Artificial intelligence and communication: A Human–Machine Communication research agenda

Artificial intelligence (AI) and people’s interactions with it—through virtual agents, socialbots, and language-generation software—do not fit neatly into paradigms of communication theory that have long focused on human–human communication. To address this disconnect between communication theory and emerging technology, this article provides a starting point for articulating the differences between communicative AI and previous technologies and introduces a theoretical basis for navigating these conditions in the form of scholarship within human–machine communication (HMC). Drawing on an HMC framework, we outline a research agenda built around three key aspects of communicative AI technologies: (1) the functional dimensions through which people make sense of these devices and applications as communicators, (2) the relational dynamics through which people associate with these technologies and, in turn, relate to themselves and others, and (3) the metaphysical implications called up by blurring ontological boundaries surrounding what constitutes human, machine, and communication.

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A New Research Agenda for Project Management Communication Theory

10.31124/advance.7234031 ◽

2018 ◽

Author(s):

Bill Brantley

Keyword(s):

Project Management ◽

Research Agenda ◽

Communication Complexity ◽

Communication Theory ◽

Communication Research ◽

Management Communication ◽

Complexity Leadership ◽

New Research ◽

Complex Responsive Processes ◽

Complexity Theories

<p>Based on an analysis of 272 peer-reviewed articles on project management communication, the authors found that only four percent of the articles advanced project management communication toward a better contemporary understanding of the complexity of communication. The authors posit that project management communication research needs a new research agenda based on complex responsive processes of relating. The new research agenda proposal comprises three major areas of study: emotional intelligence; communication complexity theories; and complexity leadership. Adopting the new project management communication research agenda will help establish more effective communication tools and methods for project management practitioners while providing new research opportunities for communication scholars.</p>

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A New Research Agenda for Project Management Communication Theory

10.31124/advance.7234031.v1 ◽

2018 ◽

Author(s):

Bill Brantley

Keyword(s):

Project Management ◽

Research Agenda ◽

Communication Complexity ◽

Communication Theory ◽

Communication Research ◽

Management Communication ◽

Complexity Leadership ◽

New Research ◽

Complex Responsive Processes ◽

Complexity Theories

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Make Us Smile! AI and the Violation of Human Intentions

34th Bled eConference Digital Support from Crisis to Progressive Change: Conference Proceedings ◽

10.18690/978-961-286-485-9.5 ◽

2021 ◽

Author(s):

Christof Wolf-Brenner ◽

Keyword(s):

Artificial Intelligence ◽

Research Agenda ◽

Research Topic ◽

Facial Muscles ◽

Starting Point ◽

Future Improvement

In his book Superintelligence, Nick Bostrom points to several ways the development of Artificial Intelligence (AI) might fail, turn out to be malignant or even induce an existential catastrophe. He describes ‘Perverse Instantiations’ (PI) as cases, in which AI figures out how to satisfy some goal through unintended ways. For instance, AI could attempt to paralyze human facial muscles into constant smiles to achieve the goal of making humans smile. According to Bostrom, cases like this ought to be avoided since they include a violation of human designer’s intentions. However, AI finding solutions that its designers have not yet thought of and therefore could also not have intended is arguably one of the main reasons why we are so eager to use it on a variety of problems. In this paper, I aim to show that the concept of PI is quite vague, mostly due to ambiguities surrounding the term ‘intention’. Ultimately, this text aims to serve as a starting point for a further discussion of the research topic, the development of a research agenda and future improvement of the terminology.

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AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations

Journal of Computer-Mediated Communication ◽

10.1093/jcmc/zmz022 ◽

2020 ◽

Vol 25 (1) ◽

pp. 89-100 ◽

Cited By ~ 2

Author(s):

Jeffrey T Hancock ◽

Mor Naaman ◽

Karen Levy

Keyword(s):

Artificial Intelligence ◽

Interpersonal Communication ◽

Research Agenda ◽

Intelligent Agent ◽

Human Communication ◽

Ethical Considerations ◽

Mediated Communication ◽

Ethical Implications ◽

Computer Mediated ◽

Communication Goals

Abstract We define Artificial Intelligence-Mediated Communication (AI-MC) as interpersonal communication in which an intelligent agent operates on behalf of a communicator by modifying, augmenting, or generating messages to accomplish communication goals. The recent advent of AI-MC raises new questions about how technology may shape human communication and requires re-evaluation – and potentially expansion – of many of Computer-Mediated Communication’s (CMC) key theories, frameworks, and findings. A research agenda around AI-MC should consider the design of these technologies and the psychological, linguistic, relational, policy and ethical implications of introducing AI into human–human communication. This article aims to articulate such an agenda.

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When Digital Trace Data Meet Traditional Communication Theory: Theoretical/Methodological Directions

Social Science Computer Review ◽

10.1177/0894439318788618 ◽

2018 ◽

Vol 38 (1) ◽

pp. 91-107 ◽

Cited By ~ 2

Author(s):

Sujin Choi

Keyword(s):

Language Processing ◽

Communication Theory ◽

Longitudinal Change ◽

Communication Research ◽

Human Communication ◽

Power Law Distribution ◽

Trace Data ◽

Automated Content Analysis ◽

Processing Techniques ◽

Social Science Approach

This study suggests one direction of theoretical and methodological coupling of communication research with the digital trace data, utilizing its differences from the traditional social science approach (e.g., sampling vs. population, normal distribution vs. power–law distribution, generalization vs. simulation, deductive vs. inductive, and perceived vs. actual). We propose specific examples of (i) combining communication research with trace data methodologically and theoretically; (ii) collaborating with linguistic psychology complemented with the automated content analysis and natural language processing techniques; and (iii) creating new theoretical inquiries by configuring the granular level of interactivity and underlying dynamics, observing the longitudinal change of interactions, and discovering the neglected presence of outliers and the invisibles. We expect the direction suggested by this study contributes to deepening our understanding of human communication behavior.

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Implementasi Algoritma Dijkstra Pada Game Pacman

CCIT Journal ◽

10.33050/ccit.v12i2.687 ◽

2019 ◽

Vol 12 (2) ◽

pp. 170-176

Author(s):

Anggit Dwi Hartanto ◽

Aji Surya Mandala ◽

Dimas Rio P.L. ◽

Sidiq Aminudin ◽

Andika Yudirianto

Keyword(s):

Artificial Intelligence ◽

Greedy Algorithm ◽

Dijkstra Algorithm ◽

Testing Phase ◽

A Value ◽

Route Problem ◽

Starting Point ◽

The Greedy Algorithm

Pacman is one of the labyrinth-shaped games where this game has used artificial intelligence, artificial intelligence is composed of several algorithms that are inserted in the program and Implementation of the dijkstra algorithm as a method of solving problems that is a minimum route problem on ghost pacman, where ghost plays a role chase player. The dijkstra algorithm uses a principle similar to the greedy algorithm where it starts from the first point and the next point is connected to get to the destination, how to compare numbers starting from the starting point and then see the next node if connected then matches one path with the path). From the results of the testing phase, it was found that the dijkstra algorithm is quite good at solving the minimum route solution to pursue the player, namely by getting a value of 13 according to manual calculations

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A Structure of Moral Theory - A Starting Point for Moral Discussions in the Era of Artificial Intelligence -

CHUL HAK SA SANG - Journal of Philosophical Ideas ◽

10.15750/chss.73.201908.006 ◽

2019 ◽

Vol 73 ◽

pp. 163-195

Author(s):

Kwangsu Mok

Keyword(s):

Artificial Intelligence ◽

Moral Theory ◽

Starting Point

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Autonomous Vehicles in the Mobility System

The Oxford Handbook of Mobile Communication and Society ◽

10.1093/oxfordhb/9780190864385.013.33 ◽

2020 ◽

pp. 500-514

Author(s):

Thilo von Pape

Keyword(s):

Artificial Intelligence ◽

Mobile Phones ◽

Mobile Communication ◽

Autonomous Vehicles ◽

Communication Research ◽

Collective Control ◽

System P ◽

Mobility System ◽

And Control ◽

Transportation Technologies

This chapter discusses how autonomous vehicles (AVs) may interact with our evolving mobility system and what they mean for mobile communication research. It juxtaposes a conceptualization of AVs as manifestations of automation and artificial intelligence with an analysis of our mobility system as a historically grown hybrid of communication and transportation technologies. Since the emergence of railroad and telegraph, this system has evolved on two layers: an underlying infrastructure to power and coordinate the movements of objects, people, and ideas in industrially scaled speeds, volumes, and complexity and an interface to seamlessly access this infrastructure and control it. AVs are poised to further enhance the seamlessness which mobile phones and cars already lent to mobility. But in assuming increasingly sophisticated control tasks, AVs also disrupt an established shift toward individual control, demanding new interfaces to enable higher levels of individual and collective control over the mobility infrastructure.

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Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

Journal of Open Innovation Technology Market and Complexity ◽

10.3390/joitmc7010071 ◽

2021 ◽

Vol 7 (1) ◽

pp. 71

Author(s):

Tan Yigitcanlar ◽

Juan M. Corchado ◽

Rashid Mehmood ◽

Rita Yi Man Li ◽

Karen Mossberger ◽

...

Keyword(s):

Artificial Intelligence ◽

Local Government ◽

Conceptual Framework ◽

Research Agenda ◽

Future Studies ◽

Expert Team ◽

Research Questions ◽

Urban Problems ◽

Technological Opportunities ◽

Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

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