Philosophy of science is full of investigations and discussions on scientific practice. In the last century, the positivists, including logical positivists and logical empirists, have been the most influential, followed by post-postivists or wholists and more recently by scientific realists, critical rationalists and pragmatists [13, 23, 24]. Eventually, as Chalmers claims “[…] there is no general account of science and scientific method to be had that applies to all sciences at all historical stages in their development” . This conclusion is especially due to the fact that besides the different scientific methodologies to approach scientific inquiries, different aims are also pursued. For example, even though new experimentalists contributed a lot to experimental reasoning in the last century, the naturalist account, which is paramount to physical and biological sciences, cannot be transferred to other sciences, as experimental manipulation is irrelevant for disciplines like social or historical sciences.Footnote 1 In short, for epistemic considerations, scientific practice can be defined on two levels: firstly, regarding scientific methodology; and secondly, regarding scientific aims. Scientific methods can be referred to as positivist (also logical empiricist) approaches relying on empirical evidence or wholist approaches, which are rather theory-laden . Concerning the aims of science, again two main conceptions can be distinguished: The one position sees the “construction of comprehensive accounts of the natural world”  as the main goal of scientific inquiry. Representatives of the other position claim that “the work of science is the discovery of the truth about the natural world”  – although being skeptical about the possibilities of reaching this aim. Hence, the former aims at knowledge extension while the latter aims at finding truth by scientific inquiry. Thus, the choice of methodology does not imply a certain aim. But theory and methodology choice differs even within scientific disciplines, as different paradigms may be pursued. This is especially due to the social impact on science, e.g., values and personal preferences [25, 26].
In her 1990 publication Science as Social Knowledge, the American philosopher Longino  analyzes different aspects of scientific reasoning in order to show the impact of social values on scientific research . Her inquiry considers the main accounts of scientific knowledge, for the sake of brevity, reduced to positivist and wholist approaches. For describing scientific inquiry as social epistemology, she questions the shortcomings of the existing forms of scientific criticism by showing the importance of constitutive and contextual values in scientific inquiry as well as the inability of existing forms of criticism to take them completely into account. Therefore her theory can be seen as a socio-epistemic one . A core issue of her inquiry is the constitution of scientific objectivity by considering these different forms of values. To handle this issue, she proposes different criteria for transformative criticism. As I will show in “Scientific methodology with regard to Longino’s social epistemology” and “A socio-epistemic discussion of foresight quality criteria” sections, these constitutive and contextual values as well as transformative criticism, may contribute to a better understanding of foresight quality criteria as a contribution to fostering a scientific debate on foresight theory.
The complexity of epistemic considerations and aims of foresight
In the field of foresight and futures studies in general, there are different approaches, which tangle epistemic considerations. For example, Mannermaa characterizes different foresight paradigms  and Aligica discusses different accounts of scientific criticism in the context of futures knowledge [29, 30] while Grunwald considers options for its argumentative validation [31, 32]. But mostly, foresight is described as a field which supposedly belongs to the social sciences [33, 34]. Fuller and Loogma  even discuss foresight as a social constructivist endeavor. Wendell Bell, who describes futures studies as a “[…] transdiciplinary action and social science” , provides a comprehensive link between critical rationalism and foresight epistemology. Bell’s definition of critical rationalism involves accounts of scientific realism as well as logical empiricism . Further, he sums up the epistemologies, which underlie the different approaches used in foresight as follows: “Futurists focus on the transformation of hindsight into foresight. On the one hand, they speculate, think laterally, intuit, reason counterfactually as well as factually, cogitate linearly and dialectically, entertain outrageous–and even despised – notions, and creatively invent in order to unveil possible and probable futures. On the other hand, they specify past and present data using a multitude of standard and special methods, collecting, analyzing, and interpreting evidence in order to make posits about possible and probable futures and to construct surrogate knowledge as reliably and validly as they can.”  By this definition, which contains methodologies of various sciences, Bell tries to encompass a futures epistemology within the concept of critical realism.
Nevertheless, it should be noted that the impact of the social is also taken into consideration in epistemic discussions of foresight (see also ). Bell also emphasizes social biases that may threaten validity as a characteristic point when describing the features of scientific realism . In the second volume of Foundations of Futures Studies he even claims that “[t]he critical realist theory of knowledge can incorporate the testing of value propositions just as it tests truth claims about the past and the present.”  As will be shown in the next chapters, Longino’s theory provides even better indications to support the claim that there is an epistemic base connecting objectivity, social aspects and values.
But a closer look at different descriptions of the aims of foresight reveals how important the issue of social aspects really is in foresight and especially in its validation. Following Slaughter, foresight can generally be defined as: “opening to the future with every means at our disposal, developing views of future options, and then choosing between them.”  Accordingly, Bell claims that “[t]he purposes of the futures studies are to discover or invent, examine or evaluate, and propose possible, probable and preferable futures.”  Besides these partly stretched definitions, in their recent paper Kuusi, Cuhls and Steinmüller also indicate different levels of purposes in futures research . In general, they also correspond to the critical realist view of science. For example, in the previous version of that paper, they propose to consider future knowledge as well-justified:
“According to the conventional definition, knowledge about a topic is justified true belief concerning the topic. Because there is no way to directly ascertain the truth of an anticipation before its defined realization time, the knowledge concerning possible futures can be nothing else than well-justified or well-argued beliefs.” .
But there is not only a scientific aim inherent to futures studies. Kuusi, Cuhls and Steinmüller emphasize the following two challenges for the validation of futures research, which also underline the aim of foresight:
“Does the ‘whole picture’ meet scientific criteria? […]
Does the ‘whole picture’ serve their [the customers’ or the target group of users’] interests? Is it relevant for them?” 
These two points show the special characteristics of foresight: it is not only expected that foresight practices and outcomes correspond to scientific practices, but also that they fulfill certain aims given by a client or customer. In order to establishing foresight quality criteria encompassing (1) the aims of foresight, (2) the goals of foresight projects and (3) the variety of scientific backgrounds involved, there are two dimensions to be considered: On the one hand, the crucial scientific challenges for foresight are the scientific criteria and the target groups. On the other hand, Longino’s statement according to which scientific activities can be evaluated with respect to both goals, knowledge extension as well as finding truth . Hence, it is crucial to clearly distinguish that the classical aims of science cannot be applied directly to foresight. This also implies that scientific criticism of foresight needs its own criteria and rules satisfying the aims and methods of foresight.
Scientific methodology with regard to Longino’s social epistemology
Regardless of the perception of the aims of science or the method used, a crucial characteristic of all forms of scientific inquiry is objectivity. The claim of objectivity responds to the idea that science should rely upon facts rather than wishes. Science can provide two different forms of objectivity. Firstly, “[…] objectivity is bound up with questions about the truth and referential character of scientific theories, that is, with issues of scientific realism” and secondly, “[…] objectivity has to do with the forms of inquiry.”  This means that while the first notion of objectivity refers to objectivity in terms of describing the natural world as it is, the second one relies on non-subjective criteria for developing, accepting, and rejecting the hypotheses and theories constituting a certain point of view . By ascribing objectivity to a scientific method, two main points are intended: Firstly, by asserting the objectivity of data, relying upon them justifies theories and hypothesis, which are inducted. Secondly, while confirming or rejecting that a method is objective, we also evaluate if the methods are the proper means for an unbiased and unprejudiced assessment of hypotheses and theories .
Based on these observations, it is possible to define what a scientific method is and which scientific methods foresight consists of. A general definition supported by classical philosophical accounts is that “[…] method, the process by which knowledge is produced, is the application of rules to data.”  But how are these rules applied? To answer this question, a closer look at application, process, and rules is necessary.
The application of scientific methods can be summarized as “activities of scientific inquiry”, consisting of (1) producing theories, (2) producing concrete interactions with natural processes, or (3) producing models of it [13, 23].
By taking a closer look at this point, it becomes obvious that the way of conducting science cannot be abstracted from the people conducting it, meaning the process per se. As Longino points out, “[t]he integration and transformation of these activities into a coherent understanding of a given phenomenon are a matter of social negotiations.”  These definitions of application and process can also be applied to foresight. The “given phenomenon” Longino mentions may also be a future state or a future scenario that is developed. But foresight does not aim at constructing a “coherent understanding” about the future. Instead, Longino’s notion on “coherent understanding” can be applied to the discursive process of establishing quality criteria in foresight. The former quotation also emphasizes that the “nature of scientific inquiry”  is a social one characterized by the following three issues:
Scientific disciplines are social enterprises, “the individual members of which are dependent on one another for the conditions (ideas, instruments, et cetera) under which they practice.”
