Collective Quality. How to design collective standards of knowledge?

Submitted draft. Do not quote without permission.

La barre de platine-iridium utilisée comme prototype du mètre de 1889 à 1960

Knowledge is a common good. A tiny part of our knowledge of the world is generated by our own personal experience. Relying on others is one of the most fundamental ways to acquire knowledge, not only about the external world, but also about who we are, (for instance about when and where we were born). To use Mary Douglas striking metaphor: “Our colonisation of each others’ minds is the price we pay for thought”.[1]

The collective dimension of knowledge is acknowledged in almost every field of thought these days, from the optimistic forecasts on the power of collective intelligence made by James Surowiecki[2], to the debate on the social dimension of knowledge within recent sociology of science and social epistemology[3]. Everybody seems to accept the blatant truth that without the import of other people’s beliefs our cognitive life wouldn’t be much different than that of animals. Yet, what is surprising in this debate is that the collective dimension of knowledge has been put forward to argue in favor of very different conceptions of the objectivity and the standards of quality of knowledge. On the one hand, within the so-called Big-Science debate, the collective dimension of scientific work is considered the ingredient that guarantees the objectivity of that form of high-quality beliefs we name science. On the other hand, the same social dimension has been used to argue against the high-quality standards of scientific method, for a more realistic view of common knowledge[4] empowered by the wisdom of the many that can overthrown the authority of the experts.

Generations of scientists have been raised in the dogma of the impersonality and collectivity of the scientific work, against a classical view inherited from the Scientific Revolution of the scientist as an isolated genius. To mention one of the most influential defenses of the collective view of science, in his famous essay on Little Science, Big Science, which laid the foundations of the contemporary scientometrics, Derek de Solla Price writes that the social nature of collaborative work in the Big Science is the only guarantee of objectivity: scientists do not base their results on their personal qualities, like artists do: scientists are interchangeable because what they do is to apply a collectively shared method of investigation of nature that has nothing to do with their own personal identity. As the zoologist J. R. Baker put it: “If Mozart had not composed that immortal work of genius, the ouverture to Le nozze di Figaro, no one else would have done so; but if Kekulé had not lived, structural formulae and the benzene ring would not have remained forever hidden: someone else would eventually have dreamed the same dreams”.[5]

Thus, according to this view, science is objective because is collective, it is a collective game of peers who scrutinize each other impersonally by applying a shared scientific method that is the Norm of Quality of our knowledge.

But, as I said, this view contrasts with a more recent view of the collective construction of knowledge, in which the standards and norms of scientific method are replaced by the rules of aggregation of lay judgments[6].

Both approaches insist on the equation: collective = objective: to achieve an objective result, that is not too biased by personal points of views, we must be many, no matter if laymen or experts. Knowledge is objective insofar as it is impersonal, disembodied, unvarnished from any singularity and subjective wisdom.

Take for example what Clay Shirky says in his last book on the power of social networks: “We are so natively good at group effort that we often factor groups out of our thinking about the world. Many jobs that we regard as the province of a single mind actually require a crowd. Michelangelo had assistants paint part of the Sistine chapel ceiling. Thomas Edison, who had over a thousand patents in his name, managed a staff of two dozens. Even writing a book, a famously solitary pursuit, involves the work of editors, publishers, and designers. Even if we exclude groups that are just labels for shared characteristics (tall people, redheads), almost everyone belongs to multiple groups based on family, friends, work, religious affiliation, on and on. The centrality of group effort to human life means that anything that changes the way groups function will have profound ramifications for everything”[7].

Thus collectivity is everything today, and knowledge seems to be a product of collective effort. Yes, but if it is so, then where do the standards of our knowledge come from? When a group is able to work out a right answer or an accurate prediction, on the basis of what do we judge that the answer or the prediction is the right one? Either we knew already that it was the right one, or it is just a posteriori verification that can guarantee the truth and the objectivity of the conclusion. In the case of science, even if it is now a truism to acknowledge the collective aspect of the scientific enterprise, the objectivity of the results doesn’t come from the collective dimension, but from the reliability of the method. A hypothetic-deductive method for inferring the theorems from the axioms of a theory, an experimental, statistical method, are the fruit of a long filtering of ideas, collective or singular, that have distilled through centuries the “right” way measure reality and make predictive models of its future possible states. Science is collective because our trust in scientific method is shared almost universally: that is why the same experiment can be replicated at the antipodes of the world and the results compared. But method is not intrinsically collective.

