Article
Aina García Mestre
Faculty of Communications and International Relations, Blanquerna Ramon Llull University, Barcelona, Spain
Abstract
The advent of digital technologies has led to a major transformation in the way knowledge is being produced, disseminated, and consumed. Some of these technologies–such as Big Data and AI–have the potential to challenge the classical DIKW (Data, Information, Knowledge, and Wisdom) pyramid, compressing the first two and leading to unreliable and contaminated knowledge, which has profound sociopolitical implications. Moreover, this new uncertainty leads to a democratization of knowledge which, along with globalization, alters and shapes a new postnormal reality. This paper explores the change and crisis in knowledge production from a classical to a postnormal perspective. Applying the Three Tomorrows approach, it portrays three different future scenarios with the intention of unveiling the intrinsic possibilities and relation among them. Ultimately, the paper offers different outcomes that involve knowledge hierarchy and uncertainty, and multiple scenarios are presented. Findings prove that new approaches must be undertaken to be able—not to overcome, as the future is not something to battle against—but to learn how to accept, prepare, and navigate these upcoming realities.
Keywords
Knowledge, International Relations, Postnormal Times, Three Tomorrows, AI
Introduction – Questionable Knowledge, Big Data & AI
The term “knowledge” once used to serve to refer to reliable information—information that had been processed, verified, and contrasted—but one can argue it is not always the case anymore. Nowadays, the production of knowledge is problematic for multiple reasons, being one of the main ones the arrival of Big Data and AI. These turn the prior DIKW pyramid system— by Ackoff (1989)— obsolete while compressing it, removing crucial steps such as contrasting information in order to obtain legitimate information from raw data. The concept of knowledge creation itself also becomes relevant in this discussion—as real wisdom nowadays is mostly non-existent (Sardar, 2020). While the exact path that is followed in knowledge creation remains a subject that sparks debate (Kuhn, 1962), a crucial distinction must be made between knowledge creation and knowledge transfer (Horan and Finch, 2016). The KM (Knowledge Management) cycle—a process of transforming information into knowledge that explains how knowledge is captured, processed, and distributed in an organization—has demonstrated that while quite a lot of research has been done in the knowledge transfer part, little is known about the first and most important one: knowledge creation (Horan and Finch, 2016).
An important factor to consider is the arrival of mobile and online communication, which undeniably increased global connectivity, networked traceability, and led to the accessibility of such enormous amounts of information (Raine and Wellman, 2012). While Big Data and AI both have a positive and a negative side—when comparing traditional techniques of processing data, Big Data shows to be very useful in terms of range and speed—a significant issue has arisen: uncertainty. This uncertainty has a huge impact in the already mentioned knowledge creation stage. Although access to information has exponentially increased compared to the one available before, most of this data is non-reliable. The huge amounts of data collected along with the increase in the speed of data comes with growing uncertainty and one of the main reasons for this uncertainty is precisely the nature of Big Data which is usually “unstructured, incomplete or noisy data” (Hariri et al, 2019). Uncertainty can be understood as a situation which involves unknown or imperfect information (Knight, 1921), and there are multiple factors intervening such as variance in data collection, multimodality, incompleteness, noise, etc. Furthermore, the number of missing links between data is around 85%, which leads to multiple forms of uncertainty that affect the accuracy of results (Hariri et al, 2019). This issue has a huge impact when it comes to Big Data and its inability to control uncertainty. Because Big Data includes many sources, and some of them may not be correctly linked or may be biased, it is very difficult to evaluate whether the obtained information is reliable or not.
The main issue relies on the fact that Big Data is non-contrasted and taken as information and, as a result, the obtained information can be considered as contaminated. On top of that, AI operates using this contaminated information and processes it, creating knowledge that is unreliable. Big Data does not allow the necessary distinction between relevant and non-relevant data when creating correlations, hence complicating the process by which information is obtained and creating a threat when it comes to reliability (Leonelli, 2020). Furthermore, one must not forget that AI is impersonal, not being able to apply its own personal criteria— something that is usually linked to wisdom, being therefore arguable the fact that AI cannot produce wisdom of any type. As Robert W. Cox (1981) stated, theory is not neutral but “always for someone and for some purpose”. This is relevant to data which is neither neutral nor reliable without interpretation. AI is currently unable to do that, as it can only process it without a critical approach. The term contaminated information— used throughout this paper—aims to refer to information without a filter or without being contrasted which perverts and corrupts knowledge. Hence, this knowledge being questionable—one cannot count on contaminated information—leads to a democratization of knowledge — discussed below — where information is confusing and produced by everyone, especially since the arrival of the internet.
The Impact – Internet, Technosphere and Democratization of the Production of Knowledge
The Technosphere surrounds us like it never did before, and its presence is growing day by day. Before the internet, people received a limited amount of information through newspapers, radio and television broadcasts along with face-to-face conversations. This has limited their access to information, making it a very different scenario from the one we see nowadays. Online technologies allow the general public not only to have access to huge loads of information but to become, for the first time, a participant in the production and creation of news. Hence, it is arguable that the internet imposes a level of agency never seen before in the hands of the users, making it both fascinating and potentially transformative (Tewksbury and Rittenberg, 2012). Even while this might be a beneficial factor to consider—since a more informed society has usually positive impact—it also poses the disadvantage of a democratization of the production of knowledge that has a contaminated information background.
The democratization of the production of knowledge is a new term that suggests a process in which things that were already scientifically accepted or taken for granted are put into question and seen in the need of having to be justified again. This leads to people using this democratization of the production of knowledge to legitimize their questioning on previous knowledge that was once considered expert knowledge and, therefore, unquestionable. Situations in which people without the proper knowledge question statements from experts without any argumentation or reliable knowledge is a phenomenon that is rising, and internet access is facilitating this process. As put by Tewksbury and Rittenberg, “audiences have more input into the news system and more control over the flow of the news” (Tewksbury & Rittenberg, 2012), allowing the phenomena of fake news and contaminated information to spread and gain popularity among the general public. There is a new parallel reality taking place in which the legitimation of knowledge as true knowledge is not on the basis of expert opinions but on the majority rule or the “trendiness” of a statement (see trendy knowledge below). As a result, knowledge has been reinforced as a power tool and those who feel like they do not have it feel manipulated and sometimes end up creating their own “facts” hoping the majority will follow.
On the whole, it is undeniable that technology alters society by transforming our surroundings, which we then adapt to (Ogburn, 1947) and this also has a repercussion in the societal and political sphere. The way new communications and the change in the production of knowledge inspire developments in society while continuing old ways of communication and facilitating new ones is fascinating. Nonetheless, the “technological determinism”— which states that people cannot resist the effects of technology—must be avoided (Tewksbury & Rittenberg, 2012). Instead, this new reality could be analyzed as a symbiosis between humans and technology, in which social, economic, and political changes facilitate technological change and vice versa. People shape technology and determine the way it is used (MacKenzie and Wajcman, 1985), and while power and technology are perceived as neutral (Winner, 1985), the democratization of the production of knowledge and information democratization are inevitably affected by the Technosphere and the rise of contaminated information, being used as a source of knowledge that is neither neutral nor reliable. The aftermath of this affectation is especially seen in the way politics and societal behavior changes according to the ongoing changes in the information and communication field.
Information and Politics – Information Democratization, Postnormal Governance and The Butterfly Effect
As stated above, the power and the possibilities of the internet when it comes to the production and spread of knowledge pose a huge impact in the societal and political sphere. The concept of information democratization can be defined as “the increasing involvement of private citizens in (…) distribution, exhibition, and curation of civically relevant information” (Tewksbury and Rittenberg, 2012), meaning that citizens are able to have some sort of impact or control over content without the need of producing it. The term has been used to portray the fact that there is a general trend of information being accessible to the general public (Schiller, 1978) and it is being used for several purposes. Among them one can include the production of knowledge—this being the reason why the information democratization is linked with the phenomena of democratization of the production of knowledge mentioned above.
One of the main motives why information democratization is linked to politics is precisely the principles of representative democracy, since being informed up to some degree and having access to information is crucial in order for the general population to perform its civic duties (Berelson, 1952). In contrast, the lack of information has a huge impact on the way the elite manipulates the general public by controlling the access and availability of knowledge (Bimber, 2003). Hence, one can argue that for the democratic system to work, it is imperial to fulfill two conditions: (1) that citizens are well-informed—up to their capacities and understanding—and (2) that the new communication technology—online news, social media, independent content creators—facilitate this task and allow the public to choose a correct representation when it comes to the government. Furthermore, is imperative to take into account that this is only possible when this information is clean and reliable—not contaminated—otherwise the possibility of citizens taking appropriate choices can be put at risk.
One also ought to consider—besides information democratization—two other important factors in which politics and international relations are altered by the new ways of production of knowledge: postnormal governance and the butterfly effect. The postnormal theory indicates entering an uncharted territory in which the “normal” issues surrounding us are changing. According to Serra del Pino, the main issue regarding postnormal governance is that the rules that once used to apply to everyone and were seen as universal are no longer valid in a nowadays society that has become multipolar and multicultural. Because the current moment society is in—its zeitgeist—is a mix of fear, confusion and perplexity, people seem to have lost interest in politics, resulting in being manipulated by information rather than know how to use it.
