ultimately affects reliance.     

NDM-Based Cognitive Agents for Supporting Decision-Making Teams

Naturalistic decision making (NDM) focuses on how people actually make decisions in realistic settings that typically involve ill-structured problems. Taking an experimental approach, we investigate the impacts of using an NDM-based software agent (R-CAST) on the performance of human decision-making teams in a simulated C3I (Communications, Command, Control and Intelligence) environment. We examined four types of decision-making teams with mixed human and agent members playing the roles of intelligence collection and command selection. The experiment also involved two within-group control variables: task complexity and context switching frequency. The result indicates that the use of an R-CAST agent in intelligence collection allows its team member to consider the latest situational information in decision making but might increase the team member's cognitive load. It also indicates that a human member playing the role of command selection should not rely too much on the agent serving as his or her decision aid. Together, it is suggested that the roles of both humans and cognitive agents are critical for achieving the best possible performance of C3I decision-making teams: Whereas agents are superior in computation-intensive activities such as information seeking and filtering, humans are superior in projecting and reasoning about dynamic situations and more adaptable to teammates' cognitive capacities. This study has demonstrated that cognitive agents empowered with NDM models can serve as the teammates and decision aids of human decision makers. Advanced decision support systems built upon such team-aware agents could help achieve reduced cognitive load and effective human-agent collaboration.     

Ironic efficiency in automation-aided signal detection

Abstract

Decision makers often make poor use of the information provided by an automated signal detection aid; recent studies have found that participants assisted by an automated aid fell well short of best-possible sensitivity levels. The present study tested the generalisability of this finding over varying levels of aid reliability. Participants performed a binary signal detection task either unaided or with assistance from a decision aid that was 60%, 85%, or 96%-reliable. Assistance from a highly reliable aid (85% or 96%) improved discrimination performance, while assistance from a low-reliability aid (60%) did not. Because their ideal strategy is to place less weight on less reliable cues, however, the decision makers’ tendency to disuse the aid became more appropriate as the aid’s reliability declined. Automation-aided efficiency was thus near to optimal when the aid was close to chance but became highly inefficient, ironically, as the aid’s reliability increased.

Practitioner Summary: Investigating operators’ automation-aided information integration strategies allows human factors practitioners to predict the level of performance the operator will attain. Ironically, in an aided signal detection task, performance when assisted by a highly reliable aid is far less efficient than that obtained when assisted by a far less reliable aid.

Abbreviations: OW: optimal weighting; UW: uniform weighting; CC: contingent criterion; BD: best decides; CF: coin flip; PM: probability matching; HDI: highest density interval; MCMC: markov chain monte carlo; HR: hit rate; FAR: false alarm rate     

Automation failures on tasks easily performed by operators undermine trust in automated aids

OBJECTIVE: We tested the hypothesis that automation errors on tasks easily performed by humans undermine trust in automation. BACKGROUND: Research has revealed that the reliability of imperfect automation is frequently misperceived. We examined the manner in which the easiness and type of imperfect automation errors affect trust and dependence. METHOD: Participants performed a target detection task utilizing an automated aid. In Study 1, the aid missed targets either on easy trials (easy miss group) or on difficult trials (difficult miss group). In Study 2, we manipulated both easiness and type of error (miss vs. false alarm). The aid erred on either difficult trials alone (difficult errors group) or on difficult and easy trials (easy miss group; easy false alarm group). RESULTS: In both experiments, easy errors led to participants mistrusting and disagreeing more with the aid on difficult trials, as compared with those using aids that generated only difficult errors. This resulted in a downward shift in decision criterion for the former, leading to poorer overall performance. Misses and false alarms led to similar effects. CONCLUSION: Automation errors on tasks that appear "easy" to the operator severely degrade trust and reliance. APPLICATION: Potential applications include the implementation of system design solutions that circumvent the negative effects of easy automation errors.     