When we come to the more debatable case of knowledge out of aggregation rules of lay judgments, the question of objectivity becomes even harder. How do we judge reliable and true a result that comes from a collective aggregation of individual opinions? How do we know that our Google search for a certain keyword will end up displaying the “best” information available on that keyword? We know it out of personal experience: after many trials with Google searches, we have come out with the conclusion that the information Google is able to provide at the top of its results for a certain search is good enough to be believed. But we do not have independent means of granting this knowledge on the fact that it has been collectively produced.

In his provocative article on the end of scientific method, Chris Anderson simply states that we can live in a groundless world of good matches of statistic data without caring too much about method: “Google's founding philosophy is that we don't know why this page is better than that one: If the statistics of incoming links say it is, that's good enough. No semantic or causal analysis is required. That's why Google can translate languages without actually "knowing" them (given equal corpus data, Google can translate Klingon into Farsi as easily as it can translate French into German). And why it can match ads to content without any knowledge or assumptions about the ads or the content. Speaking at the O'Reilly Emerging Technology Conference this past March, Peter Norvig, Google's research director, offered an update to George Box's maxim: "All models are wrong, and increasingly you can succeed without them."”[8]

So, collectivity in this second sense, of simple aggregation of data or lay opinions is replacing the collective enterprise of science, based on the centrality and robustness of method. But the problem remains: where do the collective standards of quality come from? When I check the grammaticality of an expression by inserting it into Google, I trust the answer that has the largest number of results: for example, I have checked the English spelling for the word “acknowledgment” while I was hesitating between two spellings: acknowledgment and aknowledgment: given that the first for gave me 11 300 000 results while the second one only 34 300, I have opted for the first one. Of course, I was right this time, but why? Is it just a matter of “epistemic luck” or do I have any ground for believing this result? The only ground the people have is obviously previous experience: you have used Google many times, you know that it is reliable as a spelling checker because you have independent ways of controlling its reliability, like the spelling checker or your own word processor, or other written authoritative sources (like a dictionary). But is it enough to ground our knowledge? And when your independent control of the results you obtained on Google should stop? Is the “good enough” epistemic strategy good enough?

In the rest of this chapter, I would like to argue that in a collective world of knowledge the problem of the standards of quality remains and is even harder than within the classical image of science. What is the “right” quality standard for an item? What is quality, and how to filter a common standard of quality if we aggregate in a decentralized way the opinions, tastes and biases of very different people? That is a classical philosophical question that concerned philosophers such as David Hume, who writes in his famous essay Of the Standard of Taste:

“The great variety of Taste, as well as of opinion, which prevails in the world, is too obvious not to have fallen under every one’s observation. Men of the most confined knowledge are able to remark a difference of taste in the narrow circle of their acquaintance, even where the persons have been educated under the same government, and have early imbibed the same prejudices. But those, who can enlarge their view to contemplate distant nations and remote ages, are still more surprised at the great inconsistence and contrariety. We are apt to call barbarous whatever departs widely from our own taste and apprehension: But soon find the epithet of reproach retorted on us”.[9]

Standards of quality thus change, and each human being can cultivate his or her own idea of what is good and what is bad without harmonize it with the others. In his essay, Hume’s target was aesthetic taste and its subjective dimension and how common standards can rise and stabilize: his solution was to appeal to the experts, the connoisseurs, those whose expertise can be a guide for the others:
“ It is natural for us to seek a Standard of Taste, a rule by which the various sentiments of men may be reconciled; at least, a decision, afforded, confirming one sentiment, and condemning another.” In order to achieve this, human beings have to appeal to connoisseurs, men with special qualities:
“Strong sense, united to delicate sentiment, improved by practice, perfected by comparison, and cleared of all prejudice, can alone entitle critics to this valuable character; and the joint verdict of such, wherever they are to be found, is the true standard of taste and beauty” […] Though men of delicate taste be rare, they are easily to be distinguished in society, by the soundness of their understanding and the superiority of their faculties above the rest of mankind. The ascendant, which they acquire, gives a prevalence to that lively approbation, with which they receive any productions of genius, and renders it generally predominant. Many men, when left to themselves, have but a faint and dubious perception of beauty, who yet are capable of relishing any fine stroke, which is pointed out to them.”[10]

But the appeal to the authority of wise men outside the aesthetic domain doesn’t seem to fit the rhetoric of the Modern Age and the Scientific Revolution according to which the quest of knowledge has to be based on collectively controllable experimental method and not on the authority of the elder masters. Indeed, there are many domains outside of aesthetics in which standards of quality matter and we don’t want them to be produced by the discretionary power of an authority. Quality is not just a matter of taste when we look for standards of epistemic quality, that is, the quality of knowledge we may acquire, or food quality, that is, not only the good or bad taste of food that we ingest, but the quality of its standards of eatability. Also, industrial production quality control procedures cannot be the result of the appeal to an authority, as well as life parameters, like the minimum wage, should be based on collectively agreed standards.

