Electronic Resource

Article - When AI-Based Agents Are Proactive: Implications for Competence and System Satisfaction in Human–AI Collaboration Volume 66, Issue 4, Halaman 445–464

---

As the capabilities of artificial intelligence (AI)

technologies continue to improve, collaboration with AI-
based agents enables users to be more efficient and pro-
ductive. Not only has the quality of AI-based agents’ out-
comes increased, but they can now help proactively, and

even take over entire work tasks. However, users need to be
satisfied with the system to remain motivated to collaborate

and engage with AI-based agents. Drawing on self-deter-
mination theory, a vignette-based online experiment was

conducted that revealed that proactive (vs. reactive) help

from AI-based agents leads to a higher loss of users’ com-
petence-based self-esteem and thus reduces users’ system

satisfaction. This effect is moderated by the users’ knowl-
edge of AI. Higher (vs. lower) levels of AI knowledge cause

a greater loss of competence-based self-esteem through
proactive (vs. reactive) help. The findings contribute to a
better understanding of help from AI-based agents and
provide important implications for managers and designers
who seek to enhance human–AI collaboration.

---

Ketersediaan

Informasi Detail

Judul Seri

-

No. Panggil

006.3 DIE w

Penerbit

: Springer Fachmedien Wiesbaden GmbH., 2024

Deskripsi Fisik

-

Bahasa

English

ISBN/ISSN

1867-0202

Klasifikasi

006.3 DIE w

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

Volume 66, Issue 4, Halaman 445–464

Subjek

-

Info Detail Spesifik

-

Pernyataan Tanggungjawab

-

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar