Expert biases in technology foresight. Why they are a problem and how to mitigate them

Bonaccorsi, Andrea; Apreda, Riccardo; Fantoni, Gualtiero

doi:10.1016/j.techfore.2019.119855

Cited by 87 publications

(51 citation statements)

References 243 publications

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“…Effectively stretching people's thinking in this way is a one of the aims of scenario methods, though one that is also recognized as being challenging to achieve in practice (Bonaccorsi et al, 2020; Bryson et al, 2016; Wack & P., 1985). Our scenario building approach aimed to facilitate this with the structuring the 2 × 2 matrix around extreme outcomes for each key driving force to help prompt consideration of more divergent futures outcomes.…”

Section: Discussionmentioning

confidence: 99%

Spatial Simulation of Codesigned Land Cover Change Scenarios in New England: Alternative Futures and Their Consequences for Conservation Priorities

et al. 2020

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Scientists are increasingly engaging with stakeholders to codesign scenarios of land use change necessitating methods to translate the resulting qualitative scenarios into quantitative simulations. We demonstrate a transparent method for translating participatory scenarios to simulations of land use and land cover (LULC) change using the New England Landscape Futures (NELF) project as a case study. The NELF project codesigned four divergent narrative scenarios that contrast with a Recent Trends scenario projecting a continuation of observed changes New England over the past 20 years. Here, we (1) describe the process and utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change model, (2) evaluate scenario LULC configuration relative to the Recent Trends scenario and to each other, (3) compare the fate of forests within stakeholder‐defined areas of concern, and (4) describe how a user‐inspired outreach tool was developed to make the simulations and analyses accessible to a diverse user group. The associated simulations are strongly divergent in terms of the amount of LULC change and the spatial pattern of change. Among the scenarios, there is a fivefold difference in the amount of high‐density development and a twofold difference in the amount of protected land. Features of the simulations can clearly be linked back to the original storylines. Overall, the rate of LULC change has a greater influence on stakeholder areas of concern than the spatial configuration. The simulated scenarios have been integrated into an online mapping tool via a user‐engagement process meeting the needs of a variety of stakeholders.

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Section: Discussionmentioning

confidence: 99%

Spatial Simulation of Codesigned Land Cover Change Scenarios in New England: Alternative Futures and Their Consequences for Conservation Priorities

et al. 2020

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“…Before approaching panelists for our Delphi study, pre-selection criteria were defined. Panelists should come from diverse backgrounds to mitigate biases [7] . As we focused on D2D air travel, we tried to capture this scope through an appropriate selection of panelists (see also Section "Expert interviews").…”

Section: Selection Of Panelists (Step Two)mentioning

confidence: 99%

“…Conversely, selecting a diverse panel (different age, gender, positions, companies etc.) is a strategy to mitigate biases [7] . We focused in our panel selection on the “ surface-level variables ”, such as age, gender, or job position [49] .…”

Section: Selection Of Panelists (Step Two)mentioning

confidence: 99%

Lessons Learned from a Two-Round Delphi-based Scenario Study

2021

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The Delphi technique is a suitable methodology for structuring group communication to answer current and prospective research questions within several rounds. The method is used in many disciplines and characterized by anonymity, iteration, controlled feedback, and statistical “group response” (Rowe & Wright, 2001). This technical paper presents practical details and lessons learned from a two-round Delphi-based scenario study in which projections (Delphi statements, questions or hypotheses) were developed with findings from expert interviews and an expert workshop. This Delphi study provides answers to future-related questions for which other research methods are inappropriate. This is depicted as a five-step process, making it easy to follow and replicable, for example to help first-time Delphi-method researchers. In doing so, the authors aim to provide the community with valuable technical insights and guidance for studies applying the Delphi technique both to prospective questions and in other research settings. Conducting a Delphi study can be a slow process with respect to receiving feedback from the panelists. Planning an appropriate period for distributing the questionnaire may produce a higher return rate. A sufficient time buffer should be incorporated into project planning. Projections that create dissent among the panelists may provide valuable results. Data analytics, software programs and online social networks can support researchers, save time and resources, and provide further insights in the process of conducting a Delphi study.

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“…A variety of concerns include the related issues of the time horizon of studies and the accuracy of the approaches employed. Indeed, one of the challenges is the pervasive nature of expert biases ( Bonaccorsi et al., 2020 ), which can be found in such approaches as Delphi ( Flostrand et al., 2020 ). As such, Ayres (1999 : 12) appears dismissive of Delphi and related approaches: “I do not have a high regard for expert judgments, taken as a class.…”

Section: Approaches To Conceptualising the Future Of Technologymentioning

confidence: 99%

“…Indeed, forecasting how technology will develop and which technologies will prevail is a challenging and contestable domain ( Albright, 2002 ; Phillips and Linstone, 2016 ). Firstly is the pervasive nature of expert biases ( Bonaccorsi et al., 2020 ) which can be found in such approaches as Delphi ( Flostrand et al., 2020 ). Moreover, prognostications are critiqued for being either too short-term (i.e.…”

Section: Introductionmentioning

confidence: 99%

Conceptualising technology, its development and future: The six genres of technology

Harwood

Eaves

2020

Technological Forecasting and Social Change

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Highlights Forecasting the long-term development of technology is challenging. The six Genres offers a parsimonious framework to examine future developments. This examines various configurations of human – artefact relationships. It identifies autonomy, intelligence, language, and autopoiesis as key features. The sixth genre is established as Interconnected, autopoietic, technological beings.

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Expert biases in technology foresight. Why they are a problem and how to mitigate them

Cited by 87 publications

References 243 publications

Spatial Simulation of Codesigned Land Cover Change Scenarios in New England: Alternative Futures and Their Consequences for Conservation Priorities

Spatial Simulation of Codesigned Land Cover Change Scenarios in New England: Alternative Futures and Their Consequences for Conservation Priorities

Lessons Learned from a Two-Round Delphi-based Scenario Study

Conceptualising technology, its development and future: The six genres of technology

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