The Tradition of Dialectic Logic of Enlightenment and “What If” Science Challenges
Jari Kaivo-oja & Antti Ainamo:
With globalization and new technologies, local forms of knowledge, local traditions, and local legacies, these have all lost much of their valence. Traditional boundaries between industry and art (Dalpiaz, Rindova & Ravasi, 2016), between one style of design of planning and another (Jencks, 1986), between what is masculine and what is feminine (Djelic & Ainamo, 2005), political orientation (Fukuyama, 2022), or otherwise one’s identity (Fukuyama, 2018), these are not carved in stone as they once were, but uncertain and often ambiguous topics to be but imperfectly forecasted. In this time of fluidity and flux, the past and the present serve less as models for the future or for appropriate ways of thinking and acting than earlier.
Futures research and foresight research have more to gain from cross-pollination between one another than earlier. More specifically, we here propose how and why the most gain from doing so is to integrate two kinds of research, starting from framing in a matrix “critical theory” and “traditional theory”.
Critical and traditional theory
A distinction can be made between what is generally called “critical theory” and what is generally called “traditional theory”. In the following, we briefly review each one of these two theories in turn, integrate these theories within a matrix, add a time dimension as our novel contribution and, finally, propose new directions in and across futures research and forecasting research.
Through the sections of this thought piece, we take it that traditional-theoretical links between not only deductive logic and inductive logic but also between deductive and inductive logic, on one hand, and critical-theoretical phenomenology, on the other hand, are – or at least ought to be – very interesting. Further, we propose here why experts in foresight research, in particular, ought to be even more aware than researchers in futures research of the theoretical aspects at play in our times fluid and turbulent times. This is because of the so-called Occam’s razor, or parsimony, as it is also called. First, let us briefly review critical theory.
Critical theory: Frankfurt School and its criticisms
Generally, critical theory is an approach to science with a goal transform society as a whole, taking as its starting point to ”examine the entire material and spiritual culture of mankind” (Shaw, 1985). Critical theory traces to the “Frankfurt School of Critical Theory”, founded in 1923 in Frankfurt, Germany, by Max Horkheimer. This School was originally a collection of researchers and philosophers that came together to study the application of Marxism to philosophy and society. The driving idea was Horkheimer’s examination of his personal wealth. At the same time, Horkheimer was witnessing and examining the juxtaposition of the bourgeois and the impoverished. The critical theory Horkheimer came up was (and to some extent still is) preoccupied with forces, which in his view falsely relied on “traditional theory”, failing to embrace future possibilities in his economy and society. Horkheimer’s emerging critical theory would be a left-wing precursor to Alexander’s (1962) right-wing juxtaposition of what is “traditional” and what is “modern”, decades later. Both Horkheimer and Simon in their particular ways strove to move forward with an overt of rationalizing forms of life so that these would ensure a more true, more free, and more just life than earlier.
Horkheimer and his associates were first associated with the Institut für Sozialforschung (Institute of Social Research) at Frankfurt University, and director of the Institute and Professor of Social Philosophy at the same university from 1930 to 1933. Horkheimer then, after Hitler was named Chancellor and the Institute in Frankfurt was closed, relocated to Geneva, Switzerland, where the Institute had a satellite office. In 1934, Horkheimer moved on, this time to New York, where he opened the Institute with the Department of Sociology at Columbia University. In 1937, Horkheimer crystallized what is critical theory in his essay entitled Kritische Theorie (Traditional and Critical Theory), defining it to be a social theory oriented toward critiquing and changing society as a whole, in contrast to traditional theory oriented only toward understanding or explaining one or another part of it (Benhabib et al., 1993).
Since then, critical theory has sought to develop a phenomenological perspective to discuss a large variety of social practices and social systems, without losing context of the whole. Critical theory has established itself as an approach of social philosophy that focuses on society and culture to attempt to reveal, critique and challenge power structures.
