Showing papers by "Peter A. Gloor published in 2022"
TL;DR: In this article , a state-of-the-art systematic review of academic papers and a Machine Learning-based analysis of grey literature on the social implications of Industry 4.0 are presented.
33 citations
TL;DR: An emotion recognition system for dogs automatically identifying the emotions anger, fear, happiness, and relaxation is described, based on a previously trained machine learning model, which uses automatic pose estimation to differentiate emotional states of canines.
Abstract: This paper describes an emotion recognition system for dogs automatically identifying the emotions anger, fear, happiness, and relaxation. It is based on a previously trained machine learning model, which uses automatic pose estimation to differentiate emotional states of canines. Towards that goal, we have compiled a picture library with full body dog pictures featuring 400 images with 100 samples each for the states “Anger”, “Fear”, “Happiness” and “Relaxation”. A new dog keypoint detection model was built using the framework DeepLabCut for animal keypoint detector training. The newly trained detector learned from a total of 13,809 annotated dog images and possesses the capability to estimate the coordinates of 24 different dog body part keypoints. Our application is able to determine a dog’s emotional state visually with an accuracy between 60% and 70%, exceeding human capability to recognize dog emotions.
11 citations
TL;DR: In this paper , the authors demonstrate that hidden honest signals in the language and the use of "small words" can show true moral values and behavior of individuals and organizations and that this ethical behavior is correlated to real-world success.
Abstract: Abstract Everybody claims to be ethical. However, there is a huge difference between declaring ethical behavior and living up to high ethical standards. In this paper, we demonstrate that “hidden honest signals” in the language and the use of “small words” can show true moral values and behavior of individuals and organizations and that this ethical behavior is correlated to real-world success; however not always in the direction we might expect. Leveraging the latest advances of AI in natural language processing (NLP), we construct three different “tribes” of ethical, moral, and non-ethical people, based on Twitter feeds of people of known high and low ethics and morals: fair and modest collaborators codified as ethical “bees”; hard-working competitive workers as moral “ants”; and selfish, arrogant people as non-ethical “leeches”. Results from three studies involving a total of 49 workgroups and 281 individuals within three different industries (healthcare, business consulting, and higher education) confirm the validity of our model. Associating membership in ethical or unethical tribes with performance, we find that being ethical correlates positively or negatively with success depending on the context.
3 citations
TL;DR: In this paper , the authors combine machine learning with social network analysis (SNA) and natural language processing (NLP) to predict the personal values of individuals, and then use these values to predict individual and team performance.
Abstract: Do employees with high ethical and moral values perform better? Comparing personality characteristics, moral values, and risk-taking behavior with individual and team performance has long been researched. Until now, these determinants of individual personality have been measured through surveys. However, individuals are notoriously bad at self-assessment. Combining machine learning (ML) with social network analysis (SNA) and natural language processing (NLP), this research draws on email conversations to predict the personal values of individuals. These values are then compared with the individual and team performance of employees. This prediction builds on a two-layered ML model. Building on features of social network structure, network dynamics, and network content derived from email conversations, we predict personality characteristics, moral values, and the risk-taking behavior of employees. In turn, we use these values to predict individual and team performance. Our results indicate that more conscientious and less extroverted team members increase the performance of their teams. Willingness to take social risks decreases the performance of innovation teams in a healthcare environment. Similarly, a focus on values such as power and self-enhancement increases the team performance of a global services provider. In sum, the contributions of this paper are twofold: it first introduces a novel approach to measuring personal values based on “honest signals” in emails. Second, these values are then used to build better teams by identifying ideal personality characteristics for a chosen task.
1 citations
20 Oct 2022
TL;DR: In this paper , the authors introduce the key parts of happimetrics, the AI-based science to measure human emotions for better teamwork and higher organizational performance, which consists of three parts: emotional reactions reflecting individual morals create entangled tribes, measuring emotions and morals create happy and successful teams.
Abstract: This chapter introduces the key parts of happimetrics, the AI-based science to measure human emotions for better teamwork and higher organizational performance. Happimetrics consists of three parts: I – How do emotional reactions reflecting individual morals create entangled tribes? II – How can measuring emotions and morals create happy and successful teams? - III – How can emotions and morals be measured with AI?
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TL;DR: In this article , the authors give an introduction to flow, the highest state of human productivity when people work at their best, and extend it to groupflow, where teams reach the highest states of collective performance.
Abstract: The chapter gives an introduction to flow, the highest state of human productivity, when people work at their best. It extends it to groupflow, where teams reach the highest state of collective performance. It shows how success is the capability to suffer, and that teams need both diversity and similarity in team member composition to reach groupflow.
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TL;DR: Based on 20 years of research, Gloor as discussed by the authors lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals' communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way.
Abstract: Based on 20 years of research, this book lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals’ communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way. In doing so, Peter A. Gloor introduces artificial intelligence-based methods to identify personality, moral values, and ethics of individuals based on their body language and interaction with others.
20 Oct 2022
TL;DR: In this paper , the authors propose a social compass that helps individuals navigate the social landscape of their emotions and the emotions of others to become a better member of a team, based on their moral and ethical values, their personality, and their tribes.
Abstract: Just like Google Maps shows where somebody is in the physical world, where they can go, and where the bottlenecks and traffic jams are, the "Social Compass" helps individuals navigate the social landscape of their emotions and the emotions of others to become a better member of a team. It tells individuals how they see others, how others see them, and what they can do to be happier, and more collaborative and productive. The SocialCompass can be used to find the ideal team members, based on their moral and ethical values, based on their personality, and based on their tribes. The same technology can also be used to measure emotions of horses and dogs, and to use plants as biosensors by analyzing their feedback to human movement.
20 Oct 2022
TL;DR: In this article , the authors introduce work done in the last twenty years analyzing email and other electronic communication archives using SNA with the Web-based Griffin analysis tool, a Griffin version is freely available.
Abstract: Social Network Analysis" or SNA is the science that makes "networking" measurable. SNA tracks relations between different people through the structure of their network. SNA applies graph theory to determine the strength of interactions between individuals. This chapter introduces work done in the last twenty years analyzing email and other electronic communication archives using SNA with the Web-based Griffin analysis tool, a Griffin version is freely available. Griffin can be used to create a virtual mirror of one's own communication behavior by analyzing individual email.
20 Oct 2022
TL;DR: In this paper , the authors show how computers and the Internet empower us to measure inter-human interaction on a high level of granularity and detail, which will lead to more connected, collectively aware, entangled team members, and thus to teams collaborating in groupflow.
Abstract: This chapter shows how computers and the Internet empower us to measure inter-human interaction on a high level of granularity and detail. Sensors combined with AI give the capability to constantly analyze and interpret communication. Wearable technologies, cloud computing, and artificial intelligence measure happiness, wellbeing, workplace satisfaction, and stress, and mirror back these measurements to the individual. This will lead to more connected, collectively aware, entangled team members, and thus to teams collaborating in groupflow.
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TL;DR: In this article , the authors measured emotions in many different ways, looking at facial expressions, body signals of how somebody moves, voice patterns such as the tone of the voice, and at the choice of words somebody uses when communicating with others.
Abstract: With what emotions somebody responds to an external trigger is indicative of personality, ethical values, and risk attitudes. Understanding emotions opens the door to improved collaboration. Emotions can be measured in many different ways, looking at facial expressions, body signals of how somebody moves, voice patterns such as the tone of the voice, and at the choice of words somebody uses when communicating with others.
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TL;DR: Based on 20 years of research, Gloor as discussed by the authors lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals' communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way.
Abstract: Based on 20 years of research, this book lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals’ communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way. In doing so, Peter A. Gloor introduces artificial intelligence-based methods to identify personality, moral values, and ethics of individuals based on their body language and interaction with others.
20 Oct 2022
TL;DR: In this paper , the authors use machine learning, NLP and social network analysis to predict human behavior from communication logs through machine learning and NLP techniques, and use these techniques for predicting human behavior by analyzing archives of traces of humanto-human and human-to-other-living-creatures interaction.
Abstract: The analysis process to predict human behavior from communication logs through machine learning, NLP, and social network analysis follows four steps. This chapter outlines how to use these techniques for predicting human behavior by analyzing archives of traces of human-to-human and human-to-other-living-creatures interaction such as email or GPS sensor data. The aim is to find general patterns of human behavior indicative of future actions. Learning about these patterns, and then analyzing past behavior and comparing it with desirable behavior - "the best against the rest" - will change future behavior towards better performance and happiness.
20 Oct 2022
TL;DR: The concept of entanglement between humans is introduced in this article , and the characteristics of entangled organizations, synchronization in movement, shared emotions, shared language, shared facial expressions, and shared values are discussed.
Abstract: This chapter introduces the concept of entanglement between humans. Entangled humans know what others with whom they are entangled, think, independent of where they are. It shows how entanglement is created, and how entanglement increases happiness and groupflow. It introduces the characteristics of entangled organizations, synchronization in movement, shared emotions, shared language, shared facial expressions, and shared values.
20 Oct 2022
TL;DR: This paper used Natural Language Processing (NLP) to measure the influence of the inventor of a new word on the adoption of new words in a community using the concept of persuasive power.
Abstract: How quickly inventors of new words get others to use their newly created words is an excellent measure for the persuasive power of the inventor. More generally, the speed with which new concepts are picked up by others is an efficient metric for the influence that the inventor of the new concept has within a community. Using Natural Language Processing (NLP) this influence can easily be measured.
20 Oct 2022
TL;DR: In this paper , facial expressions indicate personality characteristics and ethical and moral values, and facial emotion recognition combined with machine learning is used to automate the process of identifying personality traits and moral beliefs.
Abstract: Facial expressions indicate personality characteristics and ethical and moral values. Facial emotion recognition combined with machine learning automates this process. Because emotional responses predict tribal affiliation, the emotion shown on one's face in response to an external event predicts personality characteristics and moral values.
20 Oct 2022
TL;DR: In this paper , an entanglement metric for email logs of an organization has been defined, which looks at how synchronized the email exchange between two people is, and the more they exchange messages in a similar rhythm, the more entangled they are.
Abstract: To measure the flow state in teams, an entanglement metric for email logs of an organization has been defined. It looks at how synchronized the email exchange between two people is. The more they exchange messages in a similar rhythm, the more entangled they are. This metric has been validated in different organizations, finding that selective, focused entanglement of employees is a strong predictor of team creativity, employee satisfaction, employee performance, and customer satisfaction.
20 Oct 2022
TL;DR: In this paper , the authors describe the interplay between morality and emotions and show how our emotional response to external events is dependent on our morals and value system, and explain how controlling our emotions can reduce stress.
Abstract: The chapter describes the interplay between morality and emotions. It shows how our emotional response to external events is dependent on our morals and value system. It explains how controlling our emotions can reduce stress, and introduces the moral value frameworks of Schwartz and Haidt, and the DOSPERT risk taking measurement system.