Learning About Work Tasks to Inform Intelligent Assistant Design

This study aimed to describe the limitations in information-processing skills observed among persons with schizophrenia performing daily tasks and to explore whether subgroups of participants have similar profiles based on these functional limitations. Eighty-two participants with schizophrenia living in the community were assessed during their performance of a daily activity (meal preparation). Measures included a performance-based assessment for evaluating information-processing skills-the Perceive, Recall, Plan, and Perform System of Task Analysis-community functioning and symptom assessments, and neuropsychological tests from the Cambridge Neuropsychological Test Automated Battery. Research participants were classified as having high efficiency or low efficiency according to their score on the performance-based assessment and were compared on the functional, cognitive, and symptoms variables. Participants committed various errors, and functional limitations, namely problematic information-processing skills in the perceive, recall, and plan quadrants, were observed during the daily task performance. Participants from the high-efficiency group were more independent in their living skills and more successful in attaining residential independence compared with participants from the low-efficiency group. The only cognitive test that differentiated both groups was the visuospatial associative learning test. No differences were found in the severity of symptoms. Findings suggest that both performance in a daily task and memory-and specifically associative learning capacity-provide key information for the level of residential independence. Interventions aiming for the efficient use of information-processing skills during daily tasks among persons with schizophrenia should be carried out accordingly.

Daily Functioning and Information-Processing Skills Among Persons With Schizophrenia

The design of Brain-Machine Interface (BMI) neural decoders that have robust performance in changing environments encountered in daily life activity is a challenging problem. One solution to this problem is the design of neural decoders that are able to assist and adapt to the user by participating in their perception-action-reward cycle (PARC). Using inspiration both from artificial intelligence and neurobiology reinforcement learning theories, we have designed a novel decoding architecture that enables a symbiotic relationship between the user and an Intelligent Assistant (IA). By tapping into the motor and reward centers in the brain, the IA adapts the process of decoding neural motor commands into prosthetic actions based on the user's goals. The focus of this paper is on extraction of goal information directly from the brain and making it accessible to the IA as an evaluative feedback for adaptation. We have recorded the neural activity of the Nucleus Accumbens in behaving rats during a reaching task. The peri-event time histograms demonstrate a rich representation of the reward prediction in this subcortical structure that can be modeled on a single trial basis as a scalar evaluative feedback with high precision.

Whereas previous research has focused on the link between (mental and physical) workload and task performance, less is known about the intervening mechanisms influencing this relationship. In the present study, we test the moderating roles of daily recovery and total sleep time in the relationship between work pressure and daily task performance. Using performance and recovery theories, we hypothesized that (a) work pressure relates positively to daily task performance, and that both (b) daily recovery in the form of psychological detachment and relaxation, and (c) total sleep time independently enhance this relationship. Our hypotheses were tested in a 30-day diary study with 110 officer cadets on a cross-Atlantic voyage on a Naval sail ship. The results of multilevel modeling lend support to all three hypotheses. Taken together, our findings suggest that recovery and sleep duration between shifts play a key role in the relationship between daily work pressure and task performance. We discuss the implications of these findings for the stressor-detachment model.

Intelligent personal assistants (IPA) enable voice applications that facilitate people's daily tasks. However, due to the complexity and ambiguity of voice requests, some requests may not be handled properly by the standard natural language understanding (NLU) component. In such cases, a simple reply like “Sorry, I don't know” hurts the user's experience and limits the functionality of IPA. In this paper, we propose a two-stage shortlister-reranker recommender system to match third-party voice applications (skills) to unhandled utterances. In this approach, a skill shortlister is proposed to retrieve candidate skills from the skill catalog by calculating both lexical and semantic similarity between skills and user requests. We also illustrate how to build a new system by using observed data collected from a baseline rule-based system, and how the exposure biases can generate discrepancy between offline and human metrics. Lastly, we present two relabeling methods that can handle the incomplete ground truth, and mitigate exposure bias. We demonstrate the effectiveness of our proposed system through extensive offline experiments. Furthermore, we present online A/B testing results that show a significant boost on user experience satisfaction.