The need of an objective notion of quality raises many questions that I will try to tackle in the rest of this chapter:

· Is it possible to get rid of a normative notion of quality and rely only on mechanisms of aggregation of lay judgments?

· How is a collective standard of quality constructed and maintained in a culture?

· Are there “better” and “worse” systems of quality assessment?

My point is that quality is an intrinsic normative notion that doesn’t make it less “objective”. It is a normative notion based on the historical records of an item, i.e. its reputation in a community. “Quality” as a term has always been employed with reference to a scale of value. In philosophy the “quality” of an item is an attribute of the item that makes it fit into a certain category. The activities of categorizing items and that of ranking are thus intrinsically dependent one on the other. Cultures produce rankings of quality standards, ratings of items because this is the way of making sense of the world outside us, of sorting things in order to make them fit into a certain category. I will claim that quality is a normative notion insofar as it is a standard that is constructed within a particular tradition. What is a tradition? Traditions are evaluated taxonomies and rankings that are selected and stabilized in a culture by many different “forces”:

· Institutions: public structures whose aim is to assure the coordination and maintenance of a collectivity.

· “Sacred values”: those values in a culture that are deeply related to its identity and are hard to question or change.

· Functionality: those aspects of traditions that are socially functional and help to accomplish socially coordinated tasks.

· Problem-solving: traditional cultural artifacts are ways of solving practical problems of information sharing and productivity.

· Biases: tendencies of a culture to reinforce in a particular direction a value or a position in a ranking. For example, a culture may give a special weight to literacy because of the intrinsic value that this represents in its development.

Thus, standards of quality come from the collectively evaluated corpus of knowledge and practices that we call tradition. We trust a tradition because it imposes on our way of seeing reality a ranking, a system of evaluation that orients us in our acquisition of information.

Let me introduce an example of a cultural artifact that is maintained and sustained as a fundamental part of our tradition by many of the various forces I have mentioned above: writing. Writing is a cultural technique that introduced at the end of the 4th millennium BCE in Mesopotamia as a device for external memory that makes possible the reorganization of intellectual life and the structuring of thoughts, neither of which are possible in oral cultures. With the introduction of writing, one part of our cognition “leaves” the brain to be distributed among external supports. The visual representation of a society’s knowledge makes it possible to both reorganize the knowledge in a more useful, more ‘logical’, way by using, for example, lists, tables, or genealogical trees, and to solidify it from one generation to the next. What’s more, the birth of “managerial” casts who oversee cultural memory, such as scribes, astrologists, and librarians, makes possible the organization of meta-memory, that is, the set of processes for accessing and recovering cultural memory. Printing, introduced to our culture at the end of the 15th century, redistributes cultural memory, changing the configuration of the “informational pyramid” in the diffusion of knowledge. Writing, among other functions, helps us to categorize our past history. But why in the modern era of printing and the contemporary era of computers and Internet hand-writing is still so reinforced in school programs? That is because it is stabilized by many forces: schools, “sacred values” against illiteracy, and functionality. Even if hand-writing is a very complex graphical technique that is no more “functional” to acquiring writing skills (typing is enough in many contexts) other forces such as “sacred values” maintain handwriting in our school programs. Our illiterate past is still too close to give up to the sacred value of writing, even if its functional role is reducing thanks to new technologies.

Here I would like to make a more general point about the role of past evaluations and preferences in filtering information. I’ll start with a parallel with some famous remarks Edmund Burke wrote about the importance of traditions. Burke was suspicious of revolutions because they risked to wipe out centuries of tradition, that is, of patiently collected and selected values, judgements and preferences refined throughout the ages. And this process of refinement is for Burke the essence of civilisation, of this thick cultural lore of judgements, values and opinions that penetrates into our minds through education and socialization and constitutes the necessary background of any form of wise thought. If we do not take into account the lore of traditions, we are condemned for Burke to reinvent the wheel at each generation. Our capacity of thinking the world and the institutions around us is much more limited without the contribution of the preferences already aggregated in the past by others. As he says:

« We are afraid to put men to live and trade each on his own private stock of reason; because we suspect that this stock in each man is small, and that the individuals would do better to avail themselves of the general bank and capital of nations, and of ages »[11]

