How AI chatbots have reshaped the frontline interface in China: examining the role of sales–service ambidexterity and the personalization–privacy paradox

PurposeThis study serves two purposes: (1) to evaluate the effects of organizational ambidexterity by examining how the balanced and the combined sales–service configurations of chatbots differ in their abilities to enhance customer experience and patronage and (2) to apply information boundary theory to assess the contingent role that chatbot sales–service ambidexterity can play in adapting to customers' personalization–privacy paradox.Design/methodology/approachAn online survey of artificial intelligence chatbots users was conducted, and a mixed-methods research design involving response surface analysis and polynomial regression was adopted to address the research aim.FindingsThe results of polynomial regressions on survey data from 507 online customers indicated that as the benefits of personalization decreased and the risk to privacy increased, the inherently negative (positive) effects of imbalanced (combined) chatbots' sales–service ambidexterity had an increasing (decreasing) influence on customer experience. Furthermore, customer experience fully mediated the association of chatbots' sales–service ambidexterity with customer patronage.Originality/valueFirst, this study enriches the literature on frontline ambidexterity and extends it to the setting of human–machine interaction. Second, the study contributes to the literature on the personalization–privacy paradox by demonstrating the importance of frontline ambidexterity for adapting to customer concerns. Third, the study examines the conduit between artificial intelligence (AI) chatbots' ambidexterity and sales performance, thereby helping to reconcile the previously inconsistent evidence regarding this relationship.

Highly Sensitive Flexible Modulus Sensor for Softness Perception and Clinical Application

The wearable sensors for softness measuring are emerging as a solution of softness perception, which is an intrinsic function of human skin, for electronic skin and human-machine interaction. However, these wearable sensors suffer from a key challenge: the modulus of an object can not be characterized directly, which originates from the complicated transduction mechanism. To address this key challenge, we developed a flexible and wearable modulus sensor that can simultaneously measure the pressure and modulus without mutual interference. The modulus sensing was realized by merging the electrostatic capacitance response from the pressure sensor and the ionic capacitance response from the indentation sensor. Via the optimized structure, our sensor exhibits high modulus sensitivity of 1.9 × 102 in 0.06 MPa, a fast dynamic response time of 100 ms, and high mechanical robustness for over 2500 cycles. We also integrated the sensor onto a prosthetic hand and surgical probe to demonstrate its capability for pressure and modulus sensing. This work provides a new strategy for modulus measurement, which has great potential in softness sensing and medical application.

Improving the Understanding of a Remote Environment by Immersive Man-Machine Interaction

In a changing world, the way we interact with machines must change as well. Teleoperation becomes more important. This poses its own set of challenges. To solve these a new Human-Machine interface must be developed. By developing this HMI around the concept of immersion, these challenges can be solved. This new kind of HMI can be applied to different fields. Examples using forestry or remote robot operations are demonstrated.

Self-healing, Mechanically Robust, and 3D Printable Ionogel for Highly Sensitive and Long-Term Reliable Ionotronics

Flexible sensors which can transduce various stimuli (e.g., strain, pressure, temperature) into electrical signals are highly in demand due to the development of human-machine interaction. However, it is still a...

Autonomous Surgical Robotics at Task and Subtask Levels

The revolution of minimally invasive procedures had a significant influence on surgical practice, opening the way to laparoscopic surgery, then evolving into robotics surgery. Teleoperated master-slave robots, such as the da Vinci Surgical System, has become a standard of care during the last few decades, performing over a million procedures per year worldwide. Many believe that the next big step in the evolution of surgery is partial automation, which would ease the cognitive load on the surgeon, making them possible to pay more attention on the critical parts of the intervention. Partial and sequential introduction and increase of autonomous capabilities could provide a safe way towards Surgery 4.0. Unfortunately, autonomy in the given environment, consisting mostly of soft organs, suffers from grave difficulties. In this chapter, the current research directions of subtask automation in surgery are to be presented, introducing the recent advances in motion planning, perception, and human-machine interaction, along with the limitations of the task-level autonomy.