“initiation into scientific inquiry requires education”
“[A]s the practitioners of the sciences all together constitute a network of communities embedded in a society, the sciences are also among a society’s activities and depend for their survival on that society’s valuing what they do.”
In this regard, the scientific community has to fulfill certain criteria, or rather, follow certain rules for producing objective scientific knowledge. This raises the question how objectivity is reached if science is social? According to Longino, “[a] method of inquiry is objective to the degree that it permits transformative criticism.” By maintaining a critical dialogue, objectivity grows by degree. Longino makes this point explicit by going beyond the classical forms of criticizing hypotheses in science, which are evidential and contextual criticism, and introducing transformative criticism as the outcome of intersubjective criticism. Defining evidential and contextual criticism first, and then showing how Longino induces transformative criticism can explain this best.
Evidential and conceptual criticism
Evidential criticism proceeds “on the basis of experimental and observational concerns” . It questions “the accuracy, extent and conditions of performance of the experiments and observations serving as evidence, and questions their analysis and reporting.”  This form of criticism underlines why foresight is often claimed to be unscientific. The analysis and reporting can be applied to a foresight process only with restrictions as results produced in foresight, e.g., future scenarios, can hardly be repeated – and are not even intended to be.
Conceptual criticism proceeds on “the basis of theoretical and meta-theoretical concerns”. Here, three types of questioning can be distinguished :
Questioning the conceptual soundness of a hypothesis: Longino gives as an example Kant criticizing and questioning the Newtonian hypothesis of absolute time and space.
Questioning the consistency of a hypothesis with accepted theory: such as e.g. traditionalists who rejected the heliocentric theory as being inconsistent with the existing Aristotelian concept of physics.
Questioning the relevance of evidence presented in support of a hypothesis: Such a criticism is related to evidential criticism, yet, it questions not only data but also why certain assumptions were taken into consideration as giving evidence to a hypothesis. What matters is the relevance of certain evidence to a hypothesis. Here, criticism becomes intersubjective. Bell’s concept of critical rationalism, which is mentioned in 2.1, can be ascribed to this form of criticism.
As objectivity in the positivist understanding is limited to rejecting or accepting hypotheses based on observational and experimental data, it is only applicable to empirical scientific inquiry. This is conducted e.g., by “syntactically and deductively secured relation of hypotheses to a stable set of observational data” . From a contextual perspective, the proof of evidential objectivity is insufficient as it does not control if and which background assumptions lead to strengthen certain hypotheses. The impact of this consideration on the objectivity of scientific methods is formulated by Longino as follows: “Because the relation between hypotheses and evidence is mediated by background assumptions that themselves may not be subject to empirical confirmation or disconfirmation, and that may be infused with metaphysical or normative considerations, it would be a mistake to identify the objectivity of scientific methods with their empirical features alone.” 
Longino extends the last point of conceptual criticism in order to describe that this last form of criticism is transformative. By doing so she aims at showing that this third type of conceptual criticism reveals the impact of background beliefs. The fact that there is such kind of criticism already reveals that background beliefs and assumptions do have an influence on the creation of knowledge and therefore objectivity is to be questioned. As Longino points out:
“Objectivity in the sense under discussion requires a way to block the influence of subjective preference at the level of background beliefs. While the possibility of criticism does not totally eliminate subjective preference either from an individual’s or from a community’s practice of science, it does provide a means for checking its influence in the formation of “scientific knowledge” .
It seems that as long as background beliefs concerning a hypothesis are discussed, rejected or altered in the context of criticism by a scientific community, it is possible to establish hypotheses as scientific knowledge free from preferences of any individual. Consequently, scientific knowledge can be defined as social knowledge. Nevertheless, it is important to keep in mind that values still enter scientific debates by individual’s values, but also by community values . The next two sections will therefore describe (1) criteria of transformative criticism and (2) types of contextual values influencing and shaping knowledge.