Burke was politically wrong but, in some sense, epistemically right: there is something true in his reactionary remarks, even if their application to the analysis of the French Revolution is wrong for many reasons. One reason why his claims on revolutions are unacceptable today is that obviously not all traditions are worth preserving: the institutional biases and the social pressures that make a political tradition survive may be so wrong and oriented to defend the privileges of just one social class, that it is sometimes wiser to entrust a new generation to rethink the whole institutional design of a society from scratch. But, from an epistemic point of view, he captures the intuition that it is almost impossible to think from scratch, to know from scratch, without taking into account the lore of others’ preferences and values as it is filtered by a culture. This is an important epistemological point that evokes a similar, epistemological idea expressed by W.V.O. Quine in a famous article on his mentor, Rudolph Carnap: “The lore of our fathers is a fabric of sentences. In our hands it develops and changes, through more or less arbitrary and deliberate revisions and additions of our own […] It is a pale gray lore, black with fact and white with convention. But I have found no substantial reasons for concluding that there are any quite black threads in it, or any white ones.”[12] That is, the lore of a tradition, even of a scientific tradition, doesn’t transmit just a bunch of facts from a generation to another, but a sophisticated ensemble of judgements and conventions that shape the way facts will be extracted and classified in a given culture at a given time.

Preferences, conventions and values that others have expressed thus play a critical role in the making of collective wisdom: they shape the reputational landscape that we use to organize our own heuristics to extract information and provide a - sometimes reliable and sometimes too biased - shortcut to what is worth keeping, remembering and preserving as knowledge. The epistemological enquiry to collective wisdom I am advocating here implies that reputation and rating systems are an essential ingredient of collective processes of knowledge: their cognitive role in extracting information doesn’t depend on the intrusion of social factors than are external to the epistemological process, as many have argued. Reputation is a rational criterion of information extraction, a fundamental shortcut for cumulating knowledge in processes of collective wisdom and an ineludible filter to access facts. In my view, in an information-dense environment, where sources are in constant competition to get attention and the option of the direct verification of the information is simply not available at reasonable costs, evaluation and rankings are epistemic tools and cognitive practices that provide an inevitable shortcut to information. This is especially striking in contemporary informationally-overloaded societies, but I think it is a permanent feature of any extraction of information from a corpus of knowledge. There is no ideal knowledge that we can adjudicate without the access to previous evaluations and adjudications of others. No Robinson Crusoe’s minds that investigate and manipulate the world in a perfect solitude.

Thus, the standards of quality of collective knowledge are produced by a weighted incorporation in the production of our singular judgments of values filtered through time. That is what gives authority to a collectively produced piece of knowledge: we trust the wisdom not only of our contemporary crowd, but also of the past crowds who contributed to the crystallization of a tradition. This doesn’t mean that we are passive receivers of the authority of a tradition: traditions are indicators of value, they point to the proxies [13]that allow us to orient ourselves in a space of knowledge we do not yet master. When we enter a new domain of knowledge or a new cultural corpus we acquire the “taste” of the authorities in the domain in order to orient ourselves (the “you have to like this” effect). Who are the “good” and who are the “bad”? This is the way in which a canon is constructed. Then, the more we become autonomous thinkers, we challenge these traditions, participate to transform them and create new canons. It’s a salient feature of our contemporary knowledge world, so saturated of information, that different canons bloom, they rise and collapse in a much shorter period than it used to be before the advent of the decentralized society of information. That is, quality commons are structured in received traditions that are learned and amended from one generation to another.

Collective knowledge is presented today as a form of empowerment that frees us from the deference to experts and authorities. Nevertheless, as I have tried to argue here, experts and authorities have never been so present and influent in producing knowledge as a common achievement. Even is the impersonal game of science, as Steven Shapin has recently argued: “people and their virtues have always been pertinent to the making, maintenance, transmission and authority of knowledge”[14]. And even more in the aggregation of lay judgments, we must not forget that these lay judgments are based on received views and trust in authorities and traditions that do not come out of the blue. The power of collective knowledge is thus to articulate in a new way our trust in the transmitted authoritative views with the possibility of instantaneously sharing these values with others, thus amending these traditions and making them evolve more rapidly.

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[1] M. Douglas (1975) Implicit Meanings, London: Routledge and Kegan Paul.

[2] J. Surowiecki (2004) The Wisdom of Crowds, New York: Random House.

[3] S. Shapin (2008) The Scientific Life, Chicago : Chicago University Press; A. Goldman (1999) Knowledge in a Social World, New York : Oxford University Press.

[4] R. Hardin (2009) How Do You Know? Princeton: Princeton University Press.

[5] Cf. J. Baker (1943) The Scientific Life, New York: Mac Millan, pp. 36-37, quoted in Shapin (2008) cit. p. 9.

[6] See for example C. Anderson (2009) “The End of Methods” Wired.