Can insecurely attached dating couples get compensated on social network sites? —The effect of surveillance

Insecure attachment is detrimental to romantic relationships. However, surveillance through Social Networking Sites (SNSs) is assumed to be beneficial for romantic relationships in prior studies. Does surveillance offer a compensatory effect for insecure couples? The present study aims to explore the combined effect of romantic attachment and surveillance on relationships for college dating couples. The actor and partner interpersonal model (APIM) was introduced to deal with mutual influences between both parts of the couples. We recruited 250 dating couples for this research. Our study revealed that both anxiety and avoidance have negative effects on one's own and one's partner's perceived relationship quality. Furthermore, surveillance may offset males' lower perceived relationship quality when this perception is caused by partners' avoidance. Although surveillance may not compensate for lower perceived relationship quality caused by one's own insecure attachment, it may help mitigate the effects of an avoidant partner.     

The role of intervening variables in driver–ACC cooperation

This paper analyzes the behavior of drivers using Adaptive Cruise Control (ACC) within the theoretical framework of Human–Machine Cooperation. The study was carried out on a driving simulator. Driving task performance data and responses to a trust questionnaire were analyzed in order to examine the relationship between driver reliance on ACC and such intervening variables as trust, perceived workload and perceived risk. The participants were divided a posteriori into two groups according to their use of the ACC device during the experimental run. The results show that high-use drivers seemed to cooperate more with ACC than low-use drivers, who tended to perceive more risk and a higher workload. These findings are discussed in the light of Riley's theory of operator reliance on automation.     

The effect of distractor modality and processing code on human-automation interaction

We examined the effect of distractor characteristics (modality and processing code) on visual search performance and interaction with an automated decision aid. Multiple Resource Theory suggests that concurrent tasks that are processed similarly (e.g. two visual tasks) will cause greater interference than tasks that are not (e.g., a visual and auditory task). The impact of tasks that share processing and perceptual demands and their interaction with human-automation interaction is not established. In order to examine this, participants completed two blocks of a luggage screening simulation with or without the assistance of an automated aid. For one block, participants performed a concurrent distractor task drawn from one of four combinations of modality and processing code: auditory-verbal; auditory-spatial; visual-verbal; visual-spatial. We measured sensitivity, criterion setting, perceived workload, system trust, perceived system reliability, compliance, reliance, and confidence. Participants demonstrated highest sensitivity when performing with an auditory-spatial secondary task. Automation compliance was higher when the auditory-spatial distraction was present versus absent; however, system trust was highest in the auditory-verbal condition. Confidence (when disagreeing with the aid) was also highest when the distractor was auditory. This study indicates that some forms of auditory ‘distractors’ may actually help performance; these results further contribute to understanding how distractions influence performance when operators interact with automation and have implications for improved work environment and system design.     

个性化图像美学评价的研究进展与趋势

图像美学评价方法是当前研究的热点问题。图像美学评价分为大众化和个性化两种。大众化图像美学评价主要研究大多数人对图像共同的审美感知评估,而个性化图像美学评价可以针对用户的个性化审美感知进行评估。现有的研究工作主要集中在大众化图像美学评价上,但是由于人们对图像的审美体验具有高度主观性,研究针对特定用户的个性化图像美学评价方法更加符合现实意义。目前研究人员针对个性化图像美学评价展开了相关研究,并取得了一定的研究进展。但是现有的文献中缺少对个性化图像美学评价方法的综述,本文针对个性化图像美学评价的研究进展与趋势进行概述。首先分析图像美学评价的研究现状与发展趋势;然后针对现阶段的个性化图像美学评价模型进行概述,将现有的个性化图像美学评价模型总结为基于协同过滤的模型、基于用户交互的模型和基于审美差异的模型,并分析这3类模型主要的设计思路以及优缺点;最后介绍个性化图像美学评价在精准营销、个性化推荐系统、个性化视觉增强和个性化艺术设计上的应用前景,并指出未来研究工作在主观特性分析和知识驱动建模等方面的发展方向。     

Designing on‐demand education for simultaneous development of domain‐specific and self‐directed learning skills

On‐demand education enables individual learners to choose their learning pathways according to their own learning needs. They must use self‐directed learning (SDL) skills involving self‐assessment and task selection to determine appropriate pathways for learning. Learners who lack these skills must develop them because SDL skills are prerequisite to developing domain‐specific skills. This article describes the design of an on‐demand learning environment developed to enable novices to simultaneously develop their SDL and domain‐specific skills. Learners received advice on their self‐assessments and their selections of subsequent learning tasks. In the domain of system dynamics – a way to model a dynamic system and draw graphs depicting the system's behaviour over time – advice on self‐assessment is provided in a scoring rubric containing relevant performance standards. Advice on task selection indicates all relevant task aspects to be taken into account, including recommendations for suitable learning tasks which meet the individual learner's needs. This article discusses the design of the environment and the learners' perceptions of its usefulness. Most of the times, the learners found the advice appropriate and they followed it in 78% of their task selections.     

Creating a design science of human-computer interaction

An increasingly important task of computer science is to support the analysis and design of computers as things to learn from, as tools to use in one's work, as media for interacting with other people. Human-computer interaction (HCI) is the speciality area that addresses this task. Through the past two decades, HCI has pursued a broad and ambitious scientific agenda, progressively integrating its research concerns with the contexts of system development and use. This has created an unprecedented opportunity to manage the emergence of new technology so as to support socially responsive objectives.     

Facility location in anticipation of future competition

In this paper, we consider locating a new facility in a competitive environment. A future competitor is expected to enter the market and locate his facility at its best site. The best location for one's own facility is to be found such that the market share captured following the competitor's entry is maximized. The problem is complicated because the best location for the competitor depends on the selected location for one's own facility. The problem is formulated using the gravity model for the estimation of market share. Three heuristic solution procedures are proposed. Computational experiments with these heuristics are presented.     

Planning to see: A hierarchical approach to planning visual actions on a robot using POMDPs

Flexible, general-purpose robots need to autonomously tailor their sensing and information processing to the task at hand. We pose this challenge as the task of planning under uncertainty. In our domain, the goal is to plan a sequence of visual operators to apply on regions of interest (ROIs) in images of a scene, so that a human and a robot can jointly manipulate and converse about objects on a tabletop. We pose visual processing management as an instance of probabilistic sequential decision making, and specifically as a Partially Observable Markov Decision Process (POMDP). The POMDP formulation uses models that quantitatively capture the unreliability of the operators and enable a robot to reason precisely about the trade-offs between plan reliability and plan execution time. Since planning in practical-sized POMDPs is intractable, we partially ameliorate this intractability for visual processing by defining a novel hierarchical POMDP based on the cognitive requirements of the corresponding planning task. We compare our hierarchical POMDP planning system (HiPPo) with a non-hierarchical POMDP formulation and the Continual Planning (CP) framework that handles uncertainty in a qualitative manner. We show empirically that HiPPo and CP outperform the naive application of all visual operators on all ROIs. The key result is that the POMDP methods produce more robust plans than CP or the naive visual processing. In summary, visual processing problems represent a challenging domain for planning techniques and our hierarchical POMDP-based approach for visual processing management opens up a promising new line of research.     

Nursing staff's perception of changes in patient transfer habits after a course – a phenomenological-hermeneutic study

The objective of the study was to illuminate nursing staff's perception of changes after a course in patient transfer. The learning process took the form of self-experience focusing on the manner of supporting the patient to move independently. A total of 20 participants, who had answered a previously administered questionnaire, were chosen for interviews. The themes concerned the meaning of changing transfer habits. A phenomenological-hermeneutic analysis method showed that changes focused on the patient's body, the staff member's own body or cooperation with the patient. Awareness of one's own body and confidence in one's own ability seem to indicate differences in the manner of supporting the patient to move. The changes in transfer habits varied in content and meaning from person to person, depending on the focus during the transfer. These findings can contribute to an understanding of how change takes place after an educational intervention.     

An ontology based framework for mining dependence relationships between news and financial instruments

Before news is input into financial trading algorithms/models, it needs human judgements for exploring the market implications of news content, distinguishing significance extent of news, and finding out the impact of polar type of each kind of news on certain financial instrument trading activity. But Dawes and Faust (1989) reported that people usually rely on clinical judgements, especially it is hard for them to distinguish valid decision variables from invalid ones in decision making. Thus, in order to alleviate this problem and provide more objective decision making support about news in financial market, an ontology based framework is proposed, for investigating the actuarial dependence relationships between news and financial instruments trading activities as well as identifying more valid news for trading decision making. This framework is expected to help people in financial market how to consider weight for each kind of news when inputted in trading algorithms/models of certain financial instruments.