{"title":"Developing the needed scientific theory will not be easy: A commentary on Fergnani and Chermack 2021","authors":"Ahti Salo","doi":"10.1002/ffo2.73","DOIUrl":null,"url":null,"abstract":"<p>It is sobering to realize that the age-old human imperative to “make sense of the future” is much older than the institutional manifestations of science. One could even argue that there is an evolutionary demand for the kinds of capabilities that are fostered by foresight and futures studies.</p><p>Thus, regardless of the extent to which these capabilities are scrutinized scientifically (or through the lens of social sciences, as promoted by Fergnani and Chermack (<span>2021</span>)), it lies in the interest of individuals and societies that the processes of building and harnessing these capabilities are guided by an accumulating body of knowledge. As noted by Fergnani and Chermack, this body of knowledge is best built by developing and testing adequate scientific theories. On this point, I tend to agree with them and warmly welcome their contribution.</p><p>Yet foresight and futures studies are not alone in having faced criticisms concerning the lack of theoretical soundness in offering decision and policy advice. Analogous arguments have been raised in macroeconomics, for example. Specifically, Colander (<span>2011</span>) addresses reasons why some researchers have concluded that macroeconomics does not exhibit the attributes which are required of fundamental science. One of these reasons is that the scientific understanding of a phenomenon as complex as the real macro economy remains limited. Furthermore, Colander argues that the standard macroeconomics has confounded fundamental science and policy applications in ways that undermine both. Indeed, juxtaposing these two papers shows that there are notable parallels between the concepts “macroeconomics” and “models” in Colander (<span>2011</span>) and “futures studies” and “scenarios” in Fergnani and Chermack (<span>2021</span>), respectively.</p><p>One implication from Colander (<span>2011</span>) is that if the complexity of the macro economy (as a real phenomenon) is why macroeconomics (as a scientific discipline) has encountered difficulties in ensuring its soundness, then it should not be surprising that futures studies should encounter difficulties, too, because macro economy is but a part of the world at large about which futurists make future-oriented policy relevant statements.</p><p>A trend in many countries is that researchers are increasingly encouraged and even pressured to derive policy implications from their research and to communicate these to policy makers and stakeholders in society. For instance, the Strategic Research Council of the Academy of Finland has been established as a funding instrument which stresses policy impacts. All projects funded by this instrument need to carry out well-planned efforts to exert demonstrable impact on policy and society. Embedded in this requirement is the possibility that the crucial steps in deriving policy recommendations from research are less sound than the execution of the underlying research proper. In part, this is because the transition from “what has been observed” to “what should be done” is an uneasy one. This transition calls for a thorough understanding of stakeholders’ values and goals as well as multidirectional and collaborative processes of interpretation which—even if facilitated by scholars with strong scientific credentials—can be questioned for lack of theory—just like the endeavors of futurists.</p><p>The above possibility may be aggravated due to the fact that academic career systems tend to reward for scientific quality and productivity, thereby creating incentives which may deter researchers from making the time-consuming investment to gain a sound understanding of the sociopolitical context to which their research results are injected. This is particularly the case if the projects are relatively short or if there are but modest prospects for benefiting from such contextual knowledge later on.</p><p>Still, the establishment of such funding instruments indicates that there is a legitimate space for translating conclusive scientific findings and other forms of knowledge to defensible policy recommendations. It would be unfortunate if this space were to be occupied primarily by scientists from other fields if their respective practices in transforming scientific findings to policy implications are no less immune to criticism than those of futurists’. Rather, there should be more collaboration and cross-fertilization in both directions, that is, not only by seeking to strengthen the theoretical foundations of futures studies by building on management and organization sciences, but also by fostering the awareness and uptake of the tested intellectual and methodological apparatus that the field of futures studies can offer to other disciplines.</p><p>In theory building, there is a challenge in that it may be impossible to subject the processes by which scientific findings are translated into policy recommendations to scientific scrutiny <i>at the time when these translations are carried out</i>. For example, the attention span that policy makers can afford to futurists may be fully consumed by the urgent pressures to make timely and defensible decisions. This would undermine opportunities for engaging them in contemporaneous research activities that are not equally instrumental for the decisions at hand. While there may be prospects for conducting such research activities later on, the motivation may be lacking and, once some time passed, the later recollections may not capture the nuances of the process as it unfolded.