On the promotion of academic freedom as a response to the decline of trust in science

Although our societies still rely on scientific truths, (Wellcome, 2020) science has been affected by an emerging crisis of legitimacy, to which it is important to respond. With the term of “Science” we refer to hard sciences – the so called “Science, Technology, Engineering, and Mathematics” (STEM) – disciplines as a field of knowledge that has been artificially separated from the wider domain of the production of knowledge. In the paper we show that, to ascertain the objectivity of scientific truths, scientific research has been extracted from the sphere of cultural subjective productions such as humanities and the arts. We will explain why this separation is problematic.

A decline of trust in science might have serious consequences; for instance, it could worsen the response to global challenges and weaken governmental policies meant to cope with the numerous hurdles our societies are facing. Especially since the COVID-19 pandemic, the issue has been discussed by different organizations and institutions such as the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the European Parliamentary Research Services (EPRS) that expressed concerns over scientific and academic freedom (Lackey, 2018, Magni, 2021). In the current context, it is paramount to protect the scientists’ right to publicly communicate their findings and warnings, as well as to carry on their research programs without external constraints or obstructions. Different kinds of challenges to scientific and academic freedom are identified (Vrielink et al., 2023; Borg-Barthet et al., 2021) and classified as follows: (1) internal pressures, from within higher education and research institutions; (2) external pressures, such as those from the industrial complex in key sectors, including defense, energy or pharmaceutical, and supranational institutions, e.g. the European Commission (ALLEA, 2023); (3) societal pressures generated by the connection between scientific research and governmental policies, via, e.g. social media); (4) geopolitical pressures, such as, for instance, the competition for technological supremacy among global powers. In Vrielink et al., (2023) more recent trends are also mentioned: “New challenges for academic speech have emerged. Without any ambition of being complete, we highlight growing tensions concerning deplatforming and so-called “cancel culture”, research funding being increasingly focused on certain topics (thereby implicitly raising hurdles for research in the less “fashionable” or “less lucrative” areas), the complex impact of artificial intelligence on research, and intimidation of scholars by activists (from all sides of the political spectrum).” Dedicated studies (Scientific Foresight Unit of the European Parliament, 2023) have demonstrated that the situation has been worsening in the last years, with a negative impact on the quality of research as well as on the working conditions of researchers. Serious concerns are expressed about the space to argue in favor of formulated hypotheses, and about the shrinking opportunities to fund programs that do not align with the interests of donors and investors. Moreover, scientists are increasingly invited to public debates where often the presented “facts” are immediately interpreted as arguments supporting or contesting governmental policies (recall, for instance, what happened at the beginning of the COVID-19 pandemic). While the latter are based on sets of assumed scientific truths, any acknowledgement of the hypotheses’ refutability is taken as an expression of political engagement and ideological partisanism (Comité d’éthique du CNRS, 2024). As a consequence, scientists are suspected of taking part in wider strategies for manipulating beliefs and are therefore exposed to often aggressive criticism. The consequence is that, given the spreading attacks on social media, researchers feel their freedom of expression to be constrained and their capacity to address global challenges restricted. Preliminary work, seminars and conferences (Science Media Hub, Academic Freedom: The State of a Fundamental European Value, 2023; UNESCO, Conference on Scientific Freedom and Responsibility, 2023) led to outlining guidelines (UNESCO, UNESCO Recommendation on Science and Scientific Researchers, 2017; Bonn Declaration on Freedom of Scientific Research, 2020; Jancova and Heflich, 2023; European Parliament 2024; Harding, 1992) for improving researchers’ freedom, both within and outside laboratories and academia. The aim of these documents is to define scientific freedom, establishing criteria for its evaluation, and proposing regulation for protecting the autonomy of research. The expected effects are the improvement of the environment in which scientists work and, as a consequence, their feeling of confidence and security. Liberating scientific activities from external pressure and internal power dynamics would assure the objectivity and neutrality of the findings that are supposed to orient collective practices and governmental directives. It is evident that what is at stake is the legitimacy of public policies as it depends upon the authorities’ efforts to respect and reinforce academic and scientific freedom, and hence neutrality. The UNESCO Recommendation more specifically details that the university should be autonomous from the state as “a necessary precondition to guarantee the proper fulfillment of the functions entrusted to higher-education teaching personnel and institutions” (§ 18). This implies that, for scientific knowledge to be trustworthy, scientists must be detached from any other concern than ascertaining the facts.

