SIG AIAA at AMCIS 2023
Track Chairs
Antino Kim, Indiana University, antino@indiana.edu
Alan Dennis, Indiana University, ardennis@indiana.edu
Track Description
The Artificial Intelligence and Autonomous Applications track features research on a wide range of topics related to artificial intelligence (AI) and machine learning (ML) algorithms, including novel applications of algorithms (e.g., recommendation systems, information security analytics, healthcare, etc.), emerging types of AI agents (e.g., conversational agents, digital humans, etc.), and socio-economic aspects of AI and algorithms (e.g., ethical AI, biases in data and algorithms, impact on jobs, regulations, etc.). The track welcomes all research methods, including design science, behavioral, and economics.
Minitracks:
AI Agents
As technology advances in recent years, AI agents have been transforming the way we work, live, play, and learn. We are proposing this minitrack to bridge academic research with practitioner concerns to create synergy in promoting the creation and usage of AI agents. The focus of this mini-track is the design, adoption, and application of AI agents as well as the symbiotic relationships between AI agents and humans. AI agents in this context is a general term, which includes conversational AI agents (i.e. chatbots), voice agents (e.g. Amazon Alexa, Siri), digital human agents, and robotics. We want to emphasize the importance of investigating the behavioral and perception outcomes, uncovering the complicated interactive nature of the technology, the end user, the tasks, as well as the organizational environment, and opening the black box of the underlying cognitive processes undertaken by the end-user while interacting with AI agents.
Lingyao Yuan, Iowa State University, lyuan@iastate.edu
Vibhanshu Abhishek, University of California – Irvine, vibs@uci.edu
Human – Conversational Agent Interaction
Conversational agents (CAs) that use natural language to interact with humans are becoming ubiquitous in our daily lives. They are utilized in a number of contexts, such as for customer service or as personal assistants. CAs take on different designs, forms of embodiment, and communication modes. Despite their popularity, many CAs are unable to achieve their objectives and to create positive user experiences. The minitrack aims to improve understanding of how CAs can be designed to fulfil their intended purpose, and interact harmoniously with humans. The scope is to discuss and disseminate state-of-the-art research pertaining to interactions between humans and CAs, across application areas and research paradigms.
Topics include, but are not limited to:
- User characteristics and adaptive CA designs
- CAs for individuals and groups
- Impacts of CA embodiment
- Character and personality design
- Agents for different domains
- Ethical implications of CA design and interaction
Atreyi Kankanhalli, National University of Singapore, atreyi@comp.nus.edu.sg
Fiona Nah, City University of Hong Kong, fuihnah@cityu.edu.hk
Langtao Chen, Missouri University of Science and Technology, chenla@mst.edu
Revolutionizing the Design of AI Models for Real Impact
Despite the rapid advancement of AI, integrating AI models with business processes remains one of the most challenging tasks in the current world of Information Technology. Various industry partners (e.g., Gartner’s) reported that 80% to 90% of AI projects ended up with PowerPoint slides and never made it into production. Such failures may be attributable to the fact that AI models are not tailored to the problem or integrated with the processes and technologies of the production environment. Hence, IS researchers need to study the design and impact of AI models to create substantive value for organizations and societies. The new and exciting research topics would significantly extend our current theories, methodologies, and empirical insights that bring AI models closer to business and societal problems. We welcome submissions from a breadth of research paradigms, including behavioral, economics, design science, and data science.
Jingjing Li, University of Virginia, jl9rf@comm.virginia.edu
Reza Mousavi, University of Virginia, mousavi@virginia.edu
Conversational AI Agents and Future of Work
Many artificially intelligent agents (e.g., chatbots, voice assistants) are being integrated into teams, organizations, and everyday work. So far, humans have used these intelligent agents for simple, practical tasks to automate rudimentary tasks, for example. However, such systems are constantly evolving to take on tasks with greater organizational relevance. While intelligent agents represent a potential solution in this regard, it is unclear how humans will interact and collaborate with them.
This minitrack welcomes contributions from design science, empirical, action or case-study research that provide insights on how people interact, collaborate and behave in scenarios of joint value creation with artificial intelligent agents.
Edona Elshan, Institute of Information Management, edona.elshan@unisg.ch
Dominik Siemon, LUT University, dominik.siemon@lut.fi