Populism is directly linked to postnormal politics because people look for everything that provides certainty, and the current democratic system does not. The concern is that the system that once worked is no longer working, and this has a huge impact in society’s current zeitgeist. It is because of this confusion and loss of interest that the social pact is weakened, leaving a void in which populists take advantage of the situation. As society tends to find itself in constant chaos and contradiction—and populism is a natural outcome of this (Serra del Pino, 2017). Consequently, the production of knowledge being available to the general public increases this tendency to populism, and the consequence of this huge amount of information is that, instead of helping the citizens, they just get more confused and end up “falling” in the hands of multiple political actors with malicious intentions.
Furthermore, globalization not only has an impact on the government-citizen relationship but on the state-state relationship as well. The butterfly effect—in chaos theory, defined as the idea that one small act in a complex system can have large effects elsewhere (“Butterfly-effect”, 2007)—is linked with the revolution in information and technology. Consequently, information is instantly processed and spread worldwide, causing an almost immediate impact in multiple world regions (Bryant, 1983). This means that the socioeconomic and political problems of one nation cannot be isolated and must rather be understood in relation with other nation-states (Wilson and Al-Muhanna, 1985) thus having a clear impact in nowadays international relations field. Additionally, one could consider the concept of turbulence by Rosenau, in which is precisely this new transborder reality the one that is causing the power balance to move from public to private actors, creating an authority redistribution in which states do not hold the power they used to anymore (Rosenau, 1990).
Taking that approach into account, one can argue what is happening with the new state of affairs that the spread of information has brought can be linked to this turbulence too. Moreover, the transborder impact is not only reflected in politics but also in the societal sphere. As society transforms and adapts to the new ways of communication, the role of sociology must bend according to its needs in order to understand how to deal with this new humanity that is based in immediacy, transnationality, and liquid individuality. The immediacy of how things are done and perceived and the transnational element of it create a new reality that must be analyzed, especially in the societal sphere. Liquid identity—a concept quoined by Bauman (Bauman in Palese, 2013) is an outcome of these two, and shall be taken into consideration as such.
The Societal Sphere and Liquid Individuality
One can argue that globalization and the new ways of communication have changed forever the way humans interact with each other. While new technologies have had a positive impact on society—globalization has allowed humans to compress time and space regarding communications—it has also brought some significant changes. It is precisely the fast spread of information that has forced society to change as we knew it, bringing a new era of transnationality and immediacy, where not only people have immediate access to information produced by others around the world, but also get to feel part of multiple communities at the same time. As Amin Maalouf quoted:
“The identity cannot be compartmentalized; it cannot be split in halves or thirds, nor have any clearly defined set of boundaries. I do not have several identities, I only have one, made of all the elements that have shaped its unique proportions”. (Maalouf, 1998, p. 10).
This conception of multicultural identity has intensified due to globalization and the access to information, empowering people to abandon the once established concept of manifesting themselves as an individual belonging to a specific community. The main challenge sociology faces nowadays concerning the societal sphere is how the notion of society as it used to be conceived—the geographical scope, language, and religion of a certain group of people—is shifting towards a new reality in which the line that was used before is blurred. Technology changes society, and the impulse exerted by the arrival of new structures, goods and services alters it, destroying the old and creating the new (Schumpeter, 1950). As a result, the more society navigates postnormal times, the older concepts of knowledge and identity are now completely outdated, changing the way one perceives social environments.
Zygmunt Bauman analyzed this phenomenon of globalization and postmodernity, reaching to what he coined as liquid individuality, a term that considers life as transitory, immediate and regards utility over anything else (Bauman in Palese, 2013). Liquid individuality assumes that the transformations that surround the citizens affect human life in a very straightforward way—being a perfect example of how reality is shaped nowadays. Combining both modernity and postmodernity, one finds that the contemporary existence becomes a sort of liquid modernity in which the present and the future are no longer perceived as we used to, thus resulting in postnormality. As per usual with every significant transformational process, there are some consequences that come with it, thus being arguable that the polarity one can perceive in the societal sphere comes precisely due to this new reality shift along with the process of the general public being involved in knowledge production while, at the same time, consuming new forms of knowledge and adapting to it.
Throughout the first sections we have seen how knowledge and knowledge production are becoming problematic and which are the main causes for this phenomenon. However, it is crucial to analyze the implications of this change and make a prospection to which kind of futures this may lead. In order to do that, the following section of this paper focuses on applying all the previous theoretical approaches to provide a more tangible one that allows us to analyze the possibilities of knowledge production in future studies.