However, as discussed for example by Harding (Harding, 1992), such an assumption is a myth that, rather than assuring absolute objectivity, justifies the superiority of scientific knowledge over other means for representing the world. Harding argues that scientists usually come from homogeneous social backgrounds and belong to similar ethnicities and genders. As a consequence, the universal value of the scientific world view is a justification for imposing true beliefs on communities whose opinions and practices are often contaminated by dogmatic doctrines. Yet, the belief in complete independence of scientific knowledge and the scientist’s cultural inscription is itself dogmatic. This presumed neutrality legitimates the impartiality of governmental decisions for maximizing social welfare. As we will explain in the next section, this entanglement between the validation of scientific knowledge and the justifications of the governmental procedures defines a paradigm that is probably no longer adequate to the needs of the present; instead, it appears ill-suited to the complexity of our multicultural global and networked society and the challenges it faces. This difficulty emerged in the conferences organized by UNESCO and EPRS, where invited speakers such as Kwadwo Appiagyei-Atua (UNESCO, Academic Freedom and Freedom of Science, 2023a) and Frank Miedema (Panel for the Future of Science and Technology STOA, 2024) suggested that, to restore trust in science, it would be important to establish a more democratic and participatory framework. Rather than pretending that truth is independent from the way in which problems are formulated, the proposal is to let scientists conduct their research programs in agreement with the demands of communities, and the plurality of their concerns and values. As such, it would be a matter of authorizing everyone, including non-scientists, to express themselves about the research to be pursued and funded.

We will articulate our discussion on these proposals in more detail in the last part of this work; for now, we would like to highlight that one of the reasons frequently identified by researchers for explaining their uneasiness is the competitive pressure they are exposed to in the current system predominantly based on quantitative assessment criteria. This concern is usually neglected in the discussions we mentioned, although scientists consider it as one of the reasons for the experienced lack of autonomy as well as for the undermined quality of the investigative process (Tiokhin et al., 2021; Hill et al., 2024). From this standpoint, the whole system for producing knowledge as a commercial informational good emerges as one the causes for the diminishing trust in science not only from the general public, but also from the researchers themselves. Under the pressure to publish more and faster, in the attempt to fulfill quantitative evaluation criteria, scientists often feel that the objectives of the research are incompatible with the current conditions for career progression (Moher et al., 2018). We think that it is important to consider the spreading discontent within the scientific community, which suffers impediments to its right of expression, and the adverse effects of the system currently in place to evaluate the quality and impact of scientific activities. This diffused dissatisfaction suggests that science needs substantial reforms (Science in Transition, About Science in Transition, 2013). Engagement in social issues is required to replenish the credibility and role of science (Harding, 2023), as well as to revitalize the production of knowledge capable of making a difference in society. We argue that listening to scientists’ concerns, feelings and wishes is an important first step in the direction to granting the necessary freedom of expressing any disagreement with institutional policies or evaluation procedures. This would reduce the subtle pressure that forces to tackle scientists’ issues solely by protecting the right for self-expression and self-determination, while preventing political measures that would demand a radical transformation of the knowledge production system. In other words, it seems to us that the demand for a paradigm shift in knowledge production, aligned with a broader call for a profound social transformation, is crucial if we wish to rely on science to face the present serious challenges such as the impact of human activities to the environment and spreading inequalities.

In this paper, we propose a widened framework aimed at reviving trust in science by addressing the underlining reasons for scientists’ discontent. We convey that the latent crisis of legitimation is not simply due to external causes but, more deeply, stems from the full unraveling of the paradigm inaugurated by the logical empiricism integrated into the present competitive metric of assessment. In the next sections we attempt an historical reconstruction of the development of this paradigm, and we highlight some symptoms of its current ailing state. In the last section of the paper, we propose a preliminary scheme to rekindle trust in science through a more democratic approach and a transformation of the criteria used for assessing the value of knowledge. By doing so, we aspire to bolster the remarkable efforts of the international organizations and commissions dedicated to confronting the concerning decline of trust in science.

The crises of the reciprocal legitimation of knowledge and power

During modernity, while physics was considered to provide an objective description of sensible reality, scientific activities focused on justifying the truthfulness of this knowledge were regarded as speculative philosophy. For example, Descartes compared the system of knowledge to a tree: the roots are metaphysics, the trunk is physics, and the branches are all other sciences the principal of which are medicine, mechanics and morals. Recognizing the foundational role of metaphysics, Fichte defines philosophy “science of knowledge”. However, metaphysics rapidly started to be perceived as akin to superstition, namely a lower form of knowledge than science, opening a debate on the possibility of justifying the truth of scientific knowledge on scientifically acceptable bases (Is a scientific science of science possible? For instance, cognitive science are today trying to provide a scientific description of the process allowing humans to develop reliable descriptions of reality). Logical positivism was the first attempt to detach scientific knowledge from external philosophical legitimation. The idea of grounding the value of theories on a set of definitions derived from the linguistic analysis of the hypotheses was deemed the most reliable alternative by the scientific community. Accordingly, any meaningful theory should be derived from axioms in order to achieve a coherent system of knowledge. From these assumptions, Carnap argued in favor of the meaninglessness of metaphysical narratives and developed a logic of induction: a rationally valid procedure based on experimental proofs, meant to objectively justify the true worth of the hypotheses. Accordingly, knowledge was supposed to develop by systematically updating the probability of different acceptable predictions (i.e. those that can be derived from the axioms and the definitions of inductive logic), which were validated based on new and more accurate experimental observations. This process would allow to progressively select the most trustworthy predictions as the process continues. Rational decisions should be based on these most probable expectations, enabling a more “objective” (shared by common consensus) assessment of the risk. It is worth noting that within this epistemological framework, no hypothesis should be held as “absolutely true”. Even though some hypotheses may be considered more reliable by the scientific community at any given time, rational beliefs might change somewhat unpredictably, due to the unforeseeable acquisition of new information. Nonetheless, the procedure that leads to such developments is considered as universally valid (based on the cognitive law of induction). Despite the impossibility of establishing an axiomatic foundation from which all the acceptable scientific propositions can be derived, the project for autonomous legitimation of scientific knowledge was successfully developed, starting from cybernetics, information and decision theories. Notably, the process that allows complex systems such as animals and humans to adapt to the environment through interaction and information exchange has been modeled as information. In this framework, scientific knowledge is the result of an inductive learning process through which useful predictive hypotheses are generated to optimize interactions, practices and information exchanges. Moreover, by scientifically acknowledging the cognitive process, science was supposed to justify its own productions as an adaptative progress. Without entering details or attempting to reconstruct the entire historical narrative surrounding the “postmodern” paradigm for scientific legitimation (Lyotard, 1984), the following sections will explore its main features and identify the primary factors contributing to its current crisis.

The crisis of the cybernetic paradigm in legitimizing governmental institutions

Cybernetics or systems theory allowed extending scientific inquiry to new complex objects, such as living beings and societies, while comparing them to informational machines. As Niklas Luhman pointed out (Luhmann, 2023), this led to applying a scientific approach to governmental techniques with the aim of improving the overall efficacy and legitimization of policies in return. According to this view, social issues can be associated with technical problems and solved through a better interaction among the different sub-systems of the social machine, to assure a harmonious functioning of the communication network. As a consequence, scientific research began to legitimize governments’ decision-making procedures to promote people’s trust in institutions. Conversely, the success of governmental strategies in solving social issues legitimizes scientific hypotheses as well as the technical framework on which they are based upon. For instance, we can see the neoclassic theory of the market equilibrium as a framework based on perfect communication among rational agents. The latter optimal decisions are based on the information transmitted by prices, while the informativeness of prices is guaranteed by the sum of individual rational decisions. In a market at the equilibrium, any rational agents enjoy equal chances of maximizing utility, as a consequence, nobody would be motivated to deviate from the convention. Fast technological development has been welcomed as a means for promoting general productivity and welfare by improving the logistics of communication and information exchanges. However, this has entailed a depoliticization of society and a politicization of techno-scientific research; if formulated as and reduced to technical issues, social problems can only receive a “scientific” solution coming from experts. Today, we are detecting the limits and experiencing the crisis of this model based on a reciprocal legitimation of political power through knowledge, and of scientific knowledge through its contribution to the stability of political institutions. On the one hand, it is evident that if a statement describing a real situation is true, any prescriptive statement derived from it will be considered just. On the other hand, scientific hypotheses often serve as justifications for policies; consequently, the critiques directed at governmental policies are frequently centered on challenging the validity of the scientific facts on which the policies are based. For instance, during the COVID-19 pandemic, it was clear that the policies were criticized for the uncertainty of guiding scientific hypotheses; conversely, scientists were accused of imposing truths that were supporting specific political views. While scientists are increasingly engaging in public media debates, they face the difficulty of separating the objective assessment of plausible hypotheses and their subjective opinions on the use of research findings. This raises a critical question: when they do not agree with authorities’ measures, plans and regulations, should they limit themselves to the presentation of experimental findings or should they express their concerns? The former option conforms to the neutrality that is demanded to ensure that no other interest rather than truth-seeking motivates the research. However, the latter option conforms to the moral duty for responsible engagement with social challenges, issues and threads. The dilemma is particularly evident in the discussions on climate change, where conflicting governmental strategies rely on different interpretations of scientific “facts”. In this context, researchers are expected to support certain views in public without expressing opinions on the consequences of policies derived from their research findings (Adda et al. 2023). Nevertheless, scientists are contested since the hypotheses they present as “objective”, in fact represent arguments in support of specific policies. Hence, they are suspected of participating in the political game of persuasion and prioritizing personal interests over the impartiality of truth. For this reason, an increasing number of scientists, based on their results, are expressing their discontent with the governmental measures and the dangerous consequences of certain technologies. They do not only feel compelled to spell out their disagreement with the political, social and economic applications of their research, but they also feel morally obliged to propose alternative solutions oriented towards more radical transformations of collective modes of existence (Scientist Rebellion, 2023). Accordingly, scientists affirm that the motivation of selfless research originates from the desire to contribute to the transformation of specific cultural, social and political situations rather than advancing personal power or economic gain. Moreover, they assert the right to reclaim the scope of their work from which they have been alienated within a system that uses scientific outcomes for legitimizing projects and productions they do not wish to support. From this standpoint we understand why a movie like “Oppenheimer” is relevant in the present context. If objectivity is to be achieved by preserving inquiries from external influences, pressures, and personal political agendas, then isn’t the will to constructively shape the future according to one’s moral judgment that provides research with scope and meaning?

On the one hand, researchers are supposed to present objective facts, while on the other hand, they feel need to express their judgment on the policies based on those facts, as the application of such policies might entail counterproductive effects. Accordingly, we suggest that the discussions on scientific freedom is extended to the issue of granting scientists the possibility of orienting or controlling the way in which their findings are actually used. While the goal of the proposed regulations is to assure the autonomy of research by limiting external (political or economic) and internal pressures (for instance, cultural or gender prejudices), they might have the side effect of compelling researchers to lose sight of the finality of their work and to drop their will to contribute to transform reality according to their subjective idea of justice. Can we consider as “good” a science that is disengaged from the intention to improve reality according to specific world views, fears and hopes?

Rather than contributing to the transformation of the destructive consumerist framework of innovation, researchers are driven (for example by the aforementioned external pressures) to participate into the production of commercial products, such as technological devices, the diffusion of which amplifies the dangers of the exclusive pursuit of economic returns in the short term. However, they are pushed to accept the rules of the game to access the resources essential for their research, yet they often see how these rules effectively impede them from developing research that could make a real difference in people’s lives. As such, scientists are often confronted with the choice between two unviable alternatives: either they abandon the pursue of independent and unbiased research to stand a chance of an academic career or follow their natural vocation which would prevent them to reproduce the mechanism they wish to change. In various contexts, the need to follow an independent research agenda and develop alternatives to the procedures and technologies aligned only to the interests of political and economic powers is often systematically hindered. The researchers’ dilemma is frequently exacerbated by the system’s rewards to compliant researchers for the prestige of contributing to unfolding the political and economic agenda. These risk to become short-term rewards that end up penalizing the quality and the value of scientific knowledge in the long-term (Carignan, 2024).

The constant pressure for acquiring research funding, generates a growing frustration among researchers (Gross and Bergstrom, 2019), which should be taken seriously, as it represents a critical point of discussion for questioning the administrations. As we argued, governments cannot justify their decisions and policies without exhibiting the full support of experts. As a consequence, the transition to a more open framework for knowledge production would, at the same time, improve trust in science and governance, enabling this necessary change. In particular, the possibility of orienting the application of research results to responsibly transform the dominant modes of existence would restore the meaningfulness of the scientist’s activity. At the same time, governments would be seen more trustworthy if they would seriously demand radical changes, rather than responding with regulations often aimed at preserving the existing framework.

The crisis of the game-theory as a paradigm for legitimizing technological innovation

While different players are involved in the production and assessment of scientific research, research findings are increasingly valued in relation to their economic worth. This generates a competitive arena which can be usefully analysed within a game theory framework. For this reason, it is useful to introduce our historical reconstruction of such context with a short excursus on the theoretical background of game theory.

Game theory, first formalized by Von Neumann and Morgenstern (1940) and gradually developed to embrace more realistic situations of imperfect information, allowed extending scientific inquiry to the field of economics. The formal model based on a rational agent making decisions in the market was derived from the procedure to select the most probable predictions and align conclusions and beliefs with new observations. As we said, by following the rules of inductive reasoning, researchers reach consensus on the hypotheses that are more likely to be correct according to such rules and measure their degree of objective confirmation based on experimental proofs. According to Carnap, the rules of inductive reasoning were supposed to be deduced by the observation of the way in which scientists operate and such a procedure can be elucidated through the linguistic analysis. Later, thanks to the works of Ramsey, de Finetti and Savage, the rules for inductive reasoning were deduced by observing the way in which decision-makers treat information to establish the probability of future events in such a way to calculate the probability their actions lead to the desired consequences. AI basically works following the same procedure. However, as Norbert Wiener (Wiener, 1950) pointed out, “the laws of induction in logic cannot be established inductively. Inductive logic, the logic of Bacon, is rather something on which we can act than something which we can prove, and to act on it is a supreme assertion of faith”.

By sharing their observations and findings, researchers compare plausible alternatives, and their conclusions tend to converge towards the functions that more accurately describe the pathway to unfolding specific phenomena. The objectivity of a predictive hypothesis (function) arises from an agreement on its likelihood. As a consequence, the hypotheses considered more reliable become to constitute what is described as “common knowledge”. Common knowledge is the reason why the language of scientific theories can be embraced to determine which consequences (future occurrences) are entailed by the premises (present situation). This shared body of theories induces any member of the community to expect the occurrence of the same series of events given a certain present situation. Accordingly, symmetrically informed agents can predict each other’s decisions assuming that they seek to maximize utility. This is the reason why players in classic game theory can reach equilibrium. According to Freedman and the School of Chicago, this is also the reason why rational agents in the market can coordinate their respective decisions in a way that every agent enjoys equal chances to maximize utility. A market in perfect equilibrium is therefore a fair game as its foundation is based on complete information: each participant knows that everyone else makes decisions based on the same predictive hypotheses and accesses the same public and free information, such as prices.

It is evident that real markets differ profoundly from this ideal situation. In real markets, agents formulate their strategies according to predictions based on information other than prices. In such markets, potentially more rewarding strategies are continuously tested by innovators and their presence in the market animates an imperfect competition where everybody seeks to increase the efficacy and efficiency of their productive activities. Indeed, this very competition creates opportunities for some agents to secure higher returns than others, supporting economic growth. The latter would be impossible without constant innovation: the introduction of new efficient strategies by innovators motivates others either to imitate it or to respond with potentially more rewarding approaches. Rather than ensuring perfect predictability of future market states, the result is uncertainty: the risk associated with decisions cannot be objectively assessed since agents cannot predict each other’s moves, which depend on different hypotheses and information. This explains the actual economic value of information.

To develop new lucrative strategies, agents must invest in costly research aimed at anticipating future needs and in technologies that are likely to more efficiently produce the most desirable goods. The costs of research and development that are supposed to increase general welfare (i.e. the wider availability and affordability of needed goods) motivate agents to privately profit from their information, assigning it a price. This price is determined by the information’s novelty and its usefulness for the development of other agents’ strategies. As a consequence, information becomes a consumption good that loses value with its diffusion, motivating investments in further research. The use of new information leads to an unpredictable evolution of the situation, and hence to the need to revise hypotheses depending on the predicted consequences of the adopted innovations. It becomes apparent then how, in this framework, scientific research is valued in relation to the economic worth of the information it provides.

The technological application of scientific research, and its economic outcome, justifies the authority of science and its perceived superiority over other modalities of knowledge production. Conversely, the selection of more reliable hypotheses among the plurality of the competing ones, depends on the investments of developers and entrepreneurs. The validity of a new trustworthy hypothesis depends, in fact, on the capacity to produce convincing experiments to influence peers. Today, the availability of sophisticated and costly technologies is often the condition for obtaining peers’ consensus on the scientific merit of a research study; as such, the access to those technologies determines the winner among competing theories (Lyotard, 1984). As a consequence, the alignment of scientific research to the agenda proposed by funders provides laboratories and their leaders with the necessary resources to prove a theory and its merit.

As innovators compete to develop the most efficient solutions, often at the expense of other potentially valid options with lower access to funding, similarly, scientists compete to obtain consensus from their peers and the wider scientific community. The rules of this game are based on measurable criteria such as the number of research papers published in high-impact journals. These publications are supposed to reflect the agreement of the experts on the relevance of the findings, i.e. the net worth of the newly produced information and its potential impact both in the scientific community and in the wider world. The anticipated impact of the winning hypotheses immediately translates into the economic value of the funds and grants received, which are a direct indication of how much the market is willing to invest in scientists (the producers of the information) to exploit their research findings. However, as previously noted, investments are necessary to increase the chances of validating a theory among peers. Therefore, research topics are selected by investigators to align with the interests of the entrepreneurial elite to increase their chances of producing information that is relevant to those stakeholders. This may lead researchers to feel prevented from producing knowledge with an actual use value, as they are constrained to produce information that is assessed in terms of exchange-value. As Lyotard put it (Lyotard, 1984):

“The relationship of the suppliers and users of knowledge to the knowledge they supply and use is now tending, and will increasingly tend, to assume the form already taken by the relationship of commodity producers and consumers to the commodities they produce and consume – that is, the form of value. Knowledge is and will be produced to be sold, it is and will be consumed in order to be valorized in a new production: knowledge ceases to be an end in itself, it loses its ‘use-value’.”

Officially, the choice of a research program is justified based on social needs: the goal is to provide people with the technological solutions that will improve their lives and well-being.

However, it is becoming increasingly evident that this system perpetrates inequalities. The innovations imposed based on prospected economic profits for the funding elites introduce the dependence of people’s communities on the knowledge of experts’ and ultimately on means and resources they neither possess nor master (Illich, 1971). Moreover, the introduction of more productive technologies frequently produces a negative environmental impact. Hence, rather than solving the social issues caused by global competitiveness, the need for standardized and increasingly efficient modes of production turns less-advanced communities into consumers of information. The generation of profit from the imposed use of means and practices can be then reinvested to fuel further information that generates innovation, exacerbating disparities and needs. Refusing to accept/adopt the newest solutions – i.e. refusing to consume and use the content assessed as valuable information – means jeopardizing one’s life in the present. Conversely, to agree means contributing to an increasing dependency on the knowledge and practices developed by the most skilled producers, which in turn increases their competitiveness and ultimately proves them right according to the rules of the game (more adoption equals more impact and therefore higher alleged quality of research). Accordingly, despite the appearances and declared intentions, the main effect of the globalization of imperfect competition for innovation is the production of informational commodities. Their need is artificially created by reformulating social issues as problems of access to consumption. Hence, like any other alienated worker, researchers suffer for the meaninglessness of conducting activities whose finality is determined by external instances. This end partially lies outside their control, and, in the worst cases, it is in contradiction with their social or political engagement. Nevertheless, as we noted, the lack of confidence in scientific programs has been expressed also by scientists, who denounce the exacerbating competition as responsible for the deteriorating quality of research (Tiokhin et al., 2021; Hill et al., 2024), further undermined by adopting approaches that discourage rigor in favor of prolificacy and speed of publications.