Critical theory has never formed a coherent group of researchers, but the thinking has been multidisciplinary with emphases very different and heterogeneous from one another. Various critical theorists have postulated and examined the effects of big businesses, monopolies, electronics, consumerism, technology, and capitalism on human life and society. The work of these researchers has also explored human freedom and liberation in the context of slavery and the inhuman practices of societies.
In and across its various forms, critical theory has had a far-reaching influence on the fields of sociology, educational studies, ethics studies, philosophy, and cultural studies (Bernstein, 1976; Arato & Gebhardt, 1978; Apple, 1990; Anderson, 1992; Mann, 2008). There are also many big names in social research than Max Horkheimer associated with critical theory: Theodor Adorno, Herbert Marcuse, Erich Fromm, Jürgen Habermas, Walter Benjamin, Paulo Freire, Richard Bernstein, Axel Honneth, Judith Butler, and Rahel Jaeggi, for example, they have all worked in or with field of critical theory. These and still other critical-theory researchers have shared their work in a publication called the Journal for Social Research. According to Elliot and Ray (2003; cf. Sica, 2005), critical theory is today known as ”one of the most influential social theories of the twentieth century”.
With its original roots in sociology and literary criticism, critical theory argues that social problems stem more from social structures and cultural assumptions than from individuals. It has found applications in various fields of study, including psychoanalysis, sociology, political sciences, history, communication theory, philosophy, and feminist theory.
Still today, researchers of critical theory are critical of the effects of technology and capitalism on society. Thus, the Frankfurt School was and remains a significant exemplar a group of philosophers and social scientists. A huge variety of promising approaches in critical theory of politics are still very important today (e.g. Amy, 2021, 2016, 2007). We can nowadays credibly claim that we really need critical theory of politics, for example. Grand challenges in politics include how should we deal with populism. with uncritical identity politics, etc. In and across these challenges, one of the key ideas in critical theory is that ideology and all kinds of “isms” are the principal obstacle to human liberation and social development (see Tyson, 2023; Mann, 2008; Held, 1980; Roth & Kaivo-oja, 2016; Kaivo-oja et al., 2017; Viia et al., 2017; Roth et al., 2017, 2018, 2020; Sverre & Kaivo-oja, 2018).
On the other hand, critical theory itself has also met significant criticism and by and objections from Bohmann and Sörensen (2022), for example, for not offering any clear scenarios or road map for political action (praxis), often explicitly repudiating any solutions. Critical theory has in this way supported neither futures research or forecasting research. Critical theory’s critics have noted that politics, in particular, is a blind spot of the critical theory. They have elaborated in detail the fundamental constellation of ambivalence of the early Frankfurt School on politics.
Another criticism of critical theory is that it has often failed to provide rational standards by which it can show that it is superior to other theories of knowledge, science, or practice. For example, Rex Gibson (1986) has argued that critical theory suffers from being cliquish, conformist, elitist, immodest, anti-individualist, naivety, too critical, and contradictory, all of these in many ways. Hughes and Hughes (1990) argue that Jürgen Habermas’ theory of ideal public discourse “says much about rational talkers talking, but very little about actors acting: felt, perceptive, imaginative, bodily experience does not fit these theories”. Some feminists argue that critical theorists “can be as narrow and oppressive as the rationalization, bureaucratization, and cultures they seek to unmask and change. (see e.g. Randall & Allen-Brown, 1996, 7–8).