</p><p>Importantly, these real contexts—as well as the ways in which foresight can be carried out—are very diverse. As a result, the outcomes of futurists’ interventions (such as the efficacy and perceived usefulness of such-and-such a scenario methodology) are dependent on numerous contextual variables of which many cannot be controlled in real-life contexts. In particular, the number of these variables and ways of encoding them can be quite high relative to the number of real-life case studies which can be meaningfully compared with regard to the impacts of different methods, for example. This limits possibilities for reaching statistically significant and generalizable conclusions about which methods are “better”.</p><p>On the other hand, the design, execution, and analysis of controlled experiments makes it possible to arrive at statistically proven results. There are related research traditions in human forecasting (see, e.g., Leitner & Wildburger, <span>2011</span>) and multi-criteria decision analysis (see, e.g Ishizaka & Siraj, <span>2018</span>; Salo et al., <span>2021</span>). Yet the objectives, tasks, and outcomes addressed through such experiments appear narrower than those in typical foresight processes. Furthermore, most experiments have been carried out by recruiting students, that is, relatively homogeneous subjects who are faced with stakes that may not be high enough to be viewed as realistic.</p><p>As for the breadth of the scientific foundations of futures studies, emphasizing management and organization studies exclusively may be limiting and even stifling. Rather, the underpinning theoretical disciplines need to be broad enough, including, for instance, mathematical methods for quantifying, propagating, and understanding uncertainties. That is, if the scope of theoretically sound futures science were to be confined solely to management and organization studies, the field of futures studies could be perceived as unwelcoming by those who work on quantitative and computational techniques, thereby unnecessarily propping rather than eroding barriers. As an example, some of the many variants of scenario analysis (see, e.g. Bunn & Salo, <span>1993</span>) are highly quantitative due to the needs arising from contexts such as nuclear waste repositories (Tosoni et al., <span>2019</span>).</p><p>Given the challenges humanity is faced with, it is imperative to make continued progress to improve our capabilities for “making sense of the future.” Strengthening of the theoretical foundations of futures studies by building on the management and organizational studies can be an important part in this endeavor. To this end, it is pertinent to strengthen connections between methodological advances and accompanying real case studies which are systematically evaluated to support theory building and also to guide further methodological work.</p><p>Within the broader landscape of scientific disciplines, futures studies is set to improve its status by demonstrating intellectual rigor while ensuring that the boundaries between disciplines remain fluid enough to foster cross-fertilization, cumulative learning, and multidisciplinary achievements.</p>","PeriodicalId":100567,"journal":{"name":"FUTURES & FORESIGHT SCIENCE","volume":"3 3-4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/ffo2.73","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"FUTURES & FORESIGHT SCIENCE","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ffo2.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
It is sobering to realize that the age-old human imperative to “make sense of the future” is much older than the institutional manifestations of science. One could even argue that there is an evolutionary demand for the kinds of capabilities that are fostered by foresight and futures studies.
Thus, regardless of the extent to which these capabilities are scrutinized scientifically (or through the lens of social sciences, as promoted by Fergnani and Chermack (2021)), it lies in the interest of individuals and societies that the processes of building and harnessing these capabilities are guided by an accumulating body of knowledge. As noted by Fergnani and Chermack, this body of knowledge is best built by developing and testing adequate scientific theories. On this point, I tend to agree with them and warmly welcome their contribution.
Yet foresight and futures studies are not alone in having faced criticisms concerning the lack of theoretical soundness in offering decision and policy advice. Analogous arguments have been raised in macroeconomics, for example. Specifically, Colander (2011) addresses reasons why some researchers have concluded that macroeconomics does not exhibit the attributes which are required of fundamental science. One of these reasons is that the scientific understanding of a phenomenon as complex as the real macro economy remains limited. Furthermore, Colander argues that the standard macroeconomics has confounded fundamental science and policy applications in ways that undermine both. Indeed, juxtaposing these two papers shows that there are notable parallels between the concepts “macroeconomics” and “models” in Colander (2011) and “futures studies” and “scenarios” in Fergnani and Chermack (2021), respectively.
One implication from Colander (2011) is that if the complexity of the macro economy (as a real phenomenon) is why macroeconomics (as a scientific discipline) has encountered difficulties in ensuring its soundness, then it should not be surprising that futures studies should encounter difficulties, too, because macro economy is but a part of the world at large about which futurists make future-oriented policy relevant statements.
