EconPapers    
Economics at your fingertips  
 

Introduction

Constantinos K. Coursaris (), Joerg Beringer (), Pierre-Majorique Léger () and Burak Öz ()
Additional contact information
Constantinos K. Coursaris: HEC Montreal
Joerg Beringer: ProContext
Pierre-Majorique Léger: HEC Montreal
Burak Öz: HEC Montreal

A chapter in The Design of Human-Centered Artificial Intelligence for the Workplace, 2025, pp 1-7 from Springer

Abstract: Abstract The rapid advancement and adoption of AI technologies, including large language models (LLMs) and chatbots, marks a new era in workplace and enterprise support by enabling the generation of human-like artifacts. Through a broad range of machine learning (ML) algorithms and deep neural networks, AI enables mission-critical functions such as pattern recognition, decision-making, and automation. To navigate this exciting albeit complex technological landscape, we introduce a human-centered AI (HCAI) solution map, which classifies AI solutions according to two dimensions: human-centered AI purpose, i.e., whether the AI solution is primarily intended to assist, augment, automate, or replace the human expert, and human-centered AI cognition, i.e., the type of cognitive function support such as sensing, decision-making, and action execution. Moreover, the HCAI solution map organizes AI solutions into roles ranging from assistants and tools to orchestration agents and automation agents. These roles vary in the way they support users and reflect different levels of human involvement during the process (i.e., in-the-loop, on-the-loop, or out-of-the-loop). Designing AI systems with human-centered qualities such as empathy, transparency, and explainability fosters positive user experience and trust. Characteristics such as context awareness, human-centeredness, and human-control, in turn, determine the effectiveness of AI solutions in adapting to situational needs and corresponding user interactions. Ultimately, by considering these human-centered dimensions, characteristics, and qualities when designing AI solutions, organizations can align the AI solution with the intended users’ needs and empower users and maintain human control while creating value for all stakeholders.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-83512-4_1

Ordering information: This item can be ordered from
http://www.springer.com/9783031835124

DOI: 10.1007/978-3-031-83512-4_1

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-07-11
Handle: RePEc:spr:prochp:978-3-031-83512-4_1