The above kinds of criticisms of and objections to it mostly apply to first-generation Frankfurt School, while the issue of politics has been addressed in a much more assertive way in contemporary critical theory. As for Jürgen Habermas, it is beyond doubt that, despite the shortcomings of his work, he developed quite an impressive theoretical framework in his studies (see e.g. Habermas, 1969, 1971, 1974, 1984, 1987, 1990). In sum, there has been a lot of criticism of critical theory, much of it warranted. But it is by no means anything surprising in the field of human and social sciences, where it is normal that the best theories and studies are challenged and criticised. In the social theories, any theory is developed through criticism. In any free democratic society, too, criticism is a central way of development. In the totalitarian societies, not much criticism is allowed. The task of enlightenment is still the unfinished, as more than one social-science scholars has noted (Connerton, 1980; Hullot-Kentor, 1992; Honneth, 2000; Gandesha, 2001; Adorno & Horkheimer, 2002; Fleming, 2012; Mitchell, 2014). Hegelian dialectic and dialectics of futures research, foresight research and anticipation studies, we propose here, can and ought to be part of this kind of critical thinking.
In synthesis, the question of “what is critical theory?” in our fluid and turbulent times, has answers from both a narrower lens and a broader lens. The narrower lens points to the work of people specifically historically associated with the Frankfurt School, which addressed social movements and human freedoms of the time. The broader lens frames critical theory as a perspective that can address human freedom in any historical period, such as the one we now inhabit.
In the decades since the initial development of critical theory, the framework has been applied to several social justice issues (see Sen, 2011). Feminist theory, critical race theory, and media theory all have roots in critical theory. We remind here that this kind of scientific roots is good to know also in the field of futures research and foresight research.
During this Millennium, Horkheimer’s critical-theoretical ideas about what is theory have become the subject of renewed academic interest. Philosophers of science and their colleagues have turned their attention also to the inspiration that Horkheimer took from his predecessors: Weyl and Husserl, forefathers of phenomenology and, in turn, Husserl’s interest in Medicus’s transcendental philosophy (see Sieroka, 2007; Husserl, 1989). At first, relatively little attention was paid to Weyl’s original ideas. Then, Scholz (2012) focused on Weyl’s ideas about vector calculus and the relativity of space. Lehtonen and his colleagues (2020) have shown how geographical space can be approached on a purely subjective phenomenon, rather than objectively. Schutz, Ainamo and Lamberg (2021) have taken a radical departure from deductive logit, focusing on the relativity of time-place dynamics from a vector-calculus perspective.
All of the above begs the question of how, then, does critical theory differ from “traditional theory.” What is traditional theory?
Traditional theory in its deductive- and inductive-logic versions
As Horkheimer (1937) notes, the human and social sciences have tried to mimic the natural sciences, some human and social sciences concentrating on facts, other human and social sciences on principles. Both share the same concept of theory. This kind of natural-sciences-inspired activities of fact-gathering and general principles have been operating much like the rest of life in a society dominated by industrial production techniques. The human and social sciences’ “market value” has depended on their imitation of the natural sciences and their methods. This traditional conception of theory remains the same in and across the more deductive and more inductive variants. Empirically oriented social evolutionary social theorists since Herbert Spencer (1897) William Whewell (1853) have held that society is too complex to justify seeking general principles right away. They, and many others following their exemplars, have recommended to analyse and assemble facts first and then do some comparisons to achieve a complete induction, rather than just abductively develop armchair theories. Abductive reasoning (which is also called abduction, abductive inference, or retroduction) is a form of logical inference that seeks the simplest and most likely conclusion from a set of observations. It was formulated and advanced during the last third of the 19th century by American philosopher Charles Sanders Peirce. Today futures research and foresight research are established field of knowledge with a wealth of methods and techniques. Foresight research and its pragmatic attitude and futures research and its normal focus on scenarios, however, as a rule, are based on induction or deduction methods.
Deduction and induction methods make looking into the future a form of conservative or traditional projecting of past and present probabilities onto the road of development lying ahead of us. Closed past or present scientific outlooks give promise to give birth to open futures, but the futures thus envisioned usually are little more than exercises in common organizational learning.
The conclusion of a deductive argument is always certain given the premises are correct. The output may consist of predictions or general statements, where predictions concern unobserved singular states of affairs, and general statements, such as empirical generalizations, concern universal states of affairs.
Deductive thinking is also known as deductive reasoning or deductive logic. It is a type of logical thinking that starts with a general or basic idea to reach a specific conclusion. This idea of moving from general to specific is also known as the top-down approach. This view of social theory descends from modern philosophy and deductive thinking, such as Descartes’s “Principles of Rules” or Clarke’s (1982, 2003, 2006) “analysis – simples – order – deduction”. In addition to deductive thinking, logic or reasoning, the other side of traditional theory is inductive thinking, logic, or reasoning.
In contrast to deductive logic, the truth of the conclusion of an inductive reasoning is an argument that is always probable, based upon the evidence given application to concrete problems. Universal propositions or experiential judgments or inductive or evident insights emerge from analysis of data. In traditional theory, inductive logic is a method of reasoning in which a general principle is derived from a body of observations. It consists of making broad generalizations based on specific observations (see e.g. Romeyn, 2004). The input of an inductive method includes a data set, usually consisting of observations, and possibly some further assumptions. Often inductive logic is linked to so called Carnap–Hintikka inductive logic (see Carnap, 1950, 1952; Hintikka, 1966, 1970; Carnap & Jeffrey, 1971; Hintikka & Niiniluoto, 1976; Hintikka, 1997; Hintikka & Bachman, 1991).
Any traditional theory in this view is a sum of propositions linked to one another as a system (basic and derived), where the propositions are derived from, are consonant with, or both, with facts. The theory consists of useful hypotheses – stores of knowledge (library analogy). In the field of futures studies many author discuss about ”scenario libraries” or “scenario data libraries”.
In partial contrast to both deductive and inductive approaches, an abduction-based futures research approach what proceeds from closed, imaginary future states to alternative, truly open theoretical frameworks or explanations (see e.g. Peirce, 1878; Josephson & Josephson, 1994; Niiniluoto, 1999; Carson, 2009; Campos, 2011; Patokorpi & Ahvenainen, 2009).
A critical statement in this context is that it is possible that in the field of foresight research and futures research that we have not been investigating “what if” questions too much. Rather, we maybe ought to focus more on “what if” questions and reason more from such questions – abductively and critically.
Now, next, let us turn our attention to how to integrate understandings of critical theory and traditional theory.
Occam’s Razor and Its Sharpness
The idea of Occam´s razor can be traced to Aristotle (384–322 B.C.), the Greek philosopher, who wrote in his Posterior Analytics, “We may assume the superiority ceteris paribus [other things being equal] of the demonstration which derives from fewer postulates or hypotheses.” Another Greek philosopher, Ptolemy (c. AD 90 – c. 168), stated: “We consider it a good principle to explain the phenomena by the simplest hypothesis possible.” This kind of general approach can be applied to general theory of sustainable development with ceteris paribus assumptions (see e.g. Luukkanen, Vehmas, Kaivo-oja & O´Mahony, 2023) and to the scenario analysis of sustainability (Ravetz, 1997; Kaivo-oja, 1999, 2001; Kaivo-oja et al., 2001; Wilkinson & Elahi, 2003; Wilkinson & Eidinow, 2008; Wright & Goodwin, 2009; Lloyd & Schweizer, 2014; Thompson et al., 2012). It is always possible to postulate social and natural science scenarios as alternative hypotheses.
In the late 1950s and early 1960s, Ray Solomonoff, the largely unrecognized pioneer of futures research, developed his theory of ”inductive inference”, a branch of Artificial Intelligence (AI) that focused on probability and prediction; his envisioned AI machines governed by Algorithmic Probability distribution. The main idea of his influential traditional theory of prediction was observation-based prediction of the next symbol based upon a given series of symbols. Nowadays, such algorithms are very popular and developed, but is almost forgotten how and why Solomonoff (1964a, 1964b) founded his theory., based on formal inductive reasoning in a Bayesian framework to develop an algorithmic information theory. His “machine” generates theories together with their associated probabilities, to thus solve problems. Fundamental ingredients of the theory are the concepts of algorithmic probability and Kolmogorov complexity (see Rissanen, 2007; Kolmogorov, 1965, 1968; Vitanyi, 2013). As new problems and theories develop, the machine updates the probability distribution on the theories (Rathmanner & Hutter, 2011), essentially amounting to a mathematically formalized Occam’s razor.
The modern justification for Occam’s razor – in line with Solomonoff’s work – is that it is a direct result of basic probability theory. By definition, all assumptions in such a machine introduce possibilities for error. If an assumption does not improve the accuracy of a theory, its only effect is to increase the probability that the overall theory is wrong. Occam’s razor is also known as the principle of parsimony or the law of parsimony. Both Occam’s razor and parsimony are problem-solving principles that call for searching for explanations constructed with the smallest possible set of elements.
Recently, there have been many renewed attempts to further improve upon the works of Aristotle and Solomonoff in their respective times – to derive how Occam’s razor relates to probability theory. These recent attempts notably include those by Harold Jeffreys (Robert et al., 2009) and E. T. Jaynes (Jaynes, 2003). The probabilistic (Bayesian) basis for Occam’s razor is elaborated by David J. C. MacKay in chapter 28 in his book “Information Theory, Inference, and Learning Algorithms” (Kay, 2003), where Kay emphasizes that a bias in favour of simpler models is not always required or wise to reach valid findings in research.
These recent attempts build on Husserl (1933), from whom Horkheimer (1937) took it that any traditional theory is systematic and typically linked to the whole of propositions (like theory in natural sciences). Horkheimer also built here on Weyl (1927). Horkheimer shared Weyl’s idea that harmony and economy are necessary for a traditional-theoretical system. In traditional theory, formal logic as a model of reason is essential for theory formation. In traditional theory, theoretical fundamentals have tended toward mathematical symbolism.
From the perspective of traditional theory, classical 19th and early 20th century distinctions (Tönnies’s Gemeinschaft or community vs. Gesellschaft or society; Durkheim’s mechanical vs. organic solidarity; Weber’s culture vs. civilization) are questionable from the espoused focus on principles and fact gathering in traditional theory. These distinctions, which are more in line with critical theory than they are with traditional theory, are applied in also many scientific analyses and articles that build on traditional theory and methodologies.
Critical Theory and Traditional Theory in a Matrix, and Propositions for Further Research
We take it that, for future research, distinctions between critical and traditional theory, on the one hand, and beach heads for the cross-pollination between the two, on the other hand, are central. These distinctions are also very important in terms of specifying the scientific basis for statistical forecasting research and futures research.
As we well know, explanatory scenarios and normative scenarios are at the heart of foresight and futures research. Following Piirainen and Gonzalez (2015; cf. Martin, 2010), explanatory scenarios are related to the traditional theory of science we have briefly reviewed above. Normative theories are related to critical theory in the human and social sciences (ibid.).
Futures, foresight research and forecasting research enter here the picture in that they are both very strongly linked to the central questions of social theory and applied human and social sciences, which have been studied for a very long time, but also take in very seriously advances, and strong and weak signals about them, in the natural sciences (ibid.).
A recent challenging and important study in futures research distinguishes normative futures research not from explanatory research, but from non-normative and explorative futures research (Minkkinen et al., 2019). Normative futures research is seen as having three distinct frames (Minkkinen et al., 2019): (a) planning frame, (b) visionary frame, and (3) transformative frame (Figure 1). Non-normative and explorative futures research – which the study considers “traditional theory” – for its part, is seen to also have three distinct frames: (1) predictive frame, (2) scenaric frame, and (3) critical frame.
In Figure 1, we portray critical theory as normative and traditional theory as non-normative and explorative. Note that, in Figure 1, the critical frame has three variants: predictive or different from what we see in the present (level of perceived unpredictability), scenaric and considering what might change (alternatives), and highly critic or question and even forecasting (level of pursued change). It is good to understand that a generic typology employs an inclusive understanding of foresight that does not draw sharp distinctions between explicit foresight, futures research and futures thinking in general (anticipation). Minkkinen et al. (2019) are interested in explicit anticipation rather than implicit unconscious anticipation (see Poli, 2017, 266–268).