The Three Tomorrows
Using the Three Tomorrows approach coined by Sardar, Sweeney and later developed by Serra del Pino (Sardar & Sweeney, 2015; Serra del Pino, 2021) one can question where this crisis of knowledge is leading us to and construct future perspectives on it. Is this idea that we have been carrying since the Enlightenment completely true? Does freedom really come from knowledge? Is the hierarchy of knowledge that has been established fixed or is it, in fact, an ever-changing one? Are our choices constrained to it? These questions are analyzed and challenged through the Three Tomorrows approach, with the aim to provide future options and realities that might be the answer to them. As the names may be misleading, one ought to clarify the Three Tomorrows have little to do with the Three Horizons, beyond the three in the name. For starters, the Three Horizons is a method—telling you what to do, how to do it, and what you should get—whereas the Three Tomorrows is a methodology—an approach if you prefer—which provides theoretical scaffolding so different methods can be used in a way that is coherent with the tenets of postnormal times theory. Second, while the Three Horizons offer a structured way in which different inputs can be combined to generate a consistent output (Curry, 2015), the Three Tomorrows seeks to generate a framework in which different epistemological perspectives can be simultaneously combined to achieve a more thorough future analysis of the object. At last, the Three Horizons can be used to accommodate different times perspectives—although it may be argued that this was not the authors original intention—allowing to articulate elements on a different time scale (Curry et al., 2008). On the contrary, the Three Tomorrows refer to epistemological factors that are independent of time scale; meaning the Three Tomorrows can happen very closely or even simultaneously (Jones et al, 2021).
That being said, the first tomorrow analyses our extended present and how the current knowledge hierarchy shifts from the scientific knowledge to trendy knowledge. The second tomorrow introduces a new element in the game: AI. It proposes a hierarchy shift towards knowledge produced by a machine and—even if as seen before it is not completely reliable—analyzes how humanity puts its trust into it. The third tomorrow—alias the unthought future—goes a step beyond and puts into question this knowledge hierarchy itself. Questioning whether there is really a need for it, or it rather depends on the individuals and their own process and intentions, it argues that knowledge hierarchy acts as a form of domination that may lose its importance in the future. Overall, this section provides three future scenarios that aim to unveil how knowledge production and knowledge hierarchy shifts may lead humanity to unprecedented realities.
The First Tomorrow – Extended Present and the Democratization of Knowledge
Society is currently living in a reality of very high complexity. This new reality is composed of a new diversity of factors—such as technological advancements—and new roles played by different actors that have forever changed the rules of the game. In order to understand how the extended present of the first tomorrow affects our lives, one needs to dive into the multiple issues that surround us and lead us to this very moment. Besieged by ideological contamination and contradictory trends, humanity has experienced a shift in what we considered to be normal towards a new normality or manufactured normalcy—termed coined by Rao and used by Serra del Pino—in which this new reality has been normalized. (Serra del Pino, 2021; Rao, 2015). What once used to be the “reliable” path for knowledge production has been altered by the arrival of Big Data and new technologies, allowing the shift from people being mostly consumers to producers of knowledge. Where science is criticized a knowledge crisis appears, and one finds this future scenario in which scientific knowledge is substituted by the one that has the most popularity or trendiness—referred in this paper as trendy knowledge. The internet has completely altered the terms by which knowledge has been conceived (Kirby, 2006) and one can notice the “erosion of trust in traditional forms of knowledge making is normalized” (Mayo, 2020 – p. 61). Legitimization mechanisms have changed, and it seems that the conditions to produce “true” knowledge are blurred. There are many examples—blogs, online sites, social media networks—of platforms that allow anyone to publish content from anywhere in the world without any filter. This content—that has not been verified, double-checked or contrasted—is then propagated and consumed by others as true knowledge as long as it resonates with their personal values. As put by Mayo, facts and values have become equal elements when it comes to constructing knowledge (Mayo, 2020) and this leads to a new postnormal reality in which people can produce—and consume—unverified knowledge that has an equal—or sometimes even higher—value than scientifically or academically proved knowledge. Society is in a turning point in which what once used to be the norm is fading.
This extended present proves that the trendy knowledge is becoming heavier, leading to a legitimization process that will most likely be marked by it instead of academic methods in the future. Someone could produce knowledge without any professional background and, if it resonated with the majority or became viral enough, it would be adopted as true knowledge. This is already happening and will continue to escalate thanks to interaction capacity growing, as information can now be transferred almost immediately from one side of the planet to another (Buzan and Little, 2000). Up until now, the process of replacing dogma with scientific facts had progressed firmly, meaning that if someone claimed something was scientifically proven, people tended to believe it. Nonetheless, this legitimation is fading away. This demonstrates a very postnormal, contradictory and highly complex reality. It is clearly a moment of transition; as McKibben puts it “the end of the world as we know it” (McKibben, 2020). This leads us to a future in which the initial pyramid of knowledge by Ackoff (see Figure 1), originally marked by Enlightenment, is seized and compressed by new external actors—such as non-academics—that do not have the past requirements but fit the new ones.