Usage of Augmented Reality for Improved Human-Machine Interaction and Real-Time Error Correction of Laboratory Units

For future innovations, complex Industry 4.0-technologies need to improve the interaction of humans and technology. Augmented Reality (AR) has a significant potential for this task by introducing more interactivity into modern technical assistance systems. However, AR systems are usually very expensive and thus unsuitable for small and medium-sized enterprises (SMEs). Furthermore, the machine's reliable data transfer to the AR applications and the user activity indication appear to be problematic. This work proposes a solution to these problems. A simple and scalable data transfer from industrial systems to Android applications has been developed.The suggested prototype demonstrates an AR application for troubleshooting and error correction in real-time, even on mobile or wearable devices, while working in a laboratory unit to simulate and solve various errors. The unit components (small garage doors) are equipped with sensors. The information about the state of the system is available in real-time at any given moment and is transmitted to a mobile or wearable device (tablet or smart glass) equipped with AR application. The operator is enabled to preview the required information in a graphical form (marks and cursors). Potential errors are shown and solved with an interactive manual. The system can be used for training purposes to achieve more efficient error correction and faster repairing.

Research on rapier loom fault system based on cloud-side collaboration

The electrical control system of rapier weaving machines is susceptible to various disturbances during operation and is prone to failures. This will seriously affect the production and a fault diagnosis system is needed to reduce this effect. However, the existing popular fault diagnosis systems and methods need to be improved due to the limitations of rapier weaving machine process and electrical characteristics. Based on this, this paper presents an in-depth study of rapier loom fault diagnosis system and proposes a rapier loom fault diagnosis method combining edge expert system and cloud-based rough set and Bayesian network. By analyzing the process and fault characteristics of rapier loom, the electrical faults of rapier loom are classified into common faults and other faults according to the frequency of occurrence. An expert system is built in the field for edge computing based on knowledge fault diagnosis experience to diagnose common loom faults and reduce the computing pressure in the cloud. Collect loom fault data in the cloud, train loom fault diagnosis algorithms to diagnose other faults, and handle other faults diagnosed by the expert system. The effectiveness of loom fault diagnosis is verified by on-site operation and remote monitoring of the loom human-machine interaction system. Technical examples are provided for the research of loom fault diagnosis system.

English-Turkish Literary Translation Through Human-Machine Interaction

This article investigates perceptions of technology-mediated translations of literary texts by two groups: translation students and professional literary translators. The participants post-edited an excerpt from a classic Dickens novel into Turkish using a machine translation (MT) system of their choice. The analysis of the post-edited texts, participants’ answers to survey questions, and interviews with professional translators suggest that MT is currently a long way from being an essential part of any literary translation practice for the English–Turkish language pair. Translators’ interactions with MT and negative attitudes toward it may change in a positive direction as MT improves and translation practice evolves.

Future Directions for Human-Centered Transparent Systems for Engine Room Monitoring in Shore Control Centers

Many autonomous ship projects have reflected the increasing interest in incorporating the concept of autonomy into the maritime transportation sector. However, autonomy is not a silver bullet, as exemplified by many incidents in the past involving human and machine interaction; rather it introduces new Human Factor (HF) challenges. These challenges are especially critical for Engine Room Monitoring (ERM) in Shore Control Centre (SCCs) due to the system’s complexity and the absence of human senses in the decision-making process. A transparent system is one of the potential solutions, providing a rationale behind its suggestion. However, diverse implementations of transparency schemes have resulted in prevalent inconsistencies in its effects. This literature review paper investigates 17 transparency studies published over the last eight years to identify (a) different approaches to developing transparent systems, (b) the effects of transparency on key HFs, and (c) the effects of information presentation methods and uncertainty information. The findings suggest that the explicit presentation of information could strengthen the benefits of the transparent system and could be promising for performance improvements in ERM tasks in the SCC.