The second cause of disability in Mexico is visual impairment; 26% population is blind. Even though blind people maintain a lower quality’s life than sighted people, there is not enough social interest to develop comprehensive solutions that improve it. Although many voice-activated emerging technologies use artificial intelligence to get human-machine communication through intelligent virtual assistants, such as Alexa, Siri, Google Home, and Cortana, among others, in reality, there have not been developed specific tools just for blind people that help them to improve their independent behavior because they always depend on other people in doing their daily tasks, more even when they need to move around unknown environments for them. This document reports the development of an autonomous mobility system to be operated by blind people. By audio reconstruction, it is possible to dictate, to the blind pedestrian, in real-time, the presence of traffic lights, crosswalks, and information about their current location. This system employs real-time computer vision tools, artificial intelligence, audio playback systems, and location systems, and it improves the independent behavior of blind people because they could move through unknown environments without the assistance of any sighted person, giving them greater independence and consequently increasing their life’s quality.

Collaboration in a group has the potential to achieve more effective solutions for challenging problems, but collaboration per se is not an easy task, rather a stressful burden if the collaboration partners do not communicate well with each other. While Intelligent Virtual Assistants (IVAs), such as Amazon Alexa, are becoming part of our daily lives, there are increasing occurrences in which we collaborate with such IVAs for our daily tasks. Although IVAs can provide important support to users, the limited verbal interface in the current state of IVAs lacks the ability to provide effective non-verbal social cues, which is critical for improving collaborative performance and reducing task load.In this paper, we investigate the effects of IVA embodiment on collaborative decision making. In a within-subjects study, participants performed a desert survival task in three conditions: (1) performing the task alone, (2) working with a disembodied voice assistant, and (3) working with an embodied assistant. Our results show that both assistant conditions led to higher performance over when performing the task alone, but interestingly the reported task load with the embodied assistant was significantly lower than with the disembodied voice assistant. We discuss the findings with implications for effective and efficient collaborations with IVAs while also emphasizing the increased social presence and richness of the embodied assistant.

Purpose People with disability often require long-term care. Long-term care is changing with the availability and advances in cost and function of technologies, such as home automation. Home automation has the potential to reduce paid carer hours and can potentially offer many benefits to people with a disability. The aim of this scoping review is to identify the health, social and economic outcomes experienced by people living with a disability who use home automation. Materials and methods Two electronic databases were searched by title and abstract to identify international literature that describes home automation experiences from the perspectives of people with disability. A thematic approach was taken to synthesise the data to identify the key outcomes from home automation. Results The review identified 11 studies reporting home automation outcomes for people living with a disability. Seven outcomes were associated with home automation: independence, autonomy, participation in daily activities, social and community connectedness, safety, mental health, and paid care and informal care. Conclusion Advances in technology and changes in funding to support people living with a disability have made access to home automation more readily available. Overall, the study findings showed that there is a range of potential benefits of home automation experienced by individuals living with a disability.

Abstract: The mental health app is designed to provide users with a holistic approach to managing their mental health. The app is built using React, and features a chatbot, a meditation timer, and a task manager. The chatbot provides users with a safe space to express their feelings and emotions, and to receive advice and support from the app's virtual assistant. The meditation timer helps users to focus on their breathing and relax, while the task manager helps users to organize and prioritize their daily tasks. With these features, the mental health app provides users with the tools they need to manage their mental health in a more efficient and effective way.

This article considers some problems and features of the application of modern systems of driver assistance on single-track vehicles (“STV”). It is also mentioned the classification of intelligent driver assistance systems and design features of the “STV” that require an improvement for their successful application on such vehicle. There is also described perspective of systems’ development that helps the “STV” driver. Also perspective the “STV” types with high safety construction are considered in this article.

Increasingly complex design tasks and globally distributed designers require a design environment to be intelligent and collaboration-supported. However, as today's CAD tools are becoming more powerful in helping designers draw geometric graphs, they have little intelligence and weak capability in supporting design collaboration. In such a context, distributed agent technology poses to be a promising way to well address these problems. In this paper, we present a distributed agent environment based on the CORBA paradigm. We construct an agent community to help designers work collaboratively across computer networks. To make it autonomous, reactive and proactive, we construct an agent with a component-based framework. The case study section of this paper demonstrates that the software system implemented according to the proposed architecture can provide designers with both intelligent assistance and collaboration support.