Objectivity by criteria of transformative criticism
In order to describe how certain degrees of objectivity can still be reached, Longino has formulated “four criteria necessary for achieving the transformative dimension of critical discourse” [13, 14]. The transformative dimension of criticism is the nucleus of intersubjective criticism. The criteria are:
Recognized avenues for criticism: The most prominent form are peer review processes in scientific publishing. Also, journals and conferences are established avenues for presenting and criticizing scientific outcomes. These procedures help to shape and advance scientific knowledge. Longino claims that critical activities should receive nearly equal weight to “original research” in order to lead to valid and objective scientific knowledge. 
Shared Standards: If criticism ought to be relevant for a scientific discussion, it should also appeal to “public standards or criteria to which members of the scientific community are or feel themselves bound. These standards can include both substantive principles and epistemic as well as social values.” Of course, scientific communities differ. The standards can therefore consist of elements like “[…] empirical adequacy, truth, generation of specifiable interactions with the natural or experienced world, the expansion of existing knowledge frameworks, consistency with accepted theories in other domains, comprehensiveness, reliability as a guide to action, relevance to or satisfaction of particular social needs.”  Longino emphasizes that the weighting of the several standards varies not only from one scientific community to another, but also due to different social and historical contexts.
Community Response: “This criterion requires that the beliefs of the scientific community as a whole and over time change in response to the critical discussion taking place within it.”  The indicators for responsiveness are for example contents of textbooks, grants and awards. Critical discussions and responses can help to enhance understandings and assumptions that are guiding for the community.
Equality of intellectual authority: The last criterion refers to the possibility to “[…] disqualify a community in which a set of assumptions dominates by virtue of the political power of its adherents.”
Individuals take part in this scheme by participating in various critical discussions. All in all, these criteria for transformative criticism enable the evaluation of the objectivity of scientific inquiry itself, but also of scientific debates in society. This is achieved by the fact that at this point, background beliefs involved in science can be detected and discussed actively. Further, a contextual view of science goes beyond the limits of only applying evidential criticism, as it respects the diversity of scientific methods, and it reacts to the current practice of science but also to history. 
Types of contextual values influencing and shaping knowledge
Longino resumes that for the validation of sciences, both have to be considered:
“[…] the role of background assumptions in evidential reasoning”
“[…] the roles of (sometimes) conflicting goals of inquiry with respect to which hypotheses and theories are assessed.” 
The transformative criticism in a scientific community including the four criteria as described above helps to validate scientific inquiries and methods by involving both, the individual and social values that influence background assumptions and science. This is important to keep in mind as contextual values, interests and value-laden assumptions influence and shape not only scientific practice but also the results, even when constitutive rules of science are not violated . In other words, it is possible that a certain scientific process is valid in terms of evidential criticism, but it may nevertheless violate scientific objectivity regarding contextual values. The latter can be validated by criteria of transformative criticism.
According to Longino, the practice of both pure and applied science can be affected and influenced by contextual values in different ways. Nevertheless, it is possible to produce good scientific knowledge when taking into account which of the contextual values might affect our research. Longino therefore sums up a list of five ways in which contextual values might affect our research from the outside :
Practices. Contextual values can affect practices that bear on the integrity of science.
Questions. Contextual values can determine which questions are asked and which are ignored about a given phenomenon.
Data. Contextual values can affect the description of data, that is, value-laden terms may be employed in the description of experimental or observational data, and values may influence the selection of data or of kinds of phenomena to be investigated.
Specific assumptions. Contextual values can be expressed in or motivate the background assumptions facilitating inferences in specific areas of inquiry.
Global assumptions. Contextual values can be expressed in or motivate the acceptance of a global framework like assumptions that determine the character of research in an entire field.
These 5 ways help to recognize to which extent the research is affected and to give more emphasis to criticism as for example the intersubjective one. By doing so, it is possible to minimize the contextual values, which might lead to biased results and value-laden assumptions. Although discussing these points may lead to more clarification, e.g., in order to validate specific research programs, Longino acknowledges that even intersubjective criticism is only partially an effective barrier . One remaining problem is for example that those value-laden assumptions shared by a whole scientific community may remain hidden. Obviously, when applying the different forms of criticism, it might appear that intersubjective criticism of processes and outcomes in the field of foresight may be most appropriate. Hence, quality criteria shall also encompass all the different forms of scientific criticism in order to reveal the quality of foresight procedures and outcomes.