The Future of Research in an Artificial Intelligence-Driven World

被引：8

作者：

Kulkarni, Mukta ^{[1
]}

Mantere, Saku ^{[2
]}

Vaara, Eero ^{[3
]}

van den Broek, Elmira ^{[4
]}

Pachidi, Stella ^{[5
]}

Glaser, Vern L. ^{[6
]}

Gehman, Joel ^{[7
]}

Petriglieri, Gianpiero ^{[8
]}

Lindebaum, Dirk ^{[9
]}

Cameron, Lindsey D. ^{[10
]}

Rahman, Hatim A. ^{[11
]}

Islam, Gazi ^{[9
]}

Greenwood, Michelle ^{[12
]}

机构：

[1] Indian Inst Management Bangalore, Bangalore, India

[2] McGill Univ, Quebec City, PQ, Canada

[3] Univ Oxford, Oxford, England

[4] Stockholm Sch Econ, Dept Econ, Stockholm, Sweden

[5] Univ Cambridge, Cambridge, England

[6] Univ Alberta, Edmonton, AB, Canada

[7] George Washington Univ, Washington, DC USA

[8] INSEAD, Fontainebleau, France

[9] Grenoble Ecole Management, Grenoble, France

[10] Univ Penn, Philadelphia, PA USA

[11] Northwestern Univ, Kellogg Sch Management, Evanston, IL USA

[12] Monash Univ, Melbourne, Vic, Australia

来源：

JOURNAL OF MANAGEMENT INQUIRY | 2024年 / 33卷 / 03期

关键词：

MANAGEMENT; TECHNOLOGY; OPPORTUNITIES; KNOWLEDGE; CHATGPT; AI;

D O I：

10.1177/10564926231219622

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Current and future developments in artificial intelligence (AI) systems have the capacity to revolutionize the research process for better or worse. On the one hand, AI systems can serve as collaborators as they help streamline and conduct our research. On the other hand, such systems can also become our adversaries when they impoverish our ability to learn as theorists, or when they lead us astray through inaccurate, biased, or fake information. No matter which angle is considered, and whether we like it or not, AI systems are here to stay. In this curated discussion, we raise questions about human centrality and agency in the research process, and about the multiple philosophical and practical challenges we are facing now and ones we will face in the future.

引用

页码：207 / 229

页数：23

共 50 条

[21] Towards Establishing Artificial Intelligence-driven Cancer Medicine
Kobayashi, Kazuma
Miyake, Mototaka
Watanabe, Hirokazu
Mihara, Naoki
Hamamoto, Ryuji
CANCER SCIENCE, 2021, 112 : 527 - 527
[22] Advancements in artificial intelligence-driven techniques for interventional cardiology
Rudnicka, Zofia
Pregowska, Agnieszka
Gladys, Kinga
Perkins, Mark
Proniewska, Klaudia
CARDIOLOGY JOURNAL, 2024, 31 (02) : 321 - 341
[23] Artificial intelligence-driven prediction of multiple drug interactions
Chen, Siqi
Li, Tiancheng
Yang, Luna
Zhai, Fei
Jiang, Xiwei
Xiang, Rongwu
Ling, Guixia
BRIEFINGS IN BIOINFORMATICS, 2022, 23 (06)
[24] Artificial Intelligence-Driven Wireless Sensing for Health Management
Toruner, Merih Deniz
Shi, Victoria
Sollee, John
Hsu, Wen-Chi
Yu, Guangdi
Dai, Yu-Wei
Merlo, Christian
Suresh, Karthik
Jiao, Zhicheng
Wang, Xuyu
Mao, Shiwen
Bai, Harrison
BIOENGINEERING-BASEL, 2025, 12 (03):
[25] Artificial intelligence-driven design of ß-secretase 1 inhibitors
Njirjak, Marko
Kalafatovic, Daniela
Mausa, Goran
JOURNAL OF PEPTIDE SCIENCE, 2024, 30
[26] Artificial Intelligence-Driven Eye Disease Classification Model
Sait, Abdul Rahaman Wahab
APPLIED SCIENCES-BASEL, 2023, 13 (20):
[27] The ethical challenges of artificial intelligence-driven digital pathology
McKay, Francis
Williams, Bethany J.
Prestwich, Graham
Bansal, Daljeet
Hallowell, Nina
Treanor, Darren
JOURNAL OF PATHOLOGY CLINICAL RESEARCH, 2022, 8 (03): : 209 - 216
[28] The ethics of artificial intelligence-driven diagnostic testing in dermatology
Muzumdar, Sonal
Grant-Kels, Jane M.
JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY, 2024, 91 (06) : 1307 - 1308
[29] Artificial intelligence-driven disruption in science production ahead
de Miguel, Sergio
SILVA FENNICA, 2023, 57 (01)
[30] Artificial Intelligence-Driven Genetic Algorithm Optimization for Language Learning and Assessment in Medical Research
Yu D.
Xu T.
Computer-Aided Design and Applications, 2024, 21 (S24): : 89 - 104

← 1 2 3 4 5 →