You’re Not the Boss of me, Algorithm: Increased User Control and Positive Implicit Attitudes Are Related to Greater Adherence to an Algorithmic Aid

Author:

Morrison Ben W1ORCID,Kelson Joshua N2,Morrison Natalie M V3,Innes J Michael4,Zelic Gregory5,Al-Saggaf Yeslam1,Paul Manoranjan1

Affiliation:

1. Macquarie University Faculty of Medicine, Health and Human Sciences, School of Psychological Sciences, , Balaclava Rd, Macquarie Park NSW 2109

2. Charles Sturt University Faculty of Business, Justice and Behavioural Sciences, School of Psychology, , Panorama Ave, Bathurst NSW 279

3. Western Sydney University School of Medicine, , Narellan Road &, Gilchrist Dr, Campbelltown NSW 2560

4. University of South Australia Justice and Society, , North Terrace, Adelaide SA 5000

5. Centre for Work Health and Safety , Donnison Street, Gosford NSW 2250

Abstract

Abstract This study examined whether participants’ adherence to an algorithmic aid was related to the degree of control they were provided at decision point and their attitudes toward new technologies and algorithms. It also tested the influence of control on participants’ subjective reports of task demands whilst using the aid. A total of 159 participants completed an online experiment centred on a simulated forecasting task, which required participants to predict the performance of school students on a standardized mathematics test. For each student, participants also received an algorithm-generated forecast of their score. Participants were randomly assigned to either the ‘full control’ (adjust forecast as much as they wish), ‘moderate control’ (adjust forecast by 30%) or ‘restricted control’ (adjust forecast by 2%) group. Participants then completed an assessment of subjective task load, a measure of their explicit attitudes toward new technologies, demographic and experience items (age, gender and computer literacy) and a novel version of the Go/No-Go Association Task, which tested their implicit attitudes toward algorithms. The results revealed that participants who were provided with more control over the final forecast tended to deviate from it more greatly and reported lower levels of frustration. Furthermore, participants showing more positive implicit attitudes toward algorithms were found to deviate less from the algorithm’s forecasts, irrespective of the degree of control they were given. The findings allude to the importance of users’ control and preexisting attitudes in their acceptance of, and frustration in using a novel algorithmic aid, which may ultimately contribute to their intention to use them in the workplace. These findings can guide system developers and support workplaces implementing expert system technology.

Publisher

Oxford University Press (OUP)

Subject

Human-Computer Interaction,Software,Library and Information Sciences

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