As Ivan Illich has argued in his “Tools for Conviviality” (Illich, 1973), when the purpose of innovation is to enhancing consumerism for the sake of economic benefits, the products are not meant for relieving the masses but for generating new needs and dependencies. Therefore, where science comes to the support of a technological advancement that becomes a purpose in itself, scientists end up with producing solutions that benefit the elites more than the people who are urged to adopt them. The narrow horizon of their specialization prevents them from considering broader perspectives and leads them to preferably pursue ways to exploit their findings. Since the ultimate objective of their activity can result too far and undetermined to be fully assessed, scientists are left with the much smaller goal of introducing means of relative value that normally result in developing a chain of more unpredictable end. As the successful applications of their research in industry cannot be fully anticipated, scientists are prevented from judging the products they help create, and the ultimate consequences of their activity. In Marxian terms, their labor could be possibly alienated just as the workers in a factory, constrained to keep up with the productivity of machines and to demonstrate their value as employees. For the producers of contemporary information, the lack of direct contact with the ultimate meaning of their work often results in undermining their objective as scientists to prioritize personal success. Accordingly, their attention is diverted to the elaboration of competitive strategies within a system where opportunities are granted only to the more efficient, namely those who can stand the competition with the automated production of consumable information.

The degeneration of knowledge into a consumers’ good

When they lament the negative effects of harsh competitiveness, researchers complain about their role being reduced to the mere production of information as a consumers’ good in a system where information is just a means for producing more information. When the quality of research (and therefore of a researcher) is measured by parameters such as the Impact Factor, scientists could be regarded akin to social media influencers who compete to affirm themselves as generators of desirable pieces of information, which is used to shape behaviors and foster consumption. This explains why scientists who publish warnings, advice or suggestions are often publicly treated like influencers in social media and exposed to potential violent attacks and aggressive criticism.

In the context of competitive market for information, researchers are unable to understand the final product they contribute to release. The value of the information they produce is worth the amount of sellable information that can be derived in terms of strategies, technologies and future expectations. Hence, rather than contributing to sharing knowledge and truths, they are co-responsible for the uncertainty generated by the excess of information. It is this overflowing abundance that justifies the implementation of algorithmic technologies and fosters the industrial system for the automated production of information. For instance, the overwhelming number of research papers published in specialized journals represents a quantity that is evidently difficult to select and read. The wider tendency is then to rely on keywords and abstracts to compose bibliographies delegated to search algorithms often also based on the ranking of papers. As a consequence, it is seldom the content or the quality of the articles that determine their success, but a mere series of calculations based on quantitative criteria and metrics. The most discouraging aspect of this conduct is that researchers appear to have no choice but to collaborate with a system that ultimately deprives meaning to their activity. We hereby assume that qualitative (and not necessarily quantitative) valuable knowledge has the function to reduce uncertainty and enable the collectivity to make decisions and achieve specific and shared objectives. Already in the late ‘80 s, in his “The human use of human beings, cybernetics and society” (Wiener, 1950) Norbert Wiener warned against the dangerous degeneration of the new science of communication – i.e. cybernetics – once coupled with game theory:

“The fate of information in the typically American world is to become something which can be bought or sold. It is not my business to cavil whether this mercantile attitude is moral or immoral, crass or subtle. It is my business to show that it leads to the misunderstanding and the mistreatment of information and its associated concepts.”

After having analyzed the way in which the strategic value of information for assuring power leads to secrecy, bluffing and jamming, Weiner claims that:

“We are in an age where the enormous per-capita bulk of communication is met by an ever-thinning stream of total bulk of communication. More and more we must accept a standardized inoffensive and insignificant product which, like the white bread of the bakeries, is made rather for its keeping and selling properties than for its food value. This is fundamentally an external handicap of modern communication, but it is paralleled by another which gnaws from within.”

In Wiener words:

“This is the cancer of creative narrowness and feebleness”.

And also:

“When there is communication without need for communication, merely so that someone may earn the social and intellectual prestige of becoming a priest of communication, the quality and communicative value of the message drops like a plummet.”

The problem with the legitimation of science is therefore related to how science is put at the service of the competitive industry for the production of information rather than at the service of uncovering facts and developing knowledge. Knowledge consists of widening human capacity to understand, comprehend and feel within a framework where the goal must not be the elimination of competitors, but a collaborative and inclusive vital transformation. Again Wiener:

“To be alive is to participate in a continuous stream of influences from the outer world and acts on the outer world, in which we are merely the transitional stage. In the figurative sense, to be alive to what is happening in the world, means to participate in a continual development of knowledge and its unhampered exchange.”