[7] Cf. C. Shirky (2008) Here Comes Everybody, New York, Penguin, p. 16.

[8] Cf. C. Anderson, cit.

[9] Cf. D. Hume (1757) “Of the Standard of Taste”, originally published in his Four Dissertations.

[10] Cf. D. Hume, cit. § 6; 27.

[11] Cf. E. Burke (1790) Reflections on the Revolution in France, in E. Burke, Works, London, 1867.

[12] Cf. W. V. O. Quine (1954) « Carnap and Logical Truth » reprinted in W. V. O. Quine (1961) The Ways of Paradox and Other Essays, Harvard UP, Cambridge, MA.

[13] For the notions of indicator and proxies see K. Davis, B. Kingsbury, S. Engle Marry (2010) “Indicators as a Technology of Global Governance”, IILJ Working Paper 2010/2, New York University School of Law; G. Origgi (2008) “Un certain regard. Pour une épistémologie de la reputation”, Rome. Workshop on Reputation. April 19-22.

[14] Cf. S. Shapin (2008) The Scientific Life, Chicago University Press, p.4.

On the Epistemic Value of Reputation. The place of ratings and reputational tools in knowledge organization

Submission for the Eleventh International ISKO Conference 2010
Paradigms and conceptual systems in KO
February 23, 2010 – February 26, 2010

by Gloria Origgi and Judith Simon


Abstract: In this paper we want to explore the epistemological relevance and value of reputation understood as evaluative social information. Using reputation to classify and assess an agent or an item can be epistemologically useful in the absence or - as is especially relevant today - overabundance of information. However, in order to be and remain epistemically useful and ethically just it has to be open to constant scrutiny and revision. We will introduce a model of rational consensus as an example for the rational use of reputation for epistemic purpose before analyzing different reputational tools on the web. We will conclude our paper with a critical comment on the potential danger of using social information to evaluate information and knowledge claims, resp. to warn from epistemic injustices on the web and elsewhere.

1: Introduction

What is that scarlet piece of tissue in the shape of an A sewn on Hester Prynne's gown in Nathaniel Hawthorne's masterpiece The Scarlet Letter? Is it a symbol of her sin, a "badge of shame", an indelible sign of her community's contempt? Is it a cruel reminder of her past, a succinct history of her misdeeds? Imagine that in the same colonial New England village, you do not have just a badge for the poor Hester, but each member of the community wears a letter that represents some past records of its owner. We can also imagine sets of identical badges worn by members of the community who have similar records: sinners, heroes, drunkards....Imagine that the elders of the community have the right to attach these labels to the villagers. Their judgments, based on their purported wisdom, become an easy way for the villagers to dispose of a basic classification of social types within the community that will allow them to manage their relations with others, to make inferences and predictions about their behavior, that is, construct a basic "social map" that will help them orient in their society. Morally this may be questionable, but epistemologically it can be useful.
We want to explore in this paper, the epistemic value of this type of social information, that is, reputation, while being aware of the ethical and political problems that might come with using it for epistemic purpose. Using the judgment on past records to classify an agent or an item can be epistemologically useful in the absence or - as is especially relevant today - overabundance of information. But it has to be and remain open to constant scrutiny and revision to be epistemically useful and ethically just.

2: Reputation as Evaluative Social Information

Reputation is a special kind of social information: it is social information about the value of people, systems and processes that release information. We want to explore here the relationship between this special form of social information - that implies an evaluative stance - and the processes of knowledge organization and evaluation. More precisely, we want to argue not only that (1) we make use of other people's reputations to evaluate information, but also (2) within systems, like the Web, that make possible the easy and dynamic organization and re-organization of knowledge, our own rankings may determine new content and generate new categories.

Reputation is the informational track of our past actions, it is the credibility that an agent or an item earn through repeated interactions. We would like to defend an epistemological perspective according to which relying on reputational cues is an efficient way of shaping the too rich informational landscape around us by creating new relevant categories. Experts and authorities not only bloom where information is scanty, but also, and most crucially, in an information-dense world in which filtering out relevant information is our prominent cognitive activity. The epistemological enquiry we are advocating here implies that reputation and rating systems are an essential ingredient of collective processes of knowledge and play a cognitive role in extracting information. In an information-dense environment, where sources are in constant competition to get attention and the option of the direct verification of the information is often simply not available at reasonable costs, evaluation and rankings are epistemic tools and cognitive practices that provide an inevitable shortcut to information. We assume that there is no ideal knowledge that we can adjudicate without the access to previous evaluations and adjudications of others. No Robinson Crusoe’s minds that investigate and manipulate the world in a perfect solitude. Our modest epistemological prediction is that the higher is the uncertainty on the content of information, the stronger is the weight of the opinions of others in order to establish the quality of this content.
Of course, this opens the epistemological question of the epistemic value of these rankings and reputation mechanism, that it, to what extent their production and use by a community changes the ratio between truths and falsities produced by that community and, individually, how an awareness of rankings should affect a person’s beliefs. After all, rankings introduce a bias in judgment and the epistemic superiority of a biased judgment is in need of justification.

