A Typology of Non-functional Information

Davide Secchi*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This study takes the interaction between human beings and intelligent systems from a rather basic perspective, that of the exchanged information. Interactions with artificial intelligence (AI) systems is usually studied from the perspective of the fact that they provide information that is apt to the task at hand, that is operational in the sense that it supports the undergoing activity. The practice of the interaction is rather different in that information may result ambiguous, difficult to understand, or completely irrelevant. This paper proposes a typology of non-functional information, by classifying it in: (a) dysfunctional, that is information that is detrimental to the task at hand; (b) pseudo-functional, that is seemingly useful but its use is unclear; and (c) irrelevant information, that is of no use. These three categories are confronted with information that is perceived and is actually functional, i.e. useful for the goal it is supposed to serve. In an attempt to explore the workings of these information types, I use a systemic e-cognition (SEC) approach. This allows to change the discourse on information such that it becomes tied to the cognitive interactive system rather than objectively and neutrally defined. The proposed typology is then put to the test by using an agent-based computational simulation model (ABM) where teams gather information from tools—intended as AI systems—as to perform a task. Results show that all the three types of information are related to task performance. This is somehow surprising given that non-functional information has been traditionally discarded as non-existent to the task at hand. Instead, the simulation shows that, from an organizational or systemic perspective, even non-functionally-related interactions serve to “prepare” the tool to further interaction and eventual performance.

Original languageEnglish
Title of host publicationInternational Conference on Human-Computer Interaction : HCI International 2020 – Late Breaking Papers: Cognition, Learning and Games
EditorsConstantine Stephanidis, Don Harris, Wen-Chin Li, Dylan D. Schmorrow, Cali M. Fidopiastis, Panayiotis Zaphiris, Andri Ioannou, Andri Ioannou, Xiaowen Fang, Robert A. Sottilare, Jessica Schwarz
PublisherSpringer
Publication date2020
Pages240-254
ISBN (Print)9783030601270
DOIs
Publication statusPublished - 2020
Event22nd International Conference on Human-Computer Interaction,HCII 2020 - Copenhagen, Denmark
Duration: 19. Jul 202024. Jul 2020

Conference

Conference22nd International Conference on Human-Computer Interaction,HCII 2020
CountryDenmark
CityCopenhagen
Period19/07/202024/07/2020
SeriesLecture Notes in Computer Science
Volume12425
ISSN0302-9743

Keywords

  • Agent-based modeling
  • Information
  • Typology of information

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