Algorithmic Agency in Information Systems: Research Opportunities for Data Analytics of Digital Traces

Jonas Valbjørn Andersen; Aron Lindberg; Rikard Lindgren; Lisen Selander

doi:10.1109/HICSS.2016.571

Algorithmic Agency in Information Systems: Research Opportunities for Data Analytics of Digital Traces

Jonas Valbjørn Andersen, Aron Lindberg, Rikard Lindgren, Lisen Selander

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

The complex networks of today involve algorithms, humans, machines, and tools. As a consequence of their digital and sociotechnical nature, they increasingly exhibit autonomous and intelligent characteristics. This development puts prevailing assumptions about information systems at stake. In this paper, we specifically engage with a radical reframing of past conceptualizations of machine intelligence or agency. Based on our theorizing, we advance and substantiate a novel algorithmic agency perspective that centers around three key characteristics: algorithmic interpretation, data generativity, and input translation. These characteristics pave the way for a new wave of research in information systems. Our proposed research opportunities for data analytics of digital traces address conditions for, features of, and approaches to algorithmic agency.

Original language	English
Title of host publication	Proceedings of the 49th Annual Hawaii International Conference on System Sciences
Publisher	IEEE
Publication date	2016
Pages	4597 - 4605
ISBN (Electronic)	978-0-7695-5670-3
DOIs	https://doi.org/10.1109/HICSS.2016.571
Publication status	Published - 2016
Externally published	Yes

Access to Document

10.1109/HICSS.2016.571

Cite this

@inproceedings{0fb7ad2c941d4528abe9678f761473fe,

title = "Algorithmic Agency in Information Systems: Research Opportunities for Data Analytics of Digital Traces",

abstract = "The complex networks of today involve algorithms, humans, machines, and tools. As a consequence of their digital and sociotechnical nature, they increasingly exhibit autonomous and intelligent characteristics. This development puts prevailing assumptions about information systems at stake. In this paper, we specifically engage with a radical reframing of past conceptualizations of machine intelligence or agency. Based on our theorizing, we advance and substantiate a novel algorithmic agency perspective that centers around three key characteristics: algorithmic interpretation, data generativity, and input translation. These characteristics pave the way for a new wave of research in information systems. Our proposed research opportunities for data analytics of digital traces address conditions for, features of, and approaches to algorithmic agency. ",

author = "Andersen, {Jonas Valbj{\o}rn} and Aron Lindberg and Rikard Lindgren and Lisen Selander",

year = "2016",

doi = "10.1109/HICSS.2016.571",

language = "English",

pages = "4597 -- 4605",

booktitle = "Proceedings of the 49th Annual Hawaii International Conference on System Sciences",

publisher = "IEEE",

address = "United States",

}

Algorithmic Agency in Information Systems: Research Opportunities for Data Analytics of Digital Traces. / Andersen, Jonas Valbjørn; Lindberg, Aron; Lindgren, Rikard et al.
Proceedings of the 49th Annual Hawaii International Conference on System Sciences. IEEE, 2016. p. 4597 - 4605.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

TY - GEN

T1 - Algorithmic Agency in Information Systems

T2 - Research Opportunities for Data Analytics of Digital Traces

AU - Andersen, Jonas Valbjørn

AU - Lindberg, Aron

AU - Lindgren, Rikard

AU - Selander , Lisen

PY - 2016

Y1 - 2016

N2 - The complex networks of today involve algorithms, humans, machines, and tools. As a consequence of their digital and sociotechnical nature, they increasingly exhibit autonomous and intelligent characteristics. This development puts prevailing assumptions about information systems at stake. In this paper, we specifically engage with a radical reframing of past conceptualizations of machine intelligence or agency. Based on our theorizing, we advance and substantiate a novel algorithmic agency perspective that centers around three key characteristics: algorithmic interpretation, data generativity, and input translation. These characteristics pave the way for a new wave of research in information systems. Our proposed research opportunities for data analytics of digital traces address conditions for, features of, and approaches to algorithmic agency.

AB - The complex networks of today involve algorithms, humans, machines, and tools. As a consequence of their digital and sociotechnical nature, they increasingly exhibit autonomous and intelligent characteristics. This development puts prevailing assumptions about information systems at stake. In this paper, we specifically engage with a radical reframing of past conceptualizations of machine intelligence or agency. Based on our theorizing, we advance and substantiate a novel algorithmic agency perspective that centers around three key characteristics: algorithmic interpretation, data generativity, and input translation. These characteristics pave the way for a new wave of research in information systems. Our proposed research opportunities for data analytics of digital traces address conditions for, features of, and approaches to algorithmic agency.

UR - http://www.mendeley.com/research/algorithmic-agency-information-systems-research-opportunities-data-analytics-digital-traces

U2 - 10.1109/HICSS.2016.571

DO - 10.1109/HICSS.2016.571

M3 - Article in proceedings

SP - 4597

EP - 4605

BT - Proceedings of the 49th Annual Hawaii International Conference on System Sciences

PB - IEEE

ER -

Algorithmic Agency in Information Systems: Research Opportunities for Data Analytics of Digital Traces

Abstract

Access to Document

Fingerprint

Cite this