Figure 1. Six frames. Dimensions: Level of pursued change and level of perceived unpredictability.
These six frames capture different sets of assumptions and different types of foresight/futures research, which can be distributed to different actors in a foresight system. Minkkinen and his colleagues, the original authors of Figure 1, suggest that diversity of foresight frames is likely to be a critical element of successful foresight systems. We add that this requires understanding the diversity of foresight frames and the competence to bridge different orientation approaches of frames.
In Figure 1, building on the work of Minkkinen and his colleagues, we thus link critical theory with descriptive explorative futures research. This in partial contrast to how many other normative futures and forecasting researchers have suggested that futures, foresight, forecasting and anticipation research are both one kinds of variation of Frankfurt-school critical theory and traditional theory. Only few futures researcher refer to classical research findings and articles of critical theory and traditional theory as Max Horkheimer defined these frames of social sciences (see e.g. Benhabib, Bonß & McCole, 1993; Tuomi, 2019; Derbyshire, 2017; Szpunar et al., 2016; Dufva & Ahlqvist, 2015a, 2015b, 2015c; Ramirez & Selin, 2014; Alvesson & Kärreman, 2011; European Foresight Platform, 2010; Keenan, Loveridge, Miles & Kaivo-oja, 2004; Georghiou & Keenan, 2006; Wilkinson & Eidinow, 2008; van Asselt et al., 2007; Bishop et al., 2007; van Notten et al., 2003; Inayatullah, 1990, 1998; Jacques, 1990; Bradfield et al., 2005; Ahvenharju et al., 2018).
In partial contrast to the above researchers who have suggested that futures, foresight and anticipation research includes variations of traditional theory and critical theory, we below use the work of Francis Fukuyama, the renown Stanford University professor as illustrative of our ideas in our thought piece. That is a reason why we need to discuss more about Hegelian dialectic logic and its relevance for futures and foresight research and for general anticipation studies.
Francis Fukuyama’s work as illustrative of fluid and turbulent times
Some inductive researchers have used to inductive logic to reasons from outcomes. After the fall of the Berlin Wall in 1989, Fukuyama announced in his ‘The End of History?’ that this event was a mark of the triumph of liberal democracy and an arrival of a post-ideological world, but also a ‘sad time’ as it had ushed in the demise of all utopias and utopianism.
When we interpret the idea of inductive reasoning and Occam´s razor as do MacKay and Fukuyama, we can apply this razor also in the field of futures studies: we build “what, if” and exploratory or probability-based scenarios (compare to Hintikka & Bachman, 1991). But is the outcome-based reasoning of Fukuyama, for example, just a new right-wing argument in disguise? This is a question that in our view needs to be approached critically.
Of course, with the wars in Crimea and Ukraine, for example, we now know, by hindsight, that the end of history in Francis Fukuyama’s thinking is surely not an accurate assessment, a fact recognized also by Fukuyama himself. In the last twenty years or so, we have also seen the rise of Islamic fundamentalism, 9/11, the Arab spring, and New Cold War as proofs that ideological contests remain. What has come in the place of end-of-history thinking and end-of-history mental models are identity politics and new forms of populism, which prefer to separate values and facts, which often does not lead to very critical thinking. Thus, any announcement that the great ideological battles between East and the West would have been over, that western liberal democracy would have triumphed and “history ended” must obviously be met with healthy scepticism.
We take it that Francis Fukuyama is but one example of those many social researchers that can be dubbed “court philosophers of global capitalism”. Consider that Fukuyama has discussed one’s identity issues (Fukuyama, 2018), political orientation questions (Fukuyama, 2006a, 2006b, 2008, 2022), choice of governance model (Fukuyama, 2004), historical interpretations (Fukuyama, 1999, 2011, 2014), and trust factors of societies (Fukuyama, 1995) and future developments and challenges (Fukuyama, 2002). We focus on Fukuyama here because he has drawn, and continues to draw, on the philosophy of Georg Wilhelm Friedrich Hegel who, long time ago, defined history as a linear procession of epochs; that is, as a non-fluid process of change. For G.W.F. Hegel, technological progress and the cumulative resolution of conflict allowed humans to advance from tribal to feudal to industrial society.
Some historians (e.g. Fackenheim, 1967) have presented Hegel’s influence as being divided into two opposing camps of followers: (1) right-wing followers and (2) left-wing followers. Right-wing Hegelians, the allegedly direct disciples of Hegel at the Friedrich-Wilhelms-Universität, have advocated a Protestant orthodoxy and the political conservatism of the post-Napoleon Restoration period. Left-wing Hegelians, also known as Young Hegelians, have interpreted Hegel in a revolutionary sense, leading to an advocation of atheism in religion and liberal democracy in politics. Recent studies, however, have questioned this paradigm (Löwith, 1964; Redding, 2020). Of course, it is also possible to note that there are middle of road thinkers in politics, which are not clearly left or right-wing thinkers.
Right-wing Hegelians “were quickly forgotten” and “today mainly known only to specialists”. Left Hegelians, by contrast, have “included some of the most important thinkers of the period,” and “through their emphasis on practice, some of these thinkers have remained exceedingly influential,” primarily through the Marxist tradition. For Karl Marx, the journey ended with communism.
For Fukuyama and his readers, the Hegelian journey was ending more than 30 years ago, and he was announcing a new destination: what we know we can call it Industry 4.0, Industry 5.0 society, Industry 6 society, and so on (Kaivo-oja et al., 2022; Bzhalava et al., 2022). While Francis Fukuyama himself has admitted that history did not end (Fukuyama, 2022), he still sees a clear destination in front of us. We, in contrast, a follow Lombardo (2016), according to whom a Hegelian dialectic logic is sound path to purposeful evolution. That is, we build more critically on Hegel than does Fukuyama, and propose there ought to always – or at least for the foreseeable future – remain a Hegelian dialectic as a part of futures-research-based consciousness.
Neither Francis Fukuyama nor we thus believe that history has ended. But where Fukuyama and we maybe differ is that at least we (and maybe he also) are witnessing is a never-ending neo-Hegelian model of history and a journey, with one advance or other event after another, learning about one’s shortcomings and those of others, learning about our caveats, and the like; witnessing emerging criticisms: developing antitheses to those criticisms, and emerging or appearing to emerge with a series of dynamic equilibria. That much we can predict of the future based on what we now know of the past and the unfolding present (which is a little bit more than in the early 1990s). We now can, with the help of A.I., for example, build multiple scenarios of how near and far-away futures will unfold and at what kinds of probabilities we may attach to these scenarios (see. e.g. Makridakis, 2017; Gruetzemacher & Whittlestone, 2022).
If we take Francis Fukuyama at his word, we should focus critically on key variables such as (1) power structures and geopolitics (Fukuyama, 2022, 2008, 2006a, 2006b); (2) formation of identities (Fukuyama, 2018); (3) interpretations of history (Fukuyama, 2014, 2011, 1992); (4) governance model analyses (Fukuyama, 2004); (5) key drivers of posthuman futures (Fukuyama, 2002); (6) political processes (Fukuyama, 1999, 1992); and (7) trust factors of societies (Fukuyama, 1995).
There is much room for critical qualitative and quantitative scenario analyses. The problems of humankind are very demanding and wicked (see e.g. Dixson-Decleve et al., 2022). The relevant question in foresight and futures research is how we must, or how we ought to, forecast or to prepare for futures that in all probability will differ from how our current ecosystems and societies are set up by us and by others. As noted in this short thought piece published as a blog text, we should pay much more attention to professional “what if” questions and analyses. If we don’t ask such critical questions, we may sometimes be very surprised positively (see e.g. Ainamo, Dell’Era & Verganti, 2021; Pantzar & Ainamo, 2003). But, perhaps more importantly, we propose asking such questions will probably serve to avoid many unpleasant surprises and crises by taking the time and effort.
