Bias and Bias Remediation in Creative Problem-Solving: Managing Biases through Forecasting

Todd, E. Michelle; Higgs, Cory; Mumford, Michael D.

doi:10.1080/10400419.2018.1532268

Cited by 17 publications

(11 citation statements)

References 69 publications

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“…Rather, people move back and forth between the actions taken, often for reasons yet unknown (Mumford et al, 2012). Interestingly, forecasting, the deliberate anticipation of potential consequences of the implementation of an idea, is studied as a technique aimed to support the execution of the creative process (McIntosh et al, 2019; Todd et al, 2019). Specifically, forecasting has been studied as a technique to support idea evaluation, where forecasting the consequences of implementing ideas is used to gather information in order to make decisions about what ideas can be implemented, should be revised, or not pursued at all (Bruijninckx and de Rooij, unpublished).…”

Section: Introductionmentioning

confidence: 99%

The Predictive Creative Mind: A First Look at Spontaneous Predictions and Evaluations During Idea Generation

Valtulina

Rooij

2019

Front. Psychol.

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Idea generation, the process of creating and developing candidate solutions that when implemented can solve ill-defined and complex problems, plays a pivotal role in creativity and innovation. The algorithms that underlie classical evolutionary, cognitive, and process models of idea generation, however, appear too inefficient to effectively help solve the ill-defined and complex problems for which one would engage in idea generation. To address this, these classical models have recently been redesigned as forward models, drawing heavily on the “predictive mind” literature. These pose that more efficiency can be achieved by making predictions based on heuristics, previous experiences, and domain knowledge about what material to use to generate ideas with, and evaluate these subsequently generated ideas based on whether they indeed match the initial prediction. When a discrepancy occurs between prediction and evaluation, new predictions are made, and thus shaping what actions, and how these actions, are undertaken. Although promising, forward models of idea generation remain theoretical and thus no empirical evidence exists about whether such predictions and evaluations indeed form part of the idea generation process. To take a first empirical look at this, a mixed-methods study was conducted by analyzing people’s self-reports for the reasons of the actions that they take during an idea generation task. The results showed that predictions and evaluations are pervasive in the idea generation process. Specifically, switching between concept selection and conceptual combination and idea generation, as well as repeating idea generation based on earlier selected conceptual combination, and possibly (but to a lesser extent) concept selection and the repetition thereof, are likely to be driven by predictions and evaluations. Moreover, the frequencies of the predictions and evaluations that drive these actions influenced the amount of ideas generated, amount of concepts used, and within-concept fluency (the ratio of the amount of ideas generated per concept used). Therefore, the contribution of this paper is the first empirical evidence that indicates that the idea generation process is driven by both predictions and evaluations.

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Section: Introductionmentioning

confidence: 99%

The Predictive Creative Mind: A First Look at Spontaneous Predictions and Evaluations During Idea Generation

Valtulina

Rooij

2019

Front. Psychol.

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“…As such, it may be as important to study factors that bias creativity as it is to study creativity 5 . An understanding of factors that bias creativity can lead to remediation of such factors, therefore contributing to improvements in peoples' ability to solve problems 6 .…”

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confidence: 99%

Subjective semantic surprise resulting from divided attention biases evaluations of an idea’s creativity