Fig 1. Ackoff’s original DIKW
This extended present conducts us on the way to this already-mentioned hierarchy shift towards the trendy knowledge (see Figure 2) instead of classical wisdom. It leads us to a future in which knowledge creation does not need to go through the same filters it used to, as what counts is no longer who accepts it but how many do, creating a shift from qualitative criteria to quantitative one. It will not matter who is behind a statement or if it has been accepted in the scientific world: it will pass as “true knowledge” if accepted by the majority of those who consume it and will be adopted as such.
Fig 2. First Tomorrow
The Second Tomorrow – AI in Familiar Futures
The second tomorrow presents itself with the introduction of a new element: AI as a game changer. This tool that has sparked debate—and is both loved and hated by many—seems to be the hope our society has long searched for when it comes to achieving knowledge that perhaps seemed unattainable until now. AI is—and will continue to—generate non-scientifically based knowledge that is massively consumed and used in different sectors of our society. AI tools are not only used by global actors such as the UNSC (United Nations Security Council), where AI provides them with patterns to identify and monitor violence (IISD, 2023), but daily in our universities and schools via the famous ChatGPT and other AI tools. Linking this phenomenon to the top of Ackoff’s pyramid—in which the initial hierarchy is based on Enlightenment—one can put into question: what is wisdom? Wisdom is having criteria. As seen in the first tomorrow, having criteria is becoming extremely difficult nowadays; and what was once used to legitimize something—the scientific process—is not the first in hierarchy anymore, while what used to be “human work” is being replaced with AI (Kankanhalli, 2020). On top of that, there are many questions whose answers seem unattainable for humans—even through science—because of what seems to be human limitations. Here is where AI becomes society’s savior and promises to bless us with this so-needed-but-unreachable-knowledge in exchange for our trust. In a future reality where it feels like complexity is taking over human capacity, AI becomes the hope that will “solve all of our problems” (Sardar, 2020). Dogma used to work as the trust (Sardar, 2021), but one can argue this is not the case anymore. In a scenario in which polycrisis is ever-present—with globalization, complexity and uncertainty playing a fundamental role—the idea of finding light at the end of the tunnel through AI presents itself as this perfect solution.
We tend to rely on our own beliefs and dogmas when we try to cope with our innermost insecurities and, when relevant dogmas do not exist, we invent them (Sardar, 2021). Assuming we are lost, this familiar future promises AI to be the one that will give us the capacity to decide we are missing right now. Trust in AI takes the highest position in the hierarchy and is perceived as the solution for our knowledge crisis, seen as a way to achieve structure and criteria, along with a new way of producing knowledge. One of the main concerns towards this future is related to the main topic of the present paper, which is the fact that AI does not care or worry about the use of hundred percent reliable information. AI does not possess the human capacity of wisdom—having one own’s criteria—and yet is being used to produce new knowledge that is used in various fields (Kankanhalli, 2020) leading us to a future where the human factor of wisdom is completely erased. Scientifically proven and verified knowledge is replaced by the trust we put in knowledge produced by AI, creating a very complex and non-reliable familiar future. The reality is, in this future, society will not care about contaminated knowledge or the reliability of sources: all they want is answers that provide certainty. No matter the cost.
The reason why a world where populism and demagoguery have such a predicament is because the more uncertain and complex the questions are, the more attractive the simplistic solutions are. When you cannot find criteria, you need to have trust. People will trust AI to provide answers and knowledge about matters in which criteria is not applied, and humanity is putting their future knowledge in the hands of a machine based on trust, not reliable facts. If this goes on, human society will become a spectator rather than the main agent of its own decisions. We will lose our agency as producers of knowledge and put our trust into the hands of AI (Lukyanenko et al, 2022) with the hope that this agent—perceived somehow as “superior” to human knowledge or capabilities—will solve our problems. In this future, the pyramid of knowledge is not just compressed but puts trust in AI in the place of wisdom (see Figure 3). The structure we use to form the base for our knowledge disappears and becomes obsolete, and the concept of wisdom is redefined.
Fig 3. Second Tomorrow
The Third Tomorrow – The Unthought Future of Knowledge Hierarchy
Up until now, it has been assumed—both in the first and second tomorrow—that there is, in fact, a hierarchy of knowledge that exists and dictates our present and future. However, is it really this way? Knowledge has a background of purpose and intentions and knowledge management and demand depend on who uses it and for which motivation (Abubakar, A.M., et al. (2019). Depending on one’s interests, we tend to give different degrees of importance to certain kinds of knowledge. The unthought brings us to a future in which knowledge does not really have a hierarchy. Society is so used to believe there is a path that has already been chosen towards obtaining knowledge that forgets there is always more than one truth depending on how you formulate the question.