Hence science is not to be considered a product, nor an industrial-like process for engendering commodities and technological gadgets, but a thinking process that enriches and it is in turn enriched by other modalities of knowledge production (arts, humanities, etc.). Moreover, as a specific cultural process for knowledge production, science is not superior to other non-western systems, but develops the vocation of constructively integrating into a common world where differences are positively evaluated as creative expressions. It is the interaction among these multiple modalities that generates fecund transformations and assures the emergence of radical novelties, guaranteeing the future that the global domination of the market’s interests seems to undermine. It is then essential to significantly enrich the scientific community with the collective construction of an organization able to assure freedom and equality, thereby preventing the entropic and hypertrophic growth of means that have no other use than securing the proliferation of means. In this sense, knowledge is not a mere “know-how” to be optimized with the sole scope of assuring formal progress without content. Rather, knowledge is more a “know-what”, intended as a process where a real chance is given to broadening our understanding of reality and to our capacity to collaboratively generate a world where collective contributions aim at freeing and diversifying the forms of life expressions.

Accordingly, to foster the credibility of science, within and among societies and the scientific community, means to emancipate the production of knowledge from the interests of the industry for information. This entails a rethinking of science to make it suitable for contributing to the enrichment of the representations of reality as well as of the ways of acting in it. This means freeing science from the competitive framework that constrains it within the tight boundaries of imposing practices and values only aimed at increasing sterile and harmful consumption (UNESCO, 2023).

Diamond open access

A proposition to transform the system for assessing the production of knowledge through science

A global context marked by aggravating inequalities must be able to rely on scientists that are not reduced to mere generators of information and quantitatively assessed for their exchange value like any other kind of merchandise. The internationally growing movement for Open Science (Panel for the Future of Science and Technology STOA, 2024; UNESCO, Open Science: Updates and Progress, 2023; UNESCO, Online Open Access programme and meeting document Understanding open science, 2022; Miedema, 2022) is a clear symptom of the spreading desire to transition science from a competitive system of information production to a new paradigm that values collaboration and sharing. In such a new paradigm, knowledge is the participated creation of a common value rather than the private producer of consumers goods. In this perspective, the response to the declining trust in science is an effort that goes beyond protecting the freedom of expression of scientists and the right to autonomously determine research programs. The only adequate response to the present crisis of legitimacy of science as well as the dissatisfaction and concerns of scientists, seems to be the transitioning from the paradigm of competitive assessment to a more collaborative, inclusive and democratic system for knowledge production. Here, the concept of democratization of science must be briefly explained to clarify that, whilst the merit of scientific work should be judged more openly than by mere market, or somewhat quantitative considerations, such judgement must remain within the boundaries of the broader scientific community. Although universities declare to (and arguably, in reality, largely do) grant scientists the freedom to choose their research agenda, the researchers’ choice is limited by the remits and priorities of funders, without whom limited scientific research can be carried out. This restricts the freedom to commit responsively to the ultimate aim to advance the understanding of nature, driving the transformation that the present challenges require. The results of their work must then be openly available and debatable, or even fiercely criticizable, within the wider scientific community. This is normally a lengthy process, and efforts are invariably needed to prove or reject scientific propositions. For this reason, one of the main impediments that hinders true scientific work is the haste that the competitive model brings about to the community.

As Kwadwo Appiagyei-Atua pointed out in 2008 in his “Minority Rights, Democracy and Development: The African Experience” (Appiagyei-Atua, 2008) and recently at conferences organized by organized by UNESCO (UNESCO, Academic Freedom and Freedom of Science, 2023a), scientific freedom does not make any sense if it is not serving to improve the democratic process. Conversely, it is only under the condition of a real democratic debate that scientific research will be oriented and that the technological tools needed will be selected. Claiming the independence of expertise from political preoccupations – as it is usually proposed as a solution – can only aggravate the problem, once a mutual dependence exists between the choices of governments and scientific legitimacy, as we clarified. Here, we should make a distinction between the legitimacy of choosing a research topic and the merits of the results obtained. While the former requires broader ethical validation, which includes a political debate, the latter remains solely a concern of the scientific community. When the general public is called to directly evaluate the validity and merit of scientific investigations (often by leveraging a misconception of democratizing science), such evaluation may rely on superficial (and inexperienced) “gut-feeling” and intuition. Science can then easily become an instrument for appeasing or maneuvering the same public in validating research outcomes without appropriate knowledge or instruments. In her “Objectivity and Diversity” (Harding, 2023), Sandra Harding argues that dominant epistemological frameworks often reflect the biases and interests of those in power. Yet, a real and stable trust in science cannot be re-established if scientists are not allowed to freely engage in people’s concerns while respecting the specificities of their cultural values, experiences, and practices beyond any political or economic agenda (Harding, 2023). As mentioned, this goes hand in hand with promoting a robust method for the free and open validation of results within the scientific community. Such an opening would have the secondary outcome of effectively enhancing open debates, by showing that administrations and institutions are not afraid of allowing people to disagree with the official interpretation of their problems. Moreover, this approach would positively transform the rules of the competition that affect scientists, by empowering them to carefully revise the social consequences of their activities as well as to actively participate in the people’s growing desire to transitioning towards a more responsible and sustainable world’s organization. Ultimately, this would open the way to considering humanity and its environment as the principal target of scientists’ activities. Arguably, a significantly higher rewarding and far-reaching objective than the progress of their career.