Calic

Shamy

Kinley

et al. 2020

Sci Rep

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the evaluation of an idea's creativity constitutes an important step in successfully responding to an unexpected problem with a new solution. Yet, distractions compete for cognitive resources with the evaluation process and may change how individuals evaluate ideas. in this paper, we investigate whether attentional demands from these distractions bias creativity evaluations. this question is examined using 1,065 creativity evaluations of 15 alternative uses of everyday objects by 71 study participants. participants in the distraction group (treatment) rated the alternative uses as more creative on the novelty dimension, but not the usefulness dimension, than did participants in the baseline group (control). psychophysiological measurements-event-related and spectral eeG and pupillometry-confirm attentional resources in the Treatment group are being diverted to a distractor task and that the Control group expended significantly more cognitive resources on the evaluation of the alternative uses. these data show direct physiological evidence that distractor tasks draw cognitive resources from creative evaluation and that such distractions will bias judgements of creativity.We rely on behavioral methods, that is creativity evaluations of alternative uses (AUs), to test the broad hypothesis that distractions bias creativity evaluations. We leverage psychophysiological methods such as pupillometry and event-related (ERP) and spectral electroencephalography (EEG) to verify that distracted individuals are expending less cognitive resources on the evaluation task. The three methods are complimentary. Established pupillometry, EEG oscillations, and ERP components (e.g., alpha band desynchronization, P300) provide reliable and robust real-time measures of attention and cognitive load 13,14 that is not susceptible to retrospective and subjectivity biases 15 . Multi-method experiments provide support for the existence of a bias. Biases in creativitySelecting among alternative ideas is a fundamental challenge for individuals in a number of different organizational settings 16,17 . To this end, people devote a great deal of time and effort to evaluating ideas. Sevens and Burley 18 find that, on average, managers evaluate more than 3,000 raw ideas to identify one that is commercially successful. The challenge of idea evaluation has only grown with the increase of ideation maximization training, platform-based contests, big data, and crowdfunding as a means of generating a large number of ideas [19][20][21] . The challenge faced by decision-makers is often to select the most creative idea from a myriad of competing alternatives and to reduce biases that may have a detrimental effect on this process 22 .In social sciences, mathematics, and engineering, biases refer to systematic errors impacting performance 23 . Prior research has identified a number of decision-making errors in relatively simple decision-making tasks 24,25 . Research has also examined biases present in creativity 6,26 . Broadly, this research has examined biases ...

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“…Finally, other studies focused on changing participants' cognitive processing to influence creativity, for example, by prompting fast processing speed (Forthmann et al, 2020), comparing forced and spontaneous memorisation processes (Kurashige et al, 2019), or training participants to improve their forecasting skills (Todd et al, 2019).…”

Section: Topos: Contextual and Environmental Influences On Creative B...mentioning

confidence: 99%

“…Not surprisingly perhaps, we also noted that none of the reports that focussed on contextual or environmental influences examined the situational context within which the creative process took place. Apart from one remote study using MTurk participants (Taylor, 2021) and one study presumably testing participants in a classroom context (Bonnardel & Didier, 2020), most studies took place in laboratories on university campuses, with participants completing computer-based tasks (Forthmann et al, 2020;George & Wiley, 2020;George et al, 2021;Kurashige et al, 2019;Wu et al, 2019;Yu, 2020) or paper-andpencil tasks (Akben & Coskun, 2019;Steindorf et al, 2020;Todd et al, 2019;Yu, 2020;Zuo et al, 2019). In most cases, in was unclear whether participants completed the creativity tasks in isolation or alongside others (Akben & Coskun, 2019;George & Wiley, 2020;Kurashige et al, 2019;George et al, 2021;Steindorf et al, 2020;Taylor, 2021;Wu et al, 2019;Yu, 2020).…”

Section: Topos: Contextual and Environmental Influences On Creative B...mentioning

confidence: 99%

Individual innovation and creativity: An interdisciplinary mapping of creative cognition

Vallée-Tourangeau¹,

Sakellariou²,

Szigetvari³

2022

Preprint

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This chapter presents an interdisciplinary scoping review examining overlaps and differences in the way innovation and creativity is conceived and studied in the respective fields of innovation management and human experimental psychology research. The review mapped selected studies against five pre-existing higher-order categories of creative behaviour antecedents. Notably, we found that user innovation research characterises and seeks out individual creativity as a self-initiated, deliberate, and independent endeavour in personal contexts. Experimental psychology research, by contrast, often studies creativity using activities that are initiated by the experimenters rather than the participants in laboratory contexts.

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Bias and Bias Remediation in Creative Problem-Solving: Managing Biases through Forecasting

Cited by 17 publications

References 69 publications

The Predictive Creative Mind: A First Look at Spontaneous Predictions and Evaluations During Idea Generation

The Predictive Creative Mind: A First Look at Spontaneous Predictions and Evaluations During Idea Generation

Subjective semantic surprise resulting from divided attention biases evaluations of an idea’s creativity

Individual innovation and creativity: An interdisciplinary mapping of creative cognition

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