Complacency and Bias in Human Use of Automation: An Attentional Integration

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Objective: Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Background: Automation-related complacency and automation bias have typically been considered separately and independently. Methods: Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Results: Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator’s attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect.Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams.While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Conclusion: Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. Application: The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems

Neuroenhancement: Enhancing brain and mind in health and in disease

AbstractHumans have long used cognitive enhancement methods to expand the proficiency and range of the various mental activities that they engage in, including writing to store and retrieve information, and computers that allow them to perform myriad activities that are now commonplace in the internet age. Neuroenhancement describes the use of neuroscience-based techniques for enhancing cognitive function by acting directly on the human brain and nervous system, altering its properties to increase performance. Cognitive neuroscience has now reached the point where it may begin to put theory derived from years of experimentation into practice. This special issue includes 16 articles that employ or examine a variety of neuroenhancement methods currently being developed to increase cognition in healthy people and in patients with neurological or psychiatric illness. This includes transcranial electromagnetic stimulation methods, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), along with deep brain stimulation, neurofeedback, behavioral training techniques, and these and other techniques in conjunction with neuroimaging. These methods can be used to improve attention, perception, memory and other forms of cognition in healthy individuals, leading to better performance in many aspects of everyday life. They may also reduce the cost, duration and overall impact of brain and mental illness in patients with neurological and psychiatric illness. Potential disadvantages of these techniques are also discussed. Given that the benefits of neuroenhancement outweigh the potential costs, these methods could potentially reduce suffering and improve quality of life for everyone, while further increasing our knowledge about the mechanisms of human cognition

Neuronal and Cognitive Plasticity: A Neurocognitive Framework for Ameliorating Cognitive Aging

What is the neurocognitive basis for the considerable individual differences observed in functioning of the adult mind and brain late in life? We review the evidence that in healthy old age the brain remains capable of both neuronal and cognitive plasticity, including in response to environmental and experiential factors. Neuronal plasticity (e.g., neurogenesis, synaptogenesis, cortical re-organization) refers to neuron-level changes that can be stimulated by experience. Cognitive plasticity (e.g., increased dependence on executive function) refers to adaptive changes in patterns of cognition related to brain activity. We hypothesize that successful cognitive aging requires interactions between these two forms of plasticity. Mechanisms of neural plasticity underpin cognitive plasticity and in turn, neural plasticity is stimulated by cognitive plasticity. We examine support for this hypothesis by considering evidence that neural plasticity is stimulated by learning and novelty and enhanced by both dietary manipulations (low-fat, dietary restriction) and aerobic exercise. We also examine evidence that cognitive plasticity is affected by education and training. This is a testable hypothesis which could be assessed in humans in randomized trials comparing separate and combined effects of cognitive training, exercise, and diet on measures of cognitive and brain integrity. Greater understanding of the factors influencing the course of cognitive aging and of the mechanisms underlying those factors could provide information on which people could base choices that improve their ability to age successfully

The Visual Priming of Motion-Defined 3D Objects

The perception of a stimulus can be influenced by previous perceptual experience, a phenomenon known as perceptual priming. However, there has been limited investigation on perceptual priming of shape perception of three-dimensional object structures defined by moving dots. Here we examined the perceptual priming of a 3D object shape defined purely by motion-in-depth cues (i.e., Shape-From-Motion, SFM) using a classic prime-target paradigm. The results from the first two experiments revealed a significant increase in accuracy when a cloudy SFM stimulus (whose object structure was difficult to recognize due to the presence of strong noise) was preceded by an unambiguous SFM that clearly defined the same transparent 3D shape. In contrast, results from Experiment 3 revealed no change in accuracy when a cloudy SFM stimulus was preceded by a static shape or a semantic word that defined the same object shape. Instead, there was a significant decrease in accuracy when preceded by a static shape or a semantic word that defined a different object shape. These results suggested that the perception of a noisy SFM stimulus can be facilitated by a preceding unambiguous SFM stimulus--but not a static image or a semantic stimulus--that defined the same shape. The potential neural and computational mechanisms underlying the difference in priming are discussed

Spray pyrolisis deposition and characterization of Cd-TiO2 thin film for photocatalytic and photovoltaic applications

In the present paper, an innovative approach to enhance the photocatalytic efficiency and energy of photovoltaics by modifying the surface morphology of a TiO2 is demonstrated.The photovoltaic device provides sustainable power efficiency in TiO2 (TO) and Cd-TiO2 (CTO) thin films grown through spray pyrolysis. The structural and optical properties of the prepared undoped and Cd doped TiO2 thin films were studied. The morphology and content of the pro­duced samples were studied using scanning electron microscopy (SEM with EDAX). A UV-Vis spectrophotometer was used to record the optical absorption spectra of TiO2 nanoparticles. XRD analysis showed that TO and CTO had anatase structure, and the average crystalline size was calculated as 132.0 nm.The photocatalytic efficiency of TO and CTO for degradation of Rodhamine B (RhB) dye was examined. Also, power-voltage (P-V) and photocurrent-voltage (I-V) output current intensity relations were discussed

Current Concepts and Trends in Human-Automation Interaction

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The purpose of this panel was to provide a general overview and discussion of some of the most current and controversial concepts and trends in human-automation interaction. The panel was composed of eight researchers and practitioners. The panelists are well-known experts in the area and offered differing views on a variety of different human-automation topics. The range of concepts and trends discussed in this panel include: general taxonomies regarding stages and levels of automation and function allocation, individualized adaptive automation, automation-induced complacency, economic rationality and the use of automation, the potential utility of false alarms, the influence of different types of false alarms on trust and reliance, and a system-wide theory of trust in multiple automated aids

Neurogenetic Effects on Cognition in Aging Brains: A Window of Opportunity for Intervention?

Knowledge of genetic influences on cognitive aging can constrain and guide interventions aimed at limiting age-related cognitive decline in older adults. Progress in understanding the neural basis of cognitive aging also requires a better understanding of the neurogenetics of cognition. This selective review article describes studies aimed at deriving specific neurogenetic information from three parallel and interrelated phenotype-based approaches: psychometric constructs, cognitive neuroscience-based processing measures, and brain imaging morphometric data. Developments in newer genetic analysis tools, including genome wide association, are also described. In particular, we focus on models for establishing genotype–phenotype associations within an explanatory framework linking molecular, brain, and cognitive levels of analysis. Such multiple-phenotype approaches indicate that individual variation in genes central to maintaining synaptic integrity, neurotransmitter function, and synaptic plasticity are important in affecting age-related changes in brain structure and cognition. Investigating phenotypes at multiple levels is recommended as a means to advance understanding of the neural impact of genetic variants relevant to cognitive aging. Further knowledge regarding the mechanisms of interaction between genetic and preventative procedures will in turn help in understanding the ameliorative effect of various experiential and lifestyle factors on age-related cognitive decline

Oxytocin Receptor Genetic Variation Promotes Human Trust Behavior

Given that human trust behavior is heritable and intranasal administration of oxytocin enhances trust, the oxytocin receptor (OXTR) gene is an excellent candidate to investigate genetic contributions to individual variations in trust behavior. Although a single-nucleotide polymorphism involving an adenine (A)/guanine (G) transition (rs53576) has been associated with socio-emotional phenotypes, its link to trust behavior is unclear. We combined genotyping of healthy male students (n = 108) with the administration of a trust game experiment. Our results show that a common occurring genetic variation (rs53576) in the OXTR gene is reliably associated with trust behavior rather than a general increase in trustworthy or risk behaviors. Individuals homozygous for the G allele (GG) showed higher trust behavior than individuals with A allele carriers (AA/AG). Although the molecular functionality of this polymorphism is still unknown, future research should clarify how the OXTR gene interacts with other genes and the environment in promoting socio-emotional behaviors

Transcranial direct current stimulation facilitates cognitive multi-task performance differentially depending on anode location and subtask

There is a need to facilitate acquisition of real world cognitive multi-tasks that require long periods of training (e.g., air traffic control, intelligence analysis, medicine). Non-invasive brain stimulation—specifically transcranial Direct Current Stimulation (tDCS)—has promise as a method to speed multi-task training. We hypothesized that during acquisition of the complex multi-task Space Fortress, subtasks that require focused attention on ship control would benefit from tDCS aimed at the dorsal attention network while subtasks that require redirection of attention would benefit from tDCS aimed at the right hemisphere ventral attention network. We compared effects of 30 min prefrontal and parietal stimulation to right and left hemispheres on subtask performance during the first 45 min of training. The strongest effects both overall and for ship flying (control and velocity subtasks) were seen with a right parietal (C4, reference to left shoulder) montage, shown by modeling to induce an electric field that includes nodes in both dorsal and ventral attention networks. This is consistent with the re-orienting hypothesis that the ventral attention network is activated along with the dorsal attention network if a new, task-relevant event occurs while visuospatial attention is focused (Corbetta et al., 2008). No effects were seen with anodes over sites that stimulated only dorsal (C3) or only ventral (F10) attention networks. The speed subtask (update memory for symbols) benefited from an F9 anode over left prefrontal cortex. These results argue for development of tDCS as a training aid in real world settings where multi-tasking is critical

Dopamine Beta Hydroxylase Genotype Identifies Individuals Less Susceptible to Bias in Computer-Assisted Decision Making

Computerized aiding systems can assist human decision makers in complex tasks but can impair performance when they provide incorrect advice that humans erroneously follow, a phenomenon known as “automation bias.” The extent to which people exhibit automation bias varies significantly and may reflect inter-individual variation in the capacity of working memory and the efficiency of executive function, both of which are highly heritable and under dopaminergic and noradrenergic control in prefrontal cortex. The dopamine beta hydroxylase (DBH) gene is thought to regulate the differential availability of dopamine and norepinephrine in prefrontal cortex. We therefore examined decision-making performance under imperfect computer aiding in 100 participants performing a simulated command and control task. Based on two single nucleotide polymorphism (SNPs) of the DBH gene, −1041 C/T (rs1611115) and 444 G/A (rs1108580), participants were divided into groups of low and high DBH enzyme activity, where low enzyme activity is associated with greater dopamine relative to norepinephrine levels in cortex. Compared to those in the high DBH enzyme activity group, individuals in the low DBH enzyme activity group were more accurate and speedier in their decisions when incorrect advice was given and verified automation recommendations more frequently. These results indicate that a gene that regulates relative prefrontal cortex dopamine availability, DBH, can identify those individuals who are less susceptible to bias in using computerized decision-aiding systems