3: Rational Model for the Epistemic Use of Social Information

To illustrate how reputation understood as social information that comes with an evaluative stance can rationally be used for epistemic purpose, we introduce a formal model of rational consensus. In “Rational Consensus in Science and Society” Keith Lehrer and Carl Wagner develop their formal theory of consensus that rests upon the employment of consensual probabilities, utilities and weights and is meant to provide a model for rational decision making processes in science and society more generally ((Lehrer and Wagner 1981))). To our mind, this model is actually a model of how to quantify and use reputation for epistemic purpose.
Lehrer & Wagner argue that for decision making processes to be rational, it is central that all relevant information for the topic of concern has to be used ((Lehrer and Wagner 1981)). However, this spectrum of available information - for instance concerning disputes on scientific theories - is not limited to experimental information, but should also include the opinions of experts on other experts in the field. Lehrer calls this second type of information social information ((Lehrer 1990)) – and we call it reputation, i.e. social information that comes with an evaluative stance.
To illustrate how this social information might be used for epistemic purposes, Lehrer uses the so-called “expert dilemma” as a scenario. The expert dilemma describes the frequently encountered situation in which a decision has to be made despite the fact that evidence for answering a question is inconsistent and different experts recommend different options. An example would be whether or not to release a new medication or vaccine before all clinical trials are completed when facing the threat of an epidemic. The basic question of Lehrer & Wagner ((Lehrer and Wagner 1981)) is the following: If scientific dissent is prevailing, but suspension of judgment is not an option, how should the conflicting information be used to reach a consensual conclusion? “Consent on the reputation of the experts in order to decide on the issue” could be the motto of their approach. Social information is used here as a crucial factor to decide on content information.
Using reputation as a decisive factor for factual matter rests upon the assumption that each expert in a certain community might be more or less reliable or competent with respect to the specific question at stake. If that is the case, it would most rational to include each expert’s answer weighted by his competence regarding the issue. And the best way to assess the competence of each expert would be to use the aggregated reputation judgment of all other experts because they are most likely in the best position to judge the competence of their peers.
Lehrer & Wagner develop a quite complex mathematical model that describes an iterative and collective process to reach quantitative values for the reputation of each scientist ((Lehrer and Wagner 1981)). The basic idea however, is quite simple. The first step in this model consists in each expert giving a weight to all other experts summarizing all his information about the other’s expertise and reliability concerning the issue at stake, in other words: he gives a quantitative indicator of what he considers to be the reputation of the scientist with respect to topic at hand. In a second step, the average reputation values for each scientist are calculated with a specific algorithm and then laid open. Then in the second round, each expert has to reassess the reputation value he has given to all other members of the community, i.e. she has the chance to revise his or her judgment taking into account the average weights which the other members of the community have given to their fellows. Similarly to Delphi-studies in the social sciences, this process is then ideally repeated until finally a consensual weight for each member of a community is achieved ((Linestone and Turoff 2002)).
The idea is that, if you are less secure about the reputation of a certain researcher, you might tend more towards the group average in your second vote. If you are very sure about the reputation of someone, however, you will not let yourself be influenced by this average. If everyone acts this way, that is considered to be most rational, then the consensus that is finally achieved is considered to be the most rational consensus. Crucially, once these consensual weights are achieved, they can be applied to answering the question of concern by weighting each member’s vote on the issue with their consensual personal weight of reputation.
So, what should be obvious is that reputational cues, i.e. social information about other people that is evaluative, are being used – and that they are useful. Clearly, not all epistemic usage of reputation cues has to follow such a formal method. Quite on the contrary, ratings and other reputational tools might be used in a variety of different ways on the Web and our everyday life more generally. Nonetheless, Lehrer & Wagner’s model delivers a clear example of the potential that reputation understood as social information from an evaluative stance, can have for epistemic tasks ((Lehrer and Wagner 1981)).