A grand synthesis and alternative scenarios of problem-solving capacity of the humankind?
As a grand synthesis of our previous reflections and discussions, we can present Figure 2. This figure combines the Hegelian idea of dialectic historical development and problem-oriented scientific “what, if” thinking.
The central message of this picture is that the quality of political debate depends on the ability of the political system to produce progressive syntheses after theses and antitheses, whether left or right or middle-of-the-roaders. The ability to produce syntheses depends on the scope and quality of critical thinking and the focus of critical discussion on really important issues and problems.
Figure 2. Hegelian dialectic: Political discussion, political evolution and problem-solving capacity and potential impacts of “what if?” critical antithetical questioning of each traditional thesis that is produced in research following deductive or inductive thinking.
As many critical thinkers have argued, populism can hinder rational political debate and thus weaken the ability to solve problems in politics. Populism can also decrease societal trust and make political decision-making very difficult (see e.g. Apunen et al., 2017; Bachmann, 2018; Herkman, 2019; Eatwell & Goodwin, 2018).
The creation of synthesises may also become more difficult in circumstances where confrontations characterise social debate and decision-making. For critical discussion, it is important to develop what-if thinking and thus increase the capacity to solve societal system problems. If this is not possible, there will be a big risk of a regressive scenario.
If high-level problem-solving capacity can be achieved, a desirable progressive scenario can be achieved. It is also always possible to end up in what we can call a “stable scenario” – a scenario where we are stuck at the same level achieved.
Jari Kaivo-oja & Antti Ainamo
List of References and Background Reading
About the Authors
Jari Kaivo-oja is Research Director at the Finland Futures Research Centre, University of Turku. He is an Adjunct Professor at the Faculty of Science at the University of Helsinki (planning and management sciences of regional planning) and the Department of Social Sciences at the University of Lapland (foresight and innovation research) and at the University of Vaasa (technology foresight, knowledge management and applied research of digitalisation). He has been a researcher at the Strategic Research Council (SRC) of the Academy of Finland in Manufacturing 4.0 and EL-TRAN projects. He has worked in various foresight and innovation management projects for the European Commission, for the European Foundation, for the Nordic Innovation Centre and for the European Parliament. Dr Kaivo-oja is an active scientific reviewer and he has worked in 16 scientific journals and has very broad experience in scientific advisory tasks of the European Commission, in ministries in Finland, large corporations, and growth-oriented firms. He is also a conference reviewer of the Knowledge Management in Organisations (KMO) Conference, the International Conference of European Processes (ICEP), the Finland Futures Research Centre’s conferences (FFRC Futures Conferences), and the International Conference of the European Academy of Management (EURAM). In the years 1991–2023, he published about 260 scientific publications.
Antti Ainamo is Project Researcher in Civil Engineering, School of Engineering, and at CKIR, School of Business, both at Aalto University. Part-time, he is Associate Professor at Sandbox, Institute of Computer Science, University of Tartu. He also continues as Adjunct Professor at Aalto’s School of Arts, Design and Architecture. His earlier positions include those at Tongji University, Swedish School of Textiles, Oxford University Said School of Business, Umeå SBE, Stanford University, and London Business School. Dr Ainamo has worked in various foresight and innovation management projects for the European Commission, the Nordic Innovation Centre, Academy of Finland and Business Finland, and consulted companies such as Nokia and Kone. He has published in journals such as Organization Science, Industry and Innovation, Human Relations, Creativity and Innovation Management, Research in the Sociology of Organizations, and Scandinavian Journal of Management.
Image by Patricio González from Pixabay
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