Finally, we would stress the importance of an additional dimension of this important transition. While it is important that the scientific research agenda is opened to public discussion, its production must take into account other non-scientific ambits, world views, values and practices. As Paul Feyerabend noted (Feyerabend, 1975), it is the influence and the inspiration derived from heterogeneous forms of conceiving the world that fosters scientist creativity, leading to unexpected discoveries as well as fruitful and much needed methodological transformations. As we have discussed, such essential innovations are mostly hindered, while science is trapped in the competition to produce economically valuable information. As it has been pointed out in Farida Shaheed’s talk at mentioned UNESCO conference on Academic Freedom and Freedom of Science (UNESCO, 2023b), the common enforcement of a set of given criteria and procedures for assessing the merit of a research program discourages the opening of new unconventional hypotheses, approaches and methods. In Shaheed’s words:

“The issue of scientific and academic freedom relates to the basic issue of human creativity and… what I love is that it speaks about the freedom indispensable for this creativity, be it in the form of artistic expression, or science.”

This opening is nonetheless essential to ensure the vitality of a human activity, such as research that, from an historical standpoint, never ceased to reinvent itself and, as a consequence, influences the way we perceive reality and organize our societies. Importantly, transformative discoveries and shifts of paradigm cannot happen if not through the influence and the inspiration from non-scientific ambits, productions, and practices. Conversely, the sharing of research agendas and scientific findings with the general public would help to rehumanize the figure of scientists, by showing their concerns, troubles and hopes, as well as stimulating cultural elevation and creativity at large. A shared and collaborative production of knowledge, in fact, does not merely aim to find efficient ways of organizing practices and comparing challenges, but to affect and stimulate broader cultural expressions, intellectual growth and artistic production. A historical reconstruction of the reciprocal and beneficial influence among scientific and technical research on one side and humanities, arts, and social sciences on the other falls beyond the scope of the present work; however, it is important to mention that knowledge cannot be considered sufficiently widened and enriched if it does not concern all the dimensions of the human intelligence, rationality, and sensibility. Much against the current view of researchers, often sealed from a rooted cultural formation, we firmly believe that in order to deeply comprehend the world in which scientists are called to operate, they need to embrace alternative and non-scientific ways of thinking and acting. Conversely, we are equally convinced that science opens to new possibilities of experiencing, seeing and feeling entities, structures and processes that would be otherwise ignored. Transdisciplinarity is often invoked in the intentions of universities’ departments. Nevertheless, we hereby would like to outline a broad framework to put it into practice meaningfully: rather than grouping scholars from the science, the arts and humanities to solve pre-framed problems, the idea is that transdisciplinary collaborations should start with the mere problem formulation. We therefore would like to stress the reciprocity of the benefits for advancing cultural production at large. This widening of the conceivable and the sensible, is important not only from a pragmatic standpoint, but also because it stimulates imagination that, alike arts, has never ceased to be nourished by scientific observations and theories. Such cultural productions may often serve as subtle criticism or the expression of ethical concerns that must be considered for orienting further research, and its endeavors and means. We firmly believe that this broadened framework is the only condition under which science might legitimately claim to contribute to the production of knowledge as a common good.

While we openly acknowledge the importance of the mentioned efforts made by UNESCO, Panel for the future of Science and Technology, Science and Technology Options Assessment (STOA) and other organizations that are working on new guidelines for enhancing freedom in science and scientists’ responsibility, we also praise the current efforts to smoothly transitioning to a more collaborative and democratic system for assessing research merits. Compatibly, we would like to propose new ways for experimentation, where research laboratories are open to cultural and reciprocal contamination with ambits usually falling within the field of arts and humanities. Such an agenda will allow fruitful exchanges to overcoming the imaginary boundary that artificially separates different, however much complementary modes of producing knowledge. As our excursus through the progressive transformation of the methods for the production of knowledge shows, the system is entering a cyclical crisis and it is up to us to ensure that the transition aligns with the sensibility of our times. Accordingly, the scope of this paper is not to define clear-cut solutions but to widen the discussion of a problem that is arguably rarely faced directly. In doing so, our aim is to stimulate a public and academic debate beyond the boundaries of the so-called hard sciences to reach out for other disciplines such as arts and humanities. We think this would generate a trans-collaborative environment that is key to pursue more cooperative, transparent, communicative and overall trustworthy science.