Hierarchies hide power structures, and it seems that we have always conceived knowledge as intrinsically positive and ignorance as a void that must be filled. Knowledge as light, ignorance as dark. But it may not be that way. Several authors that belong to Critical Theory such as Cox and Strange, have analyzed how knowledge—or the absence of it—is important because it affects your preferences and can be a form of domination. It is usually presented as neutral but it’s not (Strange, 1988; Cox, 1981). Knowledge is political, and its importance must not be undermined. Knowledge is the structure that shapes our society, and the structure always responds to a certain status quo (Samuelson and Zeckhauser, 1988).
At this point, there is a clear need to reformulate the question. The issue is not which knowledge is better than another, or which one will save us. The question is up to which point our agency plays a role in knowledge production, how the structure affects us, and which process will we follow to obtain knowledge in the future depending on our personal preferences. This unthought future brings into the table the possibility of knowledge conception being different to what we have conceived until now. Starting on the assumption that people search for knowledge with different objectives and uses it for different purposes, the proposal of a knowledge hierarchy does simply not work anymore. Demand knowledge—seeking a different type of knowledge according to one’s preferences (Academic, Trendy, AI)—seems to be the driving force to reclaim human agency towards knowledge. In this sense, knowledge stops being a form of domination—there is no more knowledge weaponization—but rather a reality in which society reclaims its agency by using all the previous knowledge acquiring methods depending on one’s own preferences. Linking this idea to Sardar’s approach—in which unthought futures provide an “antidote” that emerges from perspectives we did not even think about (Sardar, 2021)—demand knowledge might be not only what we need in the future, but the reclaim of human agency that impacts both the extended present and the familiar futures. The ideas of trendy knowledge and AI trust in knowledge creation might end up having an unimagined outcome: knowledge—as we perceive it—might not be intrinsically hierarchical nor imposed. This idea provides us with the opportunity to reclaim our agency (Sardar, 2021), which the first two scenarios do not.
The crisis of knowledge is solved in the unthought by being able to change our ways of learning and embracing the fact that, in an era in which technology provides us with so many paths, the classical conception of knowledge might not be what all humans need. Instead of spending so many years forced to learn and using forced processes, citizens reclaim their need to be provided with different tools that allow them to navigate sources and research about their own desired knowledge. In this scenario (see Figure 4) knowledge acquisition presents itself in a wheel—rather than a pyramid—a that contains all previous knowledge conceptions—Enlightenment through scientific knowledge, trendy knowledge, and AI trust.
Fig 4. Third Tomorrow
Human agency is the one that chooses, and demand knowledge is the driving force. Even if still constrained by the structure—the agency is limited since one can choose among the given options—humans driven by demand knowledge and their own agency turn this wheel and choose according to their preferences the option they prefer or aligns more with their own purposes. The reality that the unthought future presents is that there is no need for an established hierarchy, but rather different knowledge paths based on demand knowledge and agency that include both the trendy knowledge and AI trust presented in the first and second tomorrow. This allows to regain agency when it comes to the paths of knowledge production, and diversifies the multiple options one has access to. As seen in Figure 1, 2, 3 and 4, the initial idea of Ackoff’s pyramid transforms through the different scenarios maintaining some sort of hierarchy but changes completely in the third tomorrow. The third tomorrow can be visualized as a multiple-choice future rather than a pyramid, where future conceptions of knowledge will lead to a more diverse and open future possibilities.
The Three Tomorrows’ Aftermath
As seen throughout the different scenarios, the possibilities are huge and very distant from one another. It is arguable that the most important to consider is human agency. Human decisions and preferences shape the way we obtain and treat knowledge, and this is no different in the future scenarios presented above. In the first tomorrow we can see how, according to the hype or trendiness of something, the preferred type of knowledge is established. This extended present correlates to the reality we live in nowadays, in which technology and the transborder element of our society make it possible for something produced by anyone to become viral despite its origin.
The second tomorrow introduces AI as a game changer and considers human wishes and aspirations towards a knowledge that may be unattainable without it. In this approach, society decides to put its trust into an external actor—AI—that while does not always provide reliable facts, is able to provide what we need: solutions to problems that seemed unsolvable. While AI is already present in our lives, what this second tomorrow depicts is the possibility of a reality that goes beyond what we have imagined. A reality in which AI takes over our decisions, and with the power of our trust, decides on multiple areas of our life using data and information that has not been contrasted neither possesses the human element of the initial conception of wisdom.