4: Reputational Tools on the Web

What the Web makes possible today is an algorithmic treatment of methods of gathering social information to extract knowledge. Ratings and rankings on the Web are the result of collective human registered activities with artificial devices. However, the control of the heuristics and techniques that underlie this dynamics of information may be out of sight or incomprehensible for the users who find themselves in the very vulnerable position of relying on external sources of information through a dynamic, machine-based channel of communication whose heuristics and biases are not under their control. Thus, the reputational tools that are proliferating on the Web should be scrutinized by epistemically responsible users who do not want to accept too naïvely the outcome of a process they do not control.
The role of these reputational tools to filter information is getting more and more central in our Web-based epistemic practices ((Origgi 2009), (Origgi 2007)). And even more explicitly, we state that those systems that embody an access to others’ judgments and rankings are rapidly outperforming, in terms of reliability, the random aggregation of multiple judgments and preferences on which many systems were based, as it is shown by the growing impact of the Web 2.0 on our epistemic practices. A growing number of examples of architectures on the Web show how these rankings work to produce new arrangements of information.
The Web 2.0 has provided the underlying networking structure to share ranked preferences. If you take the Web of the early years of 2000, one of the main feature that attracted much attention and criticism was the possibility to "customize" information for each user in order to fit each one's special needs and purposes of navigation. The endless potential of re-organization of the new, dynamic, information architectures based on the aggregation of chunks of contents according to specific rules (in contrast with the rigid tree-structures of the first-generation of web pages) opened the opportunity to create and organize "content on demand". News websites, online stores, search-engines, etc thus started to provide "My-" features to the users, that is, easily arranged customized pages with targeted news and other information for the users, personalized lists of products, personalized recommendations etc. This gave rise to a series of positive expectations and negative warnings, such as the risk of neglecting other people's points of views and perspectives by concentrating only on personally relevant information (cf. (Sunstein 2002)). Now, thanks to the social Web, these systems are evolving into systems of shared preferences, in which people can rely on someone else's preferences and ranking to construct their own categorization of information. Examples of this preferences-sharing are website such as Del.icio.us in which you can share your bookmarks with other people, or Flickr, in which, for each uploaded photo, not only you can see who uploaded it, but also who are the profiles that added it among their favorite pictures. Combining information about who comments on an image, who adds it as favorite, who tags it and how, Flickr now provides a new feature for browsing images: interestingness, http://www.flickr.com/explore/interesting/ which is an example of preference-based tools of categorization. As a Flickr user, I can decide to generate new categories of contents on the basis of an interestingness scale. A new category of the most interesting images on Flickr today is thus generated by sorting others' preferences. The success of this "fluid" way of constructing concepts and categories may depend also on the fact that it matches our cognitive capacities: it has been shown by cognitive psychologists (cf. (Barsalou 1995)) that concepts and mental categories are flexibly constructed in context.
In this perspective, the EC project LiquidPublication, (http://project.liquidpub.org/) in which both authors are involved, aims at developing "liquid" architectures for producing, accessing and gathering scholarly information on the Web. Take for example the very concept of an academic journal: it is a selection of content based on a series of criteria of categorization: ISBN number, date of issue, etc. What we are working at in this project is a model of "Liquid Journal" which easily allows people to create selections of papers, articles, blog entries as a "My-journal" and then share them on the Web. One can imagine that, with the diffusion of such a model, the very category of "academic journal", or "journal issue" will be re-created by this particular form of information sharing, in which a user X can "conceptualize" a journal issue as for example: "all the content that the user Y is selecting in her journal". Here again, preferences of a user can be used by other people to re-organize information in a creative way. Virological examples of information diffusion based on a Twitter-logic of followers and leaders may be another example worth mentioning of reputational tools that create new categories of information.
Although the information-dense environment provided by the Web is the obvious locus in which examples bloom, we do not think that our analysis should be restricted to the case of the Web: in many other domains where information about the items at stake is very costly or difficult to obtain, reputational cues become an unavoidable way of organizing knowledge. Different cultural domains such as wine labeling systems and academic citation systems are based on rating devices that classify the underlying information by evaluating it (see (Origgi 2007), (Origgi 2009)).
5: Epistemic Injustices: On the Dangers of Using Social Information for Epistemic Purposes
The model of rational consensus as well as the Web applications that we have introduced are clearly examples of how reputation can be used to decide on content information, resp. on how social and content information might be productively merged to achieve better epistemic results. However, where there is use, there also is potential misuse. And in the case of reputational cues, these dangers might be inherent in the very concept of reputation as the “recognition by other people of some characteristic or ability” ((Merriam-Webster-Online-Dictionary 2009)).
More precisely there are two threats. First of all, the use of reputation to assess content can be epistemically beneficial while being morally questionable. This problem already becomes obvious in the first example we chose to open this article: Hawthorne’s A-shaped scarlet piece of tissue. Although classifying someone as a sinner, hero or drunkard – or as an expert, layperson or lobbyist - based on some cues might prove epistemically useful in certain situations, we would have to decide whether we are willing to pay the moral price of possible discrimination that comes with such stereotypical evaluation. More generally, once social information is taken into account to rate the quality of content, the door is open for social biases, prejudices and discrimination, which are as prevalent on the Web as in the societies that have developed and maintained it. These problems are not new and have long been identified for science and other epistemic fields by feminist epistemologists. In addition to raising awareness about these problems, various scholars have also developed tools and strategies to counter these epistemic injustices ((Fricker 2007), (Scheman 2001), (Alcoff 2001)). Miranda Fricker for instance distinguishes between testimonial and hermeneutic injustices as two instances in which someone is wronged in his capacity as a knower based on his social position. According to her “testimonial injustice occurs when prejudice causes a hearer to give a deflated level of credibility to a speaker’s word, whereas hermeneutic injustice “[...] occurs at a prior stage, when a gap in collective interpretative resources puts someone at an unfair disadvantage when it comes to making sense of their social experience” ((Fricker 2007) 1). Clearly, both forms of injustice are easily conceivable when reputational cues and their epistemic usage are not critically reflected upon and kept open for constant scrutiny and revision.
The second problem concerns the limits of the epistemic usefulness of this type of information itself. The first question is how you calculate the reputation of someone else in the first place, resp. which proxies you use. Do you use the person’s academic development, his institutional background, some form of communal evaluation, such as ratings or recommendations that he has received from other people as a cue to assess someone’s reputation? Do you rely on your own experience with her? On some indicator of the quality of his former research? On her track record of different academic achievements? Her H-index or impact factor? Which of these proxies are valid and which are not? The second crucial questions concerns the stability of reputation, resp. the way you deal with evidence that supports or contradicts your view on the reputation of others. When, under which conditions and up to which point of counter-evidence or you warranted in keeping your reputation value for someone or something? Clearly, these issues as crucial as they are cannot be answered given the brevity of this paper. However, if we want to explore the utility of reputation for epistemic purposes, we have to analyze the potentials and possible dangers very carefully. That reputation is used to assess information and epistemic claims goes without saying – and it comes with benefits as much as with problems. So the question should be less how to avoid using reputation as epistemic tools, but rather how to use them wisely.
6: Conclusion
Our preliminary analyses indicate that ratings and reputational tools in knowledge organization have epistemological, cognitive, practical as well as ethical implications. From an epistemological point of view, a priority of rating tools and reputational scales over classification leads to a re-conceptualization of the “facts/values” dichotomy. Another epistemologically pressing question concerns the validity of reputation mechanism as epistemological tools. How epistemically warranted is the use of these tools? Is it just based on blind and imperfect heuristics that have a serendipitous effect on our search of information, or is it possible to conceive second order epistemic criteria that allow us to pry apart “good” and “bad” practices of trust and reliance on these reputational metrics?
For cognition, this implies to take into account a pragmatically oriented way of creating concepts and categories (i.e. the most “valued”, items preferred by “x”), as it has already been argued in some works in cognitive psychology (cf. (Barsalou 1995)). From a practical point of view, this perspective may help to rethink the bottom up/top down distinction in designing categories by suggesting ways in which rating systems can serve as middle-ground categorizations that are neither imposed from above, not completely generated from spontaneous tagging. Rather they are user-driven meta-categorizations that inform the users.
The ethical and political aspects become obvious when taking feminist critique concerning the danger of epistemic injustices into account. Miranda Fricker’s emphasis of the danger of testimonial and hermeneutic injustices are particularly pressing when reputational cues are used uncritically. It is especially when reputation mechanisms become automatized in algorithms, there is a clear danger that epistemic injustices are inscribed in and reinforced by technology. Such an entanglement between ethics and epistemology in information design has been shown for trust-aware recommender systems((Simon 2008; Simon 2009)). Different trust metrics not only yield to different search results, but that they also correspond to different views concerning the organization as well as even more fundamentally the very concept of knowledge. Moreover, different trust metrics value different people differently and depending on the algorithm, some users are automatically silenced and “sorted out” ((Bowker and Star 1999)), while others “count”. Thus, when developing reputational tools, the possibility of injustices has to be accounted for.
This example suggest that a purely epistemological or cognitive analysis of using reputation for epistemic purposes will not suffice for knowledge organization: the goals and standards for knowledge organization and epistemic practices have to be discussed and decided upon taking political and ethical considerations into account. Reputational tools open up new possibilities for knowledge organization, but they also bring with them their own problems. Raising awareness for the values as well as the dangers of using reputational cues for epistemic assessment will be the major goal of our talk.

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