Work today consists of complex arrangements of loosely interrelated digital tools that shape work and form digital infrastructures. These digital infrastructures can either support or hinder the workers in their daily tasks. Working in an environment where some digital tools are designed for work purposes, and others without the proposed end-users in mind creates a need for improvisation. The consequence for workers may include finding various types of workarounds when shifting between digital tools. These workarounds become important for how work is performed. Through a multiple case study, this paper explores how workarounds are manifested in different work settings through four cases in the public sector. We conceptualize workarounds as practices of flexibility, efficiency, and responsibility, and show how workarounds result in new and innovative ways of working, which can be understood as a form of infrastructuring.KeywordsWorkaroundsDigital toolsDigital workDigital infrastructuresInfrastructuringInnovationPublic sector

BACKGROUND:This mixed-method study aimed to develop and validate an activity reminder clock for dementia through user testing and feedback. The increasing prevalence of dementia worldwide presents significant challenges for both patients and caregivers. Dementia impairs cognitive functions, complicating daily routines and management of everyday tasks. As the disease progresses, patients often struggle with time management and maintaining a structured routine, which can lead to increased confusion and reduced quality of life. Assistive technologies, such as activity reminder clocks, have emerged as potential solutions to help address these challenges. These devices are designed to aid individuals with dementia by providing reminders for daily activities, which can help them maintain a sense of normalcy and independence.MATERIALS AND METHODS:The study was done in three main stages: the qualitative phase (phase 1), the device development phase (phase 2), and the quantitative phase (phase 3). The study’s two sections consist of demographic and semi-structured interview questions. The semi-structured survey instrument was created for Interviews with medical professionals and caregivers and included expectations for this kind of technology, as well as opinions on the necessity of an activity reminder clock and the difficulties involved in caring for dementia patients. During the qualitative phase, interviews with physicians and caregivers revealed themes such as the advantages of assistive technology and difficulties with implementation. Thematic analysis influenced the development of the user-friendly activity reminder clock. In the subsequent quantitative study, which had thirty participants, a Likert scale was used to assess effectiveness.RESULTS:The results revealed a resounding yes (86.67%), with 93.33% of participants thinking the reminder clock was essential for dementia care. A whopping 93% of the participants expressed satisfaction with its usability, affordability, and convenience of use. Fisher’s exact tests revealed a significant correlation between age and recommending the device to others (P = 0.03).CONCLUSION:The study highlights the reminder clock’s effectiveness and utility in enhancing daily tasks. Everyone agrees that it is necessary, logical, and beneficial. The findings indicate that age affects suggestions for device adoption and Favors tailored technology interventions to improve the quality of life for dementia patients.

Staff in the psychiatric emergency room (PER) have demanding jobs requiring a complex balance between the needs and safety of the individual and the community, systemic resources, and job responsibilities while providing timely, effective care. Little research exists concerning day-to-day work activities of PER staff, their interaction, and their perceptions of their work. This study explored the work of PER staff and the organisational context of the PER work setting. Observations of staff were conducted in the public spaces of a public urban PER using two observational techniques. The first was designed to measure the types of work activities staff engaged in and the time spent in these work activities (work task data). The second technique was the gathering of observational data by a peripheral-member-researcher (participant observation data). Analyses were conducted of both the work task and participant observation data. Results indicate that most PER staff time is spent in administrative and phone tasks, while less than a third is spent on direct clinical work. Four important issues for PER work were identified: a workload that is unmanageable, managing the unmanageable, bogus referrals and dumping and insurance problems. The PER remains the front-line of the medical and social service systems. Work done in these settings is of critical importance; however little attention is paid to the content and nature of the work. Our study demonstrates that staff of the PER face challenges on many levels as they struggle with the task of working with people presenting in psychiatric and social crisis.

A meta-analytic review of all adequately designed field and laboratory research on the use of incentives to motivate performance is reported. Of approximately 600 studies, 45 qualified. The overall average effect of all incentive programs in all work settings and on all work tasks was a 22% gain in performance. Team-directed incentives had a markedly superior effect on performance compared to individually-directed incentives. This effect was not influenced by the location of the study (business, government, or school), the competitive structure of the incentive system (programs where only the highest performers get incentives versus programs where everyone who increased performance receives incentives), the type of study (whether the study was a laboratory experiment or a field study), or the performance outcome (quality, quantity, or both). In these studies, money was found to result in higher performance gains than non-monetary, tangible incentives (gifts, travel). More research is needed on the relative cost-benefit of cash and gift incentives, and the way different types of tangible incentives are selected. Long-term programs led to greater performance gains than shorter-term programs did, and somewhat greater performance gains were realized for manual than for cognitive work. Explanations based on cognitive psychological principles accompany each of the analyses.