A trend in many countries is that researchers are increasingly encouraged and even pressured to derive policy implications from their research and to communicate these to policy makers and stakeholders in society. For instance, the Strategic Research Council of the Academy of Finland has been established as a funding instrument which stresses policy impacts. All projects funded by this instrument need to carry out well-planned efforts to exert demonstrable impact on policy and society. Embedded in this requirement is the possibility that the crucial steps in deriving policy recommendations from research are less sound than the execution of the underlying research proper. In part, this is because the transition from “what has been observed” to “what should be done” is an uneasy one. This transition calls for a thorough understanding of stakeholders’ values and goals as well as multidirectional and collaborative processes of interpretation which—even if facilitated by scholars with strong scientific credentials—can be questioned for lack of theory—just like the endeavors of futurists.
The above possibility may be aggravated due to the fact that academic career systems tend to reward for scientific quality and productivity, thereby creating incentives which may deter researchers from making the time-consuming investment to gain a sound understanding of the sociopolitical context to which their research results are injected. This is particularly the case if the projects are relatively short or if there are but modest prospects for benefiting from such contextual knowledge later on.
Still, the establishment of such funding instruments indicates that there is a legitimate space for translating conclusive scientific findings and other forms of knowledge to defensible policy recommendations. It would be unfortunate if this space were to be occupied primarily by scientists from other fields if their respective practices in transforming scientific findings to policy implications are no less immune to criticism than those of futurists’. Rather, there should be more collaboration and cross-fertilization in both directions, that is, not only by seeking to strengthen the theoretical foundations of futures studies by building on management and organization sciences, but also by fostering the awareness and uptake of the tested intellectual and methodological apparatus that the field of futures studies can offer to other disciplines.
In theory building, there is a challenge in that it may be impossible to subject the processes by which scientific findings are translated into policy recommendations to scientific scrutiny at the time when these translations are carried out. For example, the attention span that policy makers can afford to futurists may be fully consumed by the urgent pressures to make timely and defensible decisions. This would undermine opportunities for engaging them in contemporaneous research activities that are not equally instrumental for the decisions at hand. While there may be prospects for conducting such research activities later on, the motivation may be lacking and, once some time passed, the later recollections may not capture the nuances of the process as it unfolded.
Importantly, these real contexts—as well as the ways in which foresight can be carried out—are very diverse. As a result, the outcomes of futurists’ interventions (such as the efficacy and perceived usefulness of such-and-such a scenario methodology) are dependent on numerous contextual variables of which many cannot be controlled in real-life contexts. In particular, the number of these variables and ways of encoding them can be quite high relative to the number of real-life case studies which can be meaningfully compared with regard to the impacts of different methods, for example. This limits possibilities for reaching statistically significant and generalizable conclusions about which methods are “better”.
On the other hand, the design, execution, and analysis of controlled experiments makes it possible to arrive at statistically proven results. There are related research traditions in human forecasting (see, e.g., Leitner & Wildburger, 2011) and multi-criteria decision analysis (see, e.g Ishizaka & Siraj, 2018; Salo et al., 2021). Yet the objectives, tasks, and outcomes addressed through such experiments appear narrower than those in typical foresight processes. Furthermore, most experiments have been carried out by recruiting students, that is, relatively homogeneous subjects who are faced with stakes that may not be high enough to be viewed as realistic.
As for the breadth of the scientific foundations of futures studies, emphasizing management and organization studies exclusively may be limiting and even stifling. Rather, the underpinning theoretical disciplines need to be broad enough, including, for instance, mathematical methods for quantifying, propagating, and understanding uncertainties. That is, if the scope of theoretically sound futures science were to be confined solely to management and organization studies, the field of futures studies could be perceived as unwelcoming by those who work on quantitative and computational techniques, thereby unnecessarily propping rather than eroding barriers. As an example, some of the many variants of scenario analysis (see, e.g. Bunn & Salo, 1993) are highly quantitative due to the needs arising from contexts such as nuclear waste repositories (Tosoni et al., 2019).
Given the challenges humanity is faced with, it is imperative to make continued progress to improve our capabilities for “making sense of the future.” Strengthening of the theoretical foundations of futures studies by building on the management and organizational studies can be an important part in this endeavor. To this end, it is pertinent to strengthen connections between methodological advances and accompanying real case studies which are systematically evaluated to support theory building and also to guide further methodological work.
Within the broader landscape of scientific disciplines, futures studies is set to improve its status by demonstrating intellectual rigor while ensuring that the boundaries between disciplines remain fluid enough to foster cross-fertilization, cumulative learning, and multidisciplinary achievements.