Evaluating digital sources

Editorial
Evaluating digital sources: Trust,
truth and lies
How do you evaluate the contents of a wiki, blog or
discussion forum? How do you distinguish fake news from
legitimate reporting? Information professions are often
required to evaluate the veracity of sources that have relatively
poor provenance. Yet the bases on which these judgements
are made are often poorly understood. We
sometimes fall back on established checklist approaches
to explain the decisions we have already made. But new
research into the nature and flaws of human reasoning suggests
that a more organic approach to evaluating digital
information might be better. Mercier and Sperber’s The
Enigma of Reason (2017) explores the evolution of human
reasoning as part of a social process, and perhaps suggests
new ways of understanding information evaluation.
Evaluation has a long history in library and information
science; over time the methods that have been developed
have tended to rely on analytical approaches. These analytical
approaches generally involve disaggregating source
materials into a number identifiable attributes which can
be individually evaluated and compared to ascertain the
reliability of the source material itself. These attributes are
sometimes presented in the form of a checklist, and typically
focus on characteristics such as source, accuracy,
authority, balance, content and coverage, currency and so
on. Underpinning analytical approaches are a series of
indices of quality, reliability and authority. We should prefer
current information to old information, authoritative
sources to informal sources, impartial or disinterested
information to partial or interested information, attributed
information to unattributed information, superficially accurate
information to superficially inaccurate information and
so on. In many ways, these analytical categories can be
reduced to the idea of provenance: securing the source and
its trustworthiness against characteristics that we have traditionally
associated with trustworthy sources.
This approach to evaluation reflects the habits of the
printing and broadcasting tradition. In the recent past,
information was predominantly disseminated through a
limited number of media and publishing channels. The
limited bandwidth of the information infrastructure acted
to filter information prior to publishing or broadcast. As a
consequence, provenance became synonymous with quality
and reliability.
But the digital age presents specific challenges to this
approach; the proliferation of recorded information via
digital networks complicates traditional methods of
evaluation. Over the recent past, the volume of recorded
information in existence has grown exponentially (von
Baeyer, 2003; Conway, 1996). Cheap and easy to produce,
information now flows through countless shallow channels
scored into the web, social media and mobile communications.
But while digital culture has largely moved away
from pre-filtering approaches to publication turning instead
to post-publication filtering through algorithms and user
behaviour, the vestiges of authority, authenticity and trust
established in the age of print remain. Those vestiges of
provenance have become open to appropriation by the new
digital sources of information.
One example has been the growing problem of fake
news. Designed to be disseminated via social media, fake
news is content that presents itself as traditional journalism
(either by mimicking the style and presentation of traditional
news sources or appropriating the reputation of
respected news organizations) but that presents a partial,
inaccurate and politically motivated account. It has chiefly
been associated with the right of politics. The influence of
fake news in the 2016 US presidential election and the 2016
Brexit referendum has been of widespread concern, and
many of the leading social media companies have pledged
to tackle the problem. Fake news has now also become a
political tool used to discredit reputable journalism. US
President Donald Trump and his supporters have, for example,
accused a host of mainstream news organizations of
fake news. The then education secretary Michael Gove
courted controversy when he declared in 2016 that ‘people
in this country have had enough of experts’ (Mance, 2016).
Some followers of the British Labour Party leader Jeremy
Corbyn have used the label to describe mainstream journalism
that they disagree with. Uncertainty about the veracity
of information generally is open to be used as a political
tool to discredit public scrutiny of policy, and in some sense
all claims to truth are undermined.
Fake news presