Letteratura scientifica selezionata sul tema "Artificial empathy"
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Articoli di riviste sul tema "Artificial empathy":
1
Asada, Minoru. "Towards Artificial Empathy". International Journal of Social Robotics 7, n. 1 (29 novembre 2014): 19–33. http://dx.doi.org/10.1007/s12369-014-0253-z.
2
Asada, Minoru. "Development of artificial empathy". Neuroscience Research 90 (gennaio 2015): 41–50. http://dx.doi.org/10.1016/j.neures.2014.12.002.
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Stephan, Achim. "Empathy for Artificial Agents". International Journal of Social Robotics 7, n. 1 (18 novembre 2014): 111–16. http://dx.doi.org/10.1007/s12369-014-0260-0.
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Damiano, Luisa, Paul Dumouchel e Hagen Lehmann. "Artificial Empathy: An Interdisciplinary Investigation". International Journal of Social Robotics 7, n. 1 (31 ottobre 2014): 3–5. http://dx.doi.org/10.1007/s12369-014-0259-6.
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Wang, Yu, Yanzhong Zhang, Yanji Wang, Hao Zhang, Xinpeng Wang, Rongqing Xu e Yi Tong. "Realization of Empathy Capability for the Evolution of Artificial Intelligence Using an MXene(Ti3C2)-Based Memristor". Electronics 13, n. 9 (24 aprile 2024): 1632. http://dx.doi.org/10.3390/electronics13091632.
Abstract (sommario):
Empathy is the emotional capacity to feel and understand the emotions experienced by other human beings from within their frame of reference. As a unique psychological faculty, empathy is an important source of motivation to behave altruistically and cooperatively. Although human-like emotion should be a critical component in the construction of artificial intelligence (AI), the discovery of emotional elements such as empathy is subject to complexity and uncertainty. In this work, we demonstrated an interesting electrical device (i.e., an MXene (Ti3C2) memristor) and successfully exploited the device to emulate a psychological model of “empathic blame”. To emulate this affective reaction, MXene was introduced into memristive devices because of its interesting structure and ionic capacity. Additionally, depending on several rehearsal repetitions, self-adaptive characteristic of the memristive weights corresponded to different levels of empathy. Moreover, an artificial neural system was designed to analogously realize a moral judgment with empathy. This work may indicate a breakthrough in making cool machines manifest real voltage-motivated feelings at the level of the hardware rather than the algorithm.
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Montiel-Vázquez, Edwin Carlos, Jorge Adolfo Ramírez Uresti e Octavio Loyola-González. "An Explainable Artificial Intelligence Approach for Detecting Empathy in Textual Communication". Applied Sciences 12, n. 19 (20 settembre 2022): 9407. http://dx.doi.org/10.3390/app12199407.
Abstract (sommario):
Empathy is a necessary component of human communication. However, it has been largely ignored in favor of other concepts such as emotion and feeling in Affective computing. Research that has been carried out regarding empathy in computer science lacks a method of measuring empathy based on psychological research. Likewise, it does not present an avenue for expanding knowledge regarding this concept. We provide a comprehensive study on the nature of empathy and a method for detecting it in textual communication. We measured empathy present in conversations from a database through volunteers and psychological research. Subsequently, we made use of a pattern-based classification algorithm to predict the Empathy levels in each conversation. Our research contributions are: the Empathy score, a metric for measuring empathy in texts; Empathetic Conversations, a database containing conversations with their respective Empathy score; and our results. We show that an explicative pattern-based approach (PBC4cip) is, to date, the best approach for detecting empathy in texts. This is by measuring performance in both nominal and ordinal metrics. We found a statistically significant difference in performance for our approach and other algorithms with lower performance. In addition, we show the advantages of interpretability by our model in contrast to other approaches. This is one of the first approaches to measuring empathy in texts, and we expect it to be useful for future research.
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Alsager Alzayed, Mohammad, Scarlett R. Miller e Christopher McComb. "Empathic creativity: can trait empathy predict creative concept generation and selection?" Artificial Intelligence for Engineering Design, Analysis and Manufacturing 35, n. 4 (novembre 2021): 369–83. http://dx.doi.org/10.1017/s0890060421000196.
Abstract (sommario):
AbstractOver the past decade, engineering design research has seen a significant surge of the discussion of empathy. As such, design researchers have been devoted in devising and assessing empathic design activities. While prior research has examined the utility of empathic design experiences on driving creative concept generation, little is known about the role of a designer's empathic tendencies in driving creative concept generation and selection in an engineering design project. Without this knowledge, we cannot be sure if, when, or how empathy influences the design process. Thus, the main goal of this paper was to identify the role of trait empathy in creative concept generation and selection in an engineering design student project. In order to achieve this objective, a study was conducted with 103 first-year engineering students during two design stages of an 8-week design project (concept generation and concept selection). The main findings from this paper highlighted that empathic concern tendencies positively impacted the generation of more ideas while personal distress tendencies negatively impacted the generation of more ideas. During concept selection, perspective-taking tendencies positively impacted participants’ propensity for selecting elegant ideas. This research took the first step in encouraging empirical investigations aimed at understanding the role of trait empathy across different stages of the design process.
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Yang, Hsuan-Chia, Annisa Ristya Rahmanti, Chih-Wei Huang e Yu-Chuan Jack Li. "How Can Research on Artificial Empathy Be Enhanced by Applying Deepfakes?" Journal of Medical Internet Research 24, n. 3 (4 marzo 2022): e29506. http://dx.doi.org/10.2196/29506.
Abstract (sommario):
We propose the idea of using an open data set of doctor-patient interactions to develop artificial empathy based on facial emotion recognition. Facial emotion recognition allows a doctor to analyze patients' emotions, so that they can reach out to their patients through empathic care. However, face recognition data sets are often difficult to acquire; many researchers struggle with small samples of face recognition data sets. Further, sharing medical images or videos has not been possible, as this approach may violate patient privacy. The use of deepfake technology is a promising approach to deidentifying video recordings of patients’ clinical encounters. Such technology can revolutionize the implementation of facial emotion recognition by replacing a patient's face in an image or video with an unrecognizable face—one with a facial expression that is similar to that of the original. This technology will further enhance the potential use of artificial empathy in helping doctors provide empathic care to achieve good doctor-patient therapeutic relationships, and this may result in better patient satisfaction and adherence to treatment.
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Gómez-León, María Isabel. "Development of empathy through Socioemotional Artificial Intelligence". Papeles del Psicólogo - Psychologist Papers 43, n. 3 (2022): 218. http://dx.doi.org/10.23923/pap.psicol.2996.
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Rostami, Mehdi, e Shokouh Navabinejad. "Artificial Empathy: User Experiences with Emotionally Intelligent Chatbots". AI and Tech in Behavioral and Social Sciences 1, n. 3 (2023): 19–27. http://dx.doi.org/10.61838/kman.aitech.1.3.4.
Abstract (sommario):
This study aims to explore user experiences with emotionally intelligent chatbots, focusing on their perceived empathy, satisfaction with interactions, and the impact on user perception. Additionally, it seeks to identify the main challenges and future expectations users have towards these AI systems. Employing a qualitative research design, this study collected data through semi-structured interviews with 28 participants who had interacted with emotionally intelligent chatbots in various contexts. Thematic analysis was conducted to identify main themes, categories, and concepts within the data, providing insights into users' perceptions and experiences. The analysis revealed eight main themes: Perceived Empathy, Interaction Satisfaction, Trust and Security, Human-Like Interaction, User Adaptation, Impact on User Perception, Barriers to Engagement, and Future Expectations. These themes encompass categories such as Emotional Understanding, Contextual Sensitivity, Engagement Level, Privacy Concerns, Learning Curve, AI Capabilities, Technological Limitations, and Improvement Suggestions. Participants valued chatbots' ability to understand and adapt to their emotional states but highlighted challenges in achieving authentic empathy and expressed concerns over privacy and data security. Emotionally intelligent chatbots hold promise for enhancing user experiences through artificial empathy. However, the authenticity of empathy, coupled with ethical considerations such as privacy and security, presents significant challenges. Future developments should focus on improving the genuineness of empathetic responses, ensuring ethical use of AI, and addressing users' concerns to fully realize the potential of emotionally intelligent chatbots.
Tesi sul tema "Artificial empathy":
1
Anshar, Muh [Verfasser]. "Hardwiring Robot Empathy through Generation of Artificial Pain : Concetualizing Empathy into Adaptive Self-Awareness Framework for Robot / Muh Anshar". München : GRIN Verlag, 2019. http://d-nb.info/119552630X/34.
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Gomes, Renata Correia Lima Ferreira. "Agentes verossímeis: uma investigação sobre a construção dos personagens autônomos nos videogames". Pontifícia Universidade Católica de São Paulo, 2008. https://tede2.pucsp.br/handle/handle/5142.
Abstract (sommario):
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Renata Correia Lima Ferreira Gomes.pdf: 13310244 bytes, checksum: 461b70952a77f132a4d560c29c6c5e16 (MD5)
Previous issue date: 2008-11-03Conselho Nacional de Desenvolvimento Científico e Tecnológico
From the conceptual of character-oriented games and of simulation games the present research draws the idea of narrative games as an immersive simulation , to be experienced by the interactor through his or her traversing the virtual space of the game as an implicated character and through his or her interaction with the autonomous characters of the game. We carry through the hypothesis that the key for the implentation of a dramatic strutucture in the game albeit fundamentally different from that of film or theater is in the design of autonomous characters. These we take to be object inhabiting the space-time of the game, carrying a high degree of autonomy, complexity and intentionality, who, through the possibility of empathy, constitute in themselves a pathway towards a dramatic entity with or against whom the interactor has to act. To demonstrate that, we describe narrative as a evolutionary strategy towards a causal mindframe, which evolves side-be-side with the media that materialize it, from oral narratives to 3D interactive digital pieces. A second step toward demonstrating our hypothesis is to describe autonomous characters through Artificial Intelligence applied to narrative: the believable characters . We take as a reference the work of the research groups Oz and Synthetic Characters, and of Brazilian game designer Marcos Cuzziol. Finally, a third step is to approach the nature of the fiction character, through the work of Aristotle and Fernando Segolin, and the concept of empathy, under the approach of Evan Thompson. Empathy here is understood as pre-condition for the comprehension of the Other and of ourselves as affective, emotional and intentional entities. To illustrate this final view, we analyze a few aspects of the Creatures from the games Black & White I e II, in an attempt to point out how some qualities proposed are instantiated
A partir do universo dos games de personagem e games de simulação , a pesquisa em curso pretende descrever a narrativa nos games como uma simulação imersiva , a ser experimentada pelo interator através de seu percurso pelo espaço virtual do game no papel de um personagem e de sua interação com personagens autônomos, operados pelo software. Levamos adiante a hipótese de que a peça-chave para a implementação de uma estrutura dramática no game ainda que fundamentalmente diferente daquela conhecida no cinema e teatro - jaz no design dos personagens autônomos. Estes entendemos como objetos do espaço-tempo virtual, dotados de alto grau de autonomia, complexidade e intencionalidade, que, através da possibilidade de empatia, constituiriam em si o caminho para a emergência de uma vontade dramática com/contra a qual o interator teria que lidar. Para isto, descrevemos a narrativa como uma estratégia evolutiva de pensamento comunicacional e causal, que se desenvolve de acordo com os meios nos quais se materializa, da oralidade primária ao audiovisual digital interativo 3D. Um segundo passo trata de descrever os personagens autônomos, em sua faceta de Inteligência Artificial voltada para games e narrativas interativas: os agentes verossímeis . Para isso, tomamos como referência o trabalho dos grupo de pesquisa Oz e Sythetic Characters, assim como do game designer brasileiro Marcos Cuzziol. Um terceiro passo consiste em abordar a natureza da personagem de ficção a partir de Aristóteles, Fernando Segolin e do conceito de empatia, sobretudo na visão de Evan Thompson, esta entendida como pré-condição para a compreensão do outro e de nós mesmos como entidades afetivas, emocionais e intencionais. Para finalizar, procedemos a uma análise de alguns aspectos das Criaturas dos jogos Black & White I e II, na tentativa de descrever como se instanciam algumas qualidades das propostas anteriores
3
Wu, Di. "What Distinguishes Humans from Artificial Beings in Science Fiction World". Thesis, Blekinge Tekniska Högskola, Sektionen för planering och mediedesign, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2245.
Abstract (sommario):
In my thesis, I explore how advanced robotic technologies affect human society and my particular concern centers on investigating the boundaries between actual humans and artificial beings. Taking Steven Spielberg’s film Artificial Intelligence (2001) and Philip K. Dick’s novel Do Androids Dream of Electric Sheep (1968) as my primary sources, I illustrate how humans are experiencing dehumanization whereas artificial beings are acting much more like humans by analyzing the main characters and events that depicted in both sources. Further on, based on Nick Haslam’s theory of two main forms of dehumanization (animalistic dehumanization and mechanistic dehumanization), I discuss the interrelationships between social categorization, empathy, alienation and dehumanization by comparing actual humans and artificial beings as counter-parts. According to the descriptions of the strained relationship between these two parties, I argue that the rigid social hierarchies set foundation for dehumanization and the characteristics that define a human being, such as humanity is not a trait that only exits in humans. It can be both gained and lost.
4
Alexander, Ryan Cherian. "Artificial empathy : using vector space modeling and mixed scope alignment to infer emotional states of characters in stories". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106032.
Abstract (sommario):
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 61-62).
Emotions greatly influence human cognition. Therefore, if we are to develop artificially intelligent programs that work closely with humans, we must ensure that they are capable of empathy. In an effort to realize the goal of emotionally aware programs, I created a multi-corpus informed vector space model to determine the emotions evoked by individual terms. I then combined that information with the semantic parse trees produced by the Genesis Story Understanding System to ascertain the emotions evoked by a single sentence. Additionally, I used the story aligner within Genesis to determine the emotions evoked by stories described over multiple sentences. My program can infer characters' emotional states based on their descriptions, the situations they are involved in, and the actions they perform. For instance, it infers that Alice is joyful from the sentence "Alice wins an award" and that James is probably experiencing sadness from the sentence "James is lonely." Additionally, the program can identify that Austin is likely surprised if "Austin has to take a test" and "Austin doesn't know about the test."
by Ryan Cherian Alexander.
M. Eng.
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Basedow, Christina Anne [Verfasser], Arvid [Akademischer Betreuer] [Gutachter] Kappas, Ulrich [Gutachter] Kühnen e Eric [Gutachter] Vanman. "Empathy with Robots? Exploring Emotional Responses to Artificial Entities / Christina Anne Basedow. Betreuer: Arvid Kappas. Gutachter: Arvid Kappas ; Ulrich Kühnen ; Eric Vanman". Bremen : IRC-Library, Information Resource Center der Jacobs University Bremen, 2016. http://d-nb.info/1104481081/34.
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Colombel, Jessica. "Analyse du mouvement humain pour l'assistance à la personne : apport de la robustesse de l’observation et de l’analyse par contrôle optimal inverse". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0210.
Abstract (sommario):
Le mouvement biologique possède de nombreuses informations, qu'elles soient physique ou cognitive. Des travaux ont montré qu'il était possible de déterminer le genre d'une personne, son émotion, voire même son identité. Ces caractéristiques sont accessibles à partir d'information sur la dynamique du mouvement des corps poly-articulés (e.g. le mouvement des points d'articulation). Comprendre et interpréter le comportement d'une personne et son état sont des capacités liées à l'empathie. C'est une faculté commune à l'ensemble des mammifères qui se base sur certains systèmes neuronaux comprenant, entre autre, les neurones miroirs. Étant donné que l'empathie participe grandement aux interactions sociales chez les hommes et plus généralement les animaux, on est en mesure de se demander comment notre relation avec les robots peut s'en inspirer.Cela nous amène à la problématique suivante: l'assistance robotique à la personne peut-elle se servir de l'interprétation du mouvement humain, riche d'informations physiques et cognitives, comme modalité d'amélioration de l'Interaction Humain Robot ?Pour répondre à cette problématique, nous nous positionnons sur des outils d'observations et sur une méthode d'analyse du mouvement qui soient exploitables en temps réel par un système robotique.Dans un premier temps, nous avons travaillé sur les outils d'observation du mouvement humain. Nos objectifs d'assistance robotisée en milieu écologique, nécessitent d'installer des capteurs qui affectent le moins possible les actions de la personne. Nous avons donc choisi d'étudier le capteur Kinect de Microsoft qui est un capteur de profondeur accessible permettant de récupérer les positions cartésiennes des articulations et extrémités du corps. Cependant, ce type de capteur est sujet à des bruits de mesure qui empêcherait une analyse fine du mouvement. Nous avons donc développé deux méthodes pour améliorer la mesure de ce capteur basé sur le Filtre de Kalman Etendu (EKF): un EKF sous contrainte anthropométrique et un EKF de fusion de capteurs. Nous avons fait la première étude sur la Kinect de 2ème génération et la deuxième sur les générations 2 et 3, permettant de mettre en avant les différences entre ces deux capteurs.Dans un second temps, nous nous sommes intéressés aux méthodes d'analyse du mouvement et plus spécifiquement au problème de Control Optimal Inverse (COI). L'objectif du COI est d'identifier les pondérations associées à un ensemble de fonctions de coûts à optimiser pour générer une trajectoire donnée. Dans le cadre de cette thèse, nous cherchons à analyser en temps réel des trajectoires de mouvement humain dont les mesures, issus de capteurs, sont bruitées. Nous avons étudié la fiabilité de la méthode de résolution du COI dite Approchée, en fonction du bruit de mesure. Nous apportons également une approche originale du COI qui pose une nouvelle vision de l'optimalité de trajectoires et permet de présenter les concepts de Courbes de Singularité et de Projection. Nous montrons dans cette étude des outils permettant de mieux comprendre et prendre en compte les problématique de robustesse du COIBiological motion has a lot of information, both physical and cognitive. Studies have shown that it is possible to determine a person's gender, emotion and even identity. These characteristics are accessible from information on the dynamics of the movement of polyarticulated bodies (e.g. the movement of the articulation points). Understanding and interpreting a person's behavior and state are abilities related to empathy. It is a faculty common to all mammals and is based on certain neural systems including, among others, mirror neurons. Given that empathy is an important part of social interactions in humans and more generally in animals, we can ask ourselves how our relationship with robots can be inspired by it.This leads us to the following problem: can robotic assistance to people use the interpretation of human movement, rich in physical and cognitive information, as a modality to improve the Human-Robot Interaction?To answer this question, we are working on observation tools and on a method of motion analysis that can be used in real time by a robotic system.Initially, we worked on the observation tools of human movement. Our objectives of robotic assistance in an ecological environment require the installation of sensors that affect the person's actions as little as possible. We have therefore chosen to study the Microsoft Kinect sensor which is an accessible depth sensor allowing to recover the Cartesian positions of the joints and extremities of the body. However, this type of sensor is subject to measurement noise that would prevent a fine analysis of the movement. We have therefore developed two methods to improve the measurement of this sensor based on the Extended Kalman Filter (EKF): an anthropometrically constrained EKF and a sensor fusion EKF. We have done the first study on the 2nd generation Kinect and the second on the 2nd and 3rd generations, allowing to highlight the differences between these two sensors.In a second time, we were interested in motion analysis methods and more specifically in the problem of Inverse Optimal Control (IOC). The objective of IOC is to identify the weights associated with a set of cost functions to be optimized to generate a given trajectory. In this thesis, we seek to analyze in real time human motion trajectories whose measurements, coming from sensors, are noisy. We have studied the reliability of the IOC resolution method called Approached, as a function of the measurement noise. We also provide an original approach to the IOC that poses a new view of the optimality of trajectories and allows us to introduce the concepts of Singularity Curves and Projection. We show in this paper tools to better understand and take into account the robustness issues of IOC
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Widén, Tuva. "Artificial Resources : An Artistic Exploration of Material Subjectivity". Thesis, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-7294.
Abstract (sommario):
This essay investigates questions concerning the illusion of control and how a change of attitude can counteract an irreversible deterioration of our living environment. The key question is how an artistic practice can help to challenge contemporary attitudes and the assumption that the living planet is an inexhaustible and limitless resource. The aim is to explore three fields of experience where a shared and mutually independent relationship is possible: with ourselves, with our fellow human beings and with the living planet. It examines contemporary research that identify and describes the destructive development of a culture with an over-naturalized relationship to these thee fields of experience. It discusses how an artistic practice can operate on a methodological level to contribute to the development of this research from three perspectives: (a) by how it can relates to the materials used to communicate, (b) by how it is embodied or corporeal, and (c) by how it can apply what is called techniques of subjectivity. The essay also describes Tuva Widén’s specific piece exhibited at the spring exhibition at Konstfack 2020 and explains how the outlined methodological principles are applied in this specific work.
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Henriques, Nuno Andrade da Cruz. "SensAI+Expanse : Prediction of Emotional Valence Changes on Humans in Context by an Artificial Agent Towards Empathy". Doctoral thesis, 2020. http://hdl.handle.net/10451/44892.
Abstract (sommario):
The field of Cognitive Science is broader enough on the interdisciplinary
study of the brain, mind, and intelligence with a scientific research
community gaining momentum over the last few decades. Specifically,
joining the two fields of psychology and artificial intelligence (AI) one
may envision agents, embodied or not, human-like or wearable, with
the ability to significantly change the way humans live. This research
conceive the artificial agent as a non-anthropomorphic with adaptive
empathy for human-agent interaction (HAI) synergy towards better
companionship. Therefore, the main objectives of this research are (a) to
build a predictive model for each human user on context-based emotional
valence changes; and (b) to study the age, gender, and human behaviour
neutrality and robustness of the artificial agent regarding the prediction
ability. The context include geographically located data from sensors,
text sentiment analysis, and human emotional valence self-report, all
timestamped events, using a common mobile device such as a smartphone.
Also, to analyse and discuss the results on how to leverage such a
model to adapt interaction strategies in order to foster higher levels
of empathy between a non-anthropomorphic agent and its interacting
human. For these goals SensAI+Expanse is developed where SensAI acts as
an embodied nearby agent and Expanse encompass the machine learning
resources in efficient manner, i.e., a distributed, fault-tolerant, mobile
and Cloud-based platform from scratch as a research tool to continuously,
online, gather and process data towards automated machine learning
(AutoML) and prediction.
The study is designed with a methodology in place to avoid the Western,
Educated, Industrialized, Rich, and Democratic (WEIRD) societies bias.
This goal is accomplished by collecting data in the wild and worldwide
by making use of the publicly accessible Google Play repository for
the Android™ SensAI smartphone application. Eligible participants
are diverse in age, gender, and behaviour on self-reporting emotional
valence. In order to balance the gender distribution by age a dichotomy
approach using age median (M = 34) is used. Regarding participation
duration, two thirds (33/49) of the eligible individuals for analysis remain
interacting for the required minimum of four weeks. The analysis of the results show evidence of significant behaviour differences between some
age and gender combinations regarding self-reported emotional valence.
Furthermore, the results from a comparison study between state-of-the-art
algorithms revealed Extreme Gradient Boosting on average the best model
for prediction (F1 = 0:91) with efficient energy use, and explainable using
feature importance inspection. Moreover, the artificial agent remained
neutral regarding human demographics and, simultaneously, able to
reveal individual idiosyncrasies. Therefore, this research contributions
include results with evidence, restricted to population and data samples
available, of differences in behaviour amongst some combinations of age
ranges versus gender. The main contribution is a novel platform for
studies regarding human emotional valence changes in context. This
system may complement and supersede (eventually) traditional long-list
self-appraisal questionnaires. The SensAI+Expanse platform contributes
with several parts such as a mobile device application (SensAI) able
to adapt and learn in order to predict emotional valence states with
high performance, a cloud computing (Cloud) service (SensAI Expanse)
with ready-to-action analysis and processing modules towards AutoML.
Additionally, smartphone sensing add a contribution for continuous,
non-invasive and personalised health check. In the future, developments
about human-agent relationships regarding affective interactions are foreseen.
Further, the measurement of empathetic reactions and evaluating
outcomes may be used to verify and validate health status thus improving
care and significantly change the way humans live.O campo da ciência cognitiva é suficientemente amplo no estudo interdisciplinar do cérebro, mente, e inteligência com uma comunidade de pesquisa científica em crescimento nas últimas décadas. Especificamente, juntando os dois campos da psicologia e inteligência artificial, é possível antever agentes, incorporados ou não, como humanos ou abstratos numa pulseira, com a capacidade de mudar significativamente a maneira como vivemos. A investigação descrita neste documento concebe o agente não antropomórfico com empatia adaptativa por sinergia da interação humano-artificial no sentido de uma melhor companhia entre agentes. Assim, os principais objetivos desta pesquisa são (a) construir um modelo de previsão adaptada a cada utilizador humano sobre mudanças de valência emocional em contexto; e (b) estudar comparativamente à idade, género, e comportamento humano a neutralidade e robustez do agente artificial na sua capacidade de previsão. O contexto inclui dados geograficamente localizados de sensores, análise de sentimento em texto, e de relatórios de valência emocional pelos humanos, estes eventos incluem informação temporal, usando um dispositivo móvel comum, tal como um telemóvel. Adicionalmente, para analisar e discutir os resultados de como alavancar esse modelo para se adaptarem estratégias de interação, de modo a promover aumento da empatia entre um agente não antropomórfico e o seu utilizador humano em contacto. Para cumprir estes objetivos é desenvolvido o SensAI+Expanse onde SensAI atua como um agente corporizado e de proximidade, e o Expanse abrange os recursos de aprendizagem por computador (machine learning) de forma eficiente. Isto é, uma plataforma distribuída, tolerante ao erro, móvel e baseada na nuvem (Cloud) informática, criada de raiz como ferramenta de pesquisa para reunir dados continuamente, ligada, e os processar para a aprendizagem automatizada por computador (automated machine learning) e a previsão. O estudo é desenvolvido com uma metodologia específica para evitar o viés das sociedades educadas, industrializadas, ricas e democráticas (conhecido como WEIRD). Este objetivo é alcançado através da recolha de dados em campo e alargado ao mundo inteiro (potencialmente) fazendo uso do repositório Google Play acessível ao público como local de publicação da aplicação SensAI. Os participantes elegíveis são diversos em idade, género, e no comportamento ao informarem a valência emocional. No sentido de equilibrar adequadamente a distribuição de género por idade, uma abordagem dicotómica utiliza a mediana das idades (M = 34). Em relação à duração da participação, dois terços (33/49) dos indivíduos elegíveis para análise permaneceram em interação pelo mínimo necessário de quatro semanas. A análise dos resultados mostra evidência de diferenças significativas de comportamento entre algumas combinações de idade e género em relação à valência emocional informada pelos utilizadores. Adicionalmente, os resultados de um estudo comparativo entre os melhores algoritmos atuais revelaram o Extreme Gradient Boosting, em média, o melhor modelo para previsão (F1 = 0; 91) com uso eficiente de energia e explicável usando inspeção de importância de cada caraterística (e.g., localização específica). Além disso, o agente artificial permaneceu neutro em relação à demografia humana e, simultaneamente, capaz de revelar idiossincrasias individuais. Portanto, as contribuições desta pesquisa incluem resultados com evidência, restritos à população e amostras de dados disponíveis, de diferenças de comportamento entre algumas combinações de intervalos etários e género. A principal contribuição é uma nova plataforma para estudos sobre as mudanças de valência emocional nos humanos e em contexto. Este sistema pode complementar e substituir (eventualmente) os tradicionais questionários com listas longas de questões para autoavaliação. A plataforma SensAI+Expanse contribui com várias partes, tais como (a) uma aplicação de dispositivo móvel (SensAI) com a capacidade de se adaptar e aprender de modo a prever estados de valência emocional com elevado desempenho; e (b) um serviço de computação em nuvem (Cloud), o SensAI Expanse, capaz de análise no momento e com módulos de processamento para a aprendizagem automatizada por computador (automated machine learning). Além disso, a abordagem de recolha de dados usando os sensores do telemóvel (smartphone sensing) adiciona uma contribuição no para análise da saúde ou do bem-estar em contínuo, não invasivo, e personalizado. Num futuro próximo, prevê-se um desenvolvimento interessante sobre as relações humano-agente em relação às interações afetivas. Adicionalmente, a medição das reações empáticas e a avaliação dos resultados das mesmas podem ser usados para verificar e validar o estado de saúde, e assim melhorar os cuidados e mudar significativamente a forma de viver dos seres humanos.
9
Anshar, Muh. "Evolving robot empathy through the generation of artificial pain in an adaptive self-awareness framework for human-robot collaborative tasks". Thesis, 2017. http://hdl.handle.net/10453/116217.
Abstract (sommario):
University of Technology Sydney. Faculty of Engineering and Information Technology.The application and use of robots in various areas of human life have been growing since the advent of robotics, and as a result, an increasing number of collaboration tasks are taking place. During a collaboration, humans and robots typically interact through a physical medium and it is likely that as more interactions occur, the possibility for humans to experience pain will increase. It is therefore of primary importance that robots should be capable of understanding the human concept of pain and to react to that understanding. However, studies reveal that the concept of human pain is strongly related to the complex structure of the human nervous system and the concept of Mind which includes concepts of Self-Awareness and Consciousness. Thus, developing an appropriate concept of pain for robots must incorporate the concepts of Self-Awareness and Consciousness. Our approach is firstly to acquire an appropriate concept of self-awareness as the basis for a robot framework. Secondly, it is to develop an internal capability for a framework for the internal state of the mechanism by inferring information captured through internal and external perceptions. Thirdly, to conceptualise an artificially created pain classification in the form of synthetic pain which mimics the human concept of pain. Fourthly, to demonstrate the implementation of synthetic pain activation on top of the robot framework, using a reasoning approach in relation to past, current and future predicted conditions. Lastly, our aim is to develop and demonstrate an empathy function as a counter action to the kinds of synthetic pain being generated. The framework allows robots to develop "self-consciousness" by focusing attention on two primary levels of self, namely subjective and objective. Once implemented, we report the results and provide insights from novel experiments designed to measure whether a robot is capable of shifting its "self-consciousness" using information obtained from exteroceptive and proprioceptive sensory perceptions. We consider whether the framework can support reasoning skills that allow the robot to predict and generate an accurate "pain" acknowledgement, and at the same time, develop appropriate counter responses. Our experiments are designed to evaluate synthetic pain classification, and the results show that the robot is aware of its internal state through the ability to predict its joint motion and produce appropriate artificial pain generation. The robot is also capable of alerting humans when a task will generate artificial pain, and if this fails, the robot can take considerable preventive actions through joint stiffness adjustment. In addition, an experiment scenario also includes the projection of another robot as an object of observation into an observer robot. The main condition to be met for this scenario is that the two robots must share a similar shoulder structure. The results suggest that the observer robot is capable of reacting to any detected synthetic pain occurring in the other robot, which is captured through visual perception. We find that integrating this awareness conceptualisation into a robot architecture will enhance the robot’s performance, and at the same time, develop a self-awareness capability which is highly advantageous in human-robot interaction. Building on this implementation and proof-of-concept work, future research will extend the pain acknowledgement and responses by integrating sensor data across more than one sensor using more sophisticated sensory mechanisms. In addition, the reasoning will be developed further by utilising and comparing the performance with different learning approaches and different collaboration tasks. The evaluation concept also needs to be extended to incorporate human-centred experiments. A major possible application of the proposal to be put forward in this thesis is in the area of assistive care robots, particularly robots which are used for the purpose of shoulder therapy.
10
Abath, Beatriz Maciel. "Empatia em agentes artificiais : proposta de um novo instrumento de avaliação". Master's thesis, 2021. http://hdl.handle.net/10451/51749.
Abstract (sommario):
Tese de Mestrado, Ciência Cognitiva, 2021, Universidade de Lisboa, Faculdade de CiênciasEste trabalho visa contribuir para as discussões sobre o desenvolvimento de agentes artificiais empáticos, especialmente no que se refere à sua avaliação. Ainda não há instrumentos validados para medir a empatia em agentes artificiais e a maioria dos estudos nessa área utilizam medidas criadas ou adaptadas para cada pesquisa específica. Medidas validadas são essenciais para gerar dados confiáveis sobre aquilo que se pretende medir. O objetivo principal deste estudo é propor um instrumento de avaliação válido que possa vir a ser aplicado tanto em agentes artificiais quanto em seres humanos. O instrumento proposto avalia a empatia percebida por uma terceira pessoa, após observação da interação, e foi construído em Português, tendo sido baseado no instrumento de Davis, no instrumento de Toronto e em medidas não validadas aplicadas em estudos sobre agentes artificiais empáticos. A coleta de dados e a aplicação do instrumento foram realizadas pela internet, por meio da plataforma Qualtrics. As interações foram apresentadas em quatro vídeos legendados, 3 em que agentes artificiais (o chatbot Wysa, o personagem virtual Autotutor, e um robô do tipo NAO) interagem com seres humanos e 1 em que dois seres humanos interagem entre si. Os participantes foram convidados para participarem voluntariamente da pesquisa, via e-mail e redes sociais. O chatbot Wysa foi avaliado por 95 pessoas, o Autotutor por 96, o robô NAO por 100, e o ser humano por 99. Todos os participantes declararam ter 18 anos ou mais e serem fluentes na língua portuguesa, sendo 132 brasileiros, 50 portugueses e um argentino. Dentre os participantes, 103 declararam-se do sexo feminino e 73, do sexo masculino. A versão final do instrumento possui oito itens, que refletem componentes cognitivos, afetivos e comportamentais da empatia, e que se aproximam da definição de empatia proposta por Hoffman (1985). A análise fatorial apontou um fator único e os coeficientes do alfa de Cronbach situaram-se sempre acima de 0,8, indicando que o instrumento se mostrou válido e confiável. Com exceção do Autotutor, todos os agentes, incluindo o ser humano, foram bem avaliados como empáticos.
This research aims to contribute to the discussions on the development of empathetic artificial agents, especially regarding their evaluation. To date, there are no validated instruments to measure empathy in artificial agents and most studies in this area use measures created or adapted for each specific case. Validated measures are essential to generate reliable data on what it’s intended to measure. The main goal of this study is to propose a valid assessment instrument that can be applied to both artificial agents and human beings. The proposed instrument assesses the empathy perceived by a third person, after observing the interaction, and was built in Portuguese, having been based on the Interpersonal Reactivity Index from Davis, the Toronto Empathy Questionnaire and on non-validated measures applied in studies on empathic artificial agents. The instrument was applied through the Qualtrics platform, and all the data was collected via internet. The interactions were presented in four subtitled videos, 3 in which artificial agents (the chatbot Wysa, the virtual character Autotutor and a NAO robot) interact with human beings and 1 in which two human beings interact with each other. Participants were invited to participate voluntarily in the research, via email and social networks. The Wysa chatbot was evaluated by 95 people, the Autotutor by 96, the NAO robot by 100, and the human being by 99. All participants declared to be 18 years old or more and to be fluent in the Portuguese language, being 132 Brazilians, 50 Portuguese and one Argentine. Among the participants, 103 declared themselves to be female and 73, male. The final version of the instrument has eight items, which reflect cognitive, affective and behavioural components of empathy, and are consonant with the definition of empathy proposed by Hoffman (1985). The factor analysis pointed to a single factor and Cronbach's alpha coefficients were all above 0.8, indicating that the instrument proved to be valid and reliable. Except for the Autotutor, all agents, including the human being, were well evaluated as empathetic.
Libri sul tema "Artificial empathy":
1
Lu, Shasha, Yinghui Zhou, Li Xiao, Min Ding e Hye-Jin Kim. Audio and Visual Analytics in Marketing and Artificial Empathy. Now Publishers, 2022.
2
Rust, Roland T., e Ming-Hui Huang. Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy. Springer International Publishing AG, 2021.
3
McStay, Andrew. Emotional AI: The Rise of Empathic Media. SAGE Publications, Limited, 2017.
4
Evans, Dylan. Emotion: A Very Short Introduction. Oxford University Press, 2019. http://dx.doi.org/10.1093/actrade/9780198834403.001.0001.
Abstract (sommario):
Was love invented by European poets in the Middle Ages or is it part of human nature? Will winning the lottery really make you happy? Is it possible to build robots that have feelings? Emotion: A Very Short Introduction explores the latest thinking about emotions, drawing on a wide range of scientific research, from anthropology and psychology to neuroscience and artificial intelligence. It discusses the evolution of emotions and their biological basis, the science of happiness, and the role that emotions play in memory and decision-making. This new edition has been updated to incorporate new developments in our understanding of emotions, including the neural basis of empathy and the emotional impact of films.
5
McStay, Andrew. Emotional AI: The Rise of Empathic Media. SAGE Publications, Limited, 2018.
6
Maitra, Keya, e Jennifer McWeeny, a cura di. Feminist Philosophy of Mind. Oxford University PressNew York, 2022. http://dx.doi.org/10.1093/oso/9780190867614.001.0001.
Abstract (sommario):
Abstract This collection is the first book to focus on the emerging field of study called feminist philosophy of mind. Each of the twenty chapters of Feminist Philosophy of Mind employs theories and methodologies from feminist philosophy to offer fresh insights into issues raised in the contemporary literature in philosophy of mind and/or uses those from the philosophy of mind to advance feminist theory. The book delineates the content and aims of the field and demonstrates the fecundity of its approach, which is centered on the collective consideration of three questions: What is the mind? Whose mind is the model for the theory? To whom is mind attributed? Topics considered with this lens include mental content, artificial intelligence, the first-person perspective, personal identity, other minds, mental attribution, mental illness, perception, memory, attention, desire, trauma, agency, empathy, grief, love, gender, race, sexual orientation, materialism, panpsychism, and enactivism. In addition to engaging analytic and feminist philosophical traditions, chapters draw from resources in phenomenology, philosophy of race, decolonial studies, disability studies, embodied cognition theory, comparative philosophy, neuroscience, and psychology.
Capitoli di libri sul tema "Artificial empathy":
1
Asada, Minoru. "Artificial Empathy". In Diversity in Harmony - Insights from Psychology, 19–41. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119362081.ch2.
2
Masliković, Dejan, e Đurađ Grubišić. "Digital Empathy". In Applied Artificial Intelligence 2: Medicine, Biology, Chemistry, Financial, Games, Engineering, 190–93. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60840-7_23.
3
Bryant, Peter T. "Cognitive Empathy". In Augmented Humanity, 139–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76445-6_5.
Abstract (sommario):
AbstractHuman beings try to interpret and read other minds. This is the process of cognitive empathizing, which can be implicit and intuitive, or explicit and deliberate. The process also qualifies as a form of complex problem-solving, where the focal problem is another person’s mental states. Hence, cognitive empathizing by digitally augmented agents will exhibit the characteristics discussed in the preceding chapter, regarding digitalized problem-solving. It follows, therefore, that augmented agents might combine human myopia and bias, with overly farsighted, artificial sampling and search of other minds. Augmented agents will then misread other minds, often viewing them as unrealistic, irrational, or deviant. This chapter examines the origins and implications of these effects, especially for interpersonal trust and cooperation.
4
Kolonin, Anton. "Resource-Constrained Social Evidence Based Cognitive Model for Empathy-Driven Artificial Intelligence". In Artificial General Intelligence, 100–108. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97676-1_10.
5
Boukricha, Hana, Ipke Wachsmuth, Maria Nella Carminati e Pia Knoeferle. "Empathy and Its Modulation in a Virtual Human". In KI 2013: Advances in Artificial Intelligence, 25–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40942-4_3.
6
Neroznikova, Yulia M., e Alexander V. Vartanov. "Reflection Mechanisms of Empathy Processes in Evoked Potentials". In Brain-Inspired Cognitive Architectures for Artificial Intelligence: BICA*AI 2020, 342–49. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65596-9_41.
7
Vargas Martin, Miguel, Eduardo Pérez Valle e Sheri Horsburgh. "Artificial Empathy for Clinical Companion Robots with Privacy-By-Design". In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 351–61. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70569-5_23.
8
Didenko, Valeriy D., Sergey G. Afanasiev e Nikita A. Shcherbakov. "Secrets of the Empathy of Artificial Intelligence and Digital Economy. Philosophical and Cultural Aspects". In Studies in Systems, Decision and Control, 145–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56433-9_17.
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Gierer, Alfred. "Evolution of Empathy as a Source of Human Altruism". In Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3, 1036–45. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0870-9_65.
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Gama, Sandra, Gabriel Barata, Daniel Gonçalves, Rui Prada e Ana Paiva. "SARA: Social Affective Relational Agent: A Study on the Role of Empathy in Artificial Social Agents". In Affective Computing and Intelligent Interaction, 507–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24600-5_54.
Atti di convegni sul tema "Artificial empathy":
1
Sharma, Ashish, Inna W. Lin, Adam S. Miner, Dave C. Atkins e Tim Althoff. "Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach (Extended Abstract)". In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/747.
Abstract (sommario):
Online peer-to-peer support platforms enable conversations between millions of people who seek and provide mental health support. If successful, web-based mental health conversations could improve access to treatment and reduce the global disease burden. Psychologists have repeatedly demonstrated that empathy, the ability to understand and feel the emotions and experiences of others, is a key component leading to positive outcomes in supportive conversations. However, recent studies have shown that highly empathic conversations are rare in online mental health platforms. In this paper, we work towards improving empathy in online mental health support conversations. We introduce a new task of empathic rewriting which aims to transform low-empathy conversational posts to higher empathy. Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context. Here we propose Partner, a deep reinforcement learning (RL) agent that learns to make sentence-level edits to posts in order to increase the expressed level of empathy while maintaining conversation quality. Our RL agent leverages a policy network, based on a transformer language model adapted from GPT-2, which performs the dual task of generating candidate empathic sentences and adding those sentences at appropriate positions. Through a combination of automatic and human evaluation, we demonstrate that Partner successfully generates more empathic, specific, and diverse responses and outperforms NLP methods from related tasks such as style transfer and empathic dialogue generation.
2
Yalcin, Ozge Nilay. "Evaluating Empathy in Artificial Agents". In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE, 2019. http://dx.doi.org/10.1109/acii.2019.8925498.
3
Hall, Theodore. "Artificial Gravity Visualization, Empathy, and Design". In Space 2006. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-7321.
4
Zhu, Qihao, e Jianxi Luo. "Toward Artificial Empathy for Human-Centered Design: A Framework". In ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/detc2023-117266.
Abstract (sommario):
Abstract In the early stages of the design process, designers explore opportunities by discovering unmet needs and developing innovative concepts as potential solutions. From a human-centered design perspective, designers must develop empathy with people to truly understand their needs. However, developing empathy is a complex and subjective process that relies heavily on the designer’s empathetic capability. Therefore, the development of empathetic understanding is intuitive, and the discovery of underlying needs is often serendipitous. This paper aims to provide insights from artificial intelligence research to indicate the future direction of AI-driven human-centered design, taking into account the essential role of empathy. Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user studies, empathetic understanding development, and artificial empathy. Based on this foundation, we discuss the role that artificial empathy can play in human-centered design and propose an artificial empathy framework for human-centered design. Building on the mechanisms behind empathy and insights from empathetic design research, the framework aims to break down the rather complex and subjective concept of empathy into components and modules that can potentially be modeled computationally. Furthermore, we discuss the expected benefits of developing such systems and identify current research gaps to encourage future research efforts.
5
Matsumura, Tadayuki, Kanako Esaki e Hiroyuki Mizuno. "Empathic Active Inference: Active Inference with Empathy Mechanism for Socially Behaved Artificial Agent". In The 2022 Conference on Artificial Life. Cambridge, MA: MIT Press, 2022. http://dx.doi.org/10.1162/isal_a_00496.
6
Siqueiros, Jesús M. "You, Robot: Empathy in a Hybrid World". In The 2021 Conference on Artificial Life. Cambridge, MA: MIT Press, 2021. http://dx.doi.org/10.1162/isal_a_00391.
7
Polajnar, Jernej, Behrooz Dalvandi e Desanka Polajnar. "Does empathy between artificial agents improve agent teamwork?" In Cognitive Computing (ICCI-CC). IEEE, 2011. http://dx.doi.org/10.1109/coginf.2011.6016126.
8
Matsumura, Tadayuki, Kanako Esaki, Shunsuke Minusa, Yang Shao, Chihiro Yoshimura e Hiroyuki Mizuno. "Social Emotional Valence for Regulating Empathy in Active Inference". In The 2023 Conference on Artificial Life. MIT Press, 2023. http://dx.doi.org/10.1162/isal_a_00573.
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Priya, Priyanshu, Kshitij Mishra, Palak Totala e Asif Ekbal. "PARTNER: A Persuasive Mental Health and Legal Counselling Dialogue System for Women and Children Crime Victims". In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/686.
Abstract (sommario):
The World Health Organization has underlined the significance of expediting the preventive measures for crime against women and children to attain the United Nations Sustainable Development Goals 2030 (promoting well-being, gender equality, and equal access to justice). The crime victims typically need mental health and legal counselling support for their ultimate well-being and sometimes they need to be persuaded to seek desired support. Further, counselling interactions should adopt correct politeness and empathy strategies so that a warm, amicable, and respectful environment can be built to better understand the victims’ situations. To this end, we propose PARTNER, a Politeness and empAthy strategies-adaptive peRsuasive dialogue sysTem for meNtal health and LEgal counselling of cRime victims. For this, first, we create a novel mental HEalth and legAl counseLling conversational dataset HEAL, annotated with three distinct aspects, viz. counselling act, politeness strategy, and empathy strategy. Then, by formulating a novel reward function, we train a counselling dialogue system in a reinforcement learning setting to ensure correct counselling act, politeness strategy, and empathy strategy in the generated responses. Extensive empirical analysis and experimental results show that the proposed reward function ensures persuasive counselling responses with correct polite and empathetic tone in the generated responses. Further, PARTNER proves its efficacy to engage the victim by generating diverse and natural responses.
10
James, Jesin, Catherine Inez Watson e Bruce MacDonald. "Artificial Empathy in Social Robots: An analysis of Emotions in Speech". In 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 2018. http://dx.doi.org/10.1109/roman.2018.8525652.
Rapporti di organizzazioni sul tema "Artificial empathy":
1
Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, febbraio 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.
Abstract (sommario):
The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.