The third tomorrow goes beyond every conception that we deem as established. It takes down the pyramid and offers the possibility of different options according to multiple preferences. This future reality is not just about choosing what is best or establishing a podium but acknowledging that not everything is black and white. This scenario embraces diversity and enhances human agency by giving more options to choose from, not establishing a “top” one. And while human agency is still constrained by options and the structure of the system we live in, the third tomorrow explores the possibility to get rid of the hierarchy of knowledge. It ultimately allows us to choose from the multiple prospects the future postnormal reality and its complexity has to offer.
Conclusions
All things considered, one can see how the new ways of production of knowledge—specifically Big Data and AI—affect directly both into the sociological and the political sphere. Contaminated information—both its production, use and spread— alter society as it was once conceived, leading it into this new reality where uncertainty has become the normalcy. Even if a difference between what it used to be and what it is must be acknowledged and accepted, one finds that even if former knowledge gathering methods cannot deal completely with the vast amounts of data that currently must be dealt with, some adjustments need to be made in new methods to fight unreliability and uncertainty.
After going through the multiple scenarios this crisis of knowledge can unveil, one can argue that knowledge—as we know it—has fallen in what Mayo and Miah call a zombie discipline (Mayo and Miah, 2021). The conception of knowledge—both in its production and consumption—does no longer fit actual and future definitions, and it needs to be renovated. The Three Tomorrows approach portray the different possibilities of knowledge production’s future along with the multiple variables that one ought to consider when prospecting new realities. The different factors that drive hierarchy in the First and Second Tomorrow and the presence of the structure in a non-so-hierarchical Third Tomorrow portray how the democratization of knowledge impacts society on multiple level and changes our conception of it.
Furthermore, as seen throughout the paper, it is arguable that the way in which society was once analyzed has become obsolete, and new approaches must be found to navigate the ongoing reality. Changes in the way humans organize themselves happen along with the development of new technologies, and it is pivotal to ponder all the elements that make it happen. New ways of producing knowledge bring uncertainty, complexity and are full of unknowns, and analyzing them is crucial in order to prepare for upcoming realities. Seeing how our ancient conception of knowledge transforms into a completely different one might tremble the foundations of society as we know it, but it has proven to be an inevitable path that we will have to walk. A balance between the old and the new must be found to be able not to overcome uncertainty—as it is an intrinsic part of nowadays postnormal society—but to be able to navigate it.
Acknowledgements
I would like to acknowledge and thank Jordi Serra del Pino, Research Director at the Centre for Postnormal Policy and Futures Studies for guiding and encouraging me through this publication, along with assisting me with the academic background I needed on postnormal issues. This journey would not have been possible without you. I would also like to thank Professor Federico Guerrero Cabrera for his International Relations insight on the research and providing the sociopolitical key factors I needed for this paper, you supported me from the beginning. At last, I would like to thank Onno Gerard Hubert Seero, for trusting my vision and motivating me throughout my IR studies.
References
Abubakar, A.M. et al. (2019). Knowledge management, decision-making style and organizational performance. Journal of Innovation & Knowledge, 4(2), 104—114. DOI: 10.1016/j.jik.2017.07.003
Ackoff, R. L. (1989). From data to wisdom. Journal of Applied Systems Analysis, 16, 3–9.
Berelson, B. (1952). Democratic theory and public opinion. Public Opinion Quarterly, 16, 313–330.
Bimber, B. (2003). Information and American Democracy: Technology in the Evolution of Political Power. Cambridge University Press.
Bryant, R.C. (1983). Eurocurrency Banking: Alarmist Concerns and Genuine Issues. OECD Economic Studies, 1, 7-39.
Butterfly-effect. (2007). In Oxford Reference dictionary. Retrieved from https://www.oxfordreference.com/display/10.1093/oi/authority.20110803095538985
Buzan, B., & Little, R. (2000). International Systems in World History: Remaking the Study of International Relations. Oxford University Press.
Cox, R. W. (1981). Social Forces, States and World Orders: Beyond International Relations Theory. Millennium 10 (2), 126–155.
Curry, A. et. al. (2008). Seeing in Multiple Horizons: Connecting Futures to Strategy. Journal of Future Studies, 13(1), 1—20. https://jfsdigital.org/articles-and-essays/2008-2/vol-13-no-1-august/articles/seeing-in-multiple-horizons-connecting-futures-to-strategy/
Curry, A. (2015). Searching for systems: understanding Three Horizons. APF Compass, January Methods, 11—13.
Hariri et al. (2019). Uncertainty in big data analytics: survey, opportunities, and challenges. Journal of Big Data, 6, 1— 16.
Horan, C., & Finch, J. (2016). The Concept of ‘Knowledge Creating’: Re-conceptualising the Problems of Knowledge Transfer and Creation Processually. British Academy of Management, 6th-8th September 2016
IISD (IISD SDG Knowledge Hub). (2023). Security Council Debates AI’s Impacts on Peace, Sustainable Development. Available at: https://sdg.iisd.org/news/security-council-debates-ais-impacts-on-peace-sustainable-development/#:~:text=Acknowledging%20that%20even%20the%20UN
Jones, C., Serra del Pino, J, and Mayo, L. (2021). The Perfect Postnormal Storm: COVID-19 Chronicles (2020 Edition). World Futures Review, 13(2) 71-85. DOI: 10.1177/194675672110273
Kankanhalli, A. (2020). Artificial intelligence and the role of researchers: Can it replace us?. Drying Technology, 38(12), 1539—1541. DOI: 10.1080/07373937.2020.1801562
Kirby, A. (2006). The death of postmodernism and beyond. Philosophy now, 58, 34-37.
Knight, FH. (1921). Risk, Uncertainty and Profit. The Riverside Press Cambridge.
Kuhn, T. S. (1962). The Structure of Scientific Revolutions. Second Edition. The University of Chicago
Leonelli, S. (2020). Scientific Research and Big Data. The Stanford Encyclopedia of Philosophy, Summer 2020 Edition.
Lukyanenko, R. et al. (2022). Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities. Electron Markets, 33. DOI: 10.1007/s12525-022-00605-4
Maalouf, A. (1998). Les identités meurtrières. Grasset.
MacKenzie, D., & J. Wajcman, (eds.) (1985). The Social Shaping of Technology. Open University Press.
Mayo, L. (2020). The Postnormal Condition. Journal of Future Studies, 24(4), 61—72. DOI: 10.6531/JFS.202006_24(4).0006
Mayo L., & Miah S. (2021). Zombie Disciplines: Knowledge, Anticipatory Imagination, and Becoming in Postnormal Times. World Futures Review, Special Issue – Postnormal Matters 0(0) 1—15. DOI: 10.1177/19467567211025546
McKibben, B. (2020, July 31). The end of the world as we know it. Times Literary Supplement, 4-5.
Ogburn, W.F. (1947). How Technology Changes Society. The ANNALS of the American Academy of Political and Social Science, 249(1), 81-88. DOI: 10.1177/000271624724900111
Palese, E. (2013). Zygmunt Bauman. Individual and society in the liquid modernity. SpringerPlus, 2:191. DOI: 10.1186/2193-1801-2-191
Raine, L., & Wellman, B. (2012). Networked. The new social operating system. MIT Press.
Rao, V. (2012). Welcome to the Future Nauseous. Ribbonfarm. Available at: https://www.ribbonfarm.com/2012/05
Rosenau, J. (1990). Turbulence in World Politics. A Theory of Change and Continuity. Princeton University Press
Samuelson, W. & Zeckhauser, R. Status Quo Bias in Decision Making. Journal of Risk and Unceirtainty, 1(1), 7—59. Available at: http://www.jstor.org/stable/41760530.
Sardar, Z & Sweeney, J.A. (2015). The Three Tomorrows of Postnormal Times. Futures, 75 (2016) , 1-13
Sardar, Z. (2020). The smog of ignorance: Knowledge and wisdom in Postnormal times. Futures, 120, 102554.
Sardar, Z. (2021). On the Nature of Time in Postnormal Times. Journal of Future Studies, 25(4) 17—30. DOI: 10.6531/JFS.202106_25(4).0002
Schiller, H. I. (1978). Decolonization of information: Efforts toward a new international order. Latin American Perspectives, 5, 35–48. DOI: 10.1177/009458X7800500103
Schumpeter, J.A. (1950). Capitalism, Socialism and Democracy. Harper & Row.
Serra del Pino, J. (2017). Postnormal Governance. In Sardar, Z. (ed). The Postnormal Times Reader. Centre for Postnormal Policy & Future Studies, pp. 242—251
Serra del Pino, J. (2021). Building Scenarios With the Three Tomorrows. World Futures Review, 0(0) 1—14. DOI: 10.1177/19467567211025562
Strange, S. (1988). States and Markets. Pinter Publishers.
Tewksbury, D., & Rittenberg, J. (2012). News on the Internet: Information and Citizenship in the 21st Century. Oxford University Press.
Wilson, L., & Al-Muhanna, I. (1985). The Political Economy of Information: The Impact of Transborder Data Flows. Journal of Peace Research, 22(4), 289—301. DOI: 10.1177/002234338502200402
Winner, L. (1985). Do artifacts have politics?. In MacKenzie, D. and Wajcman, D. (eds.). The Social Shaping of Technology (pp. 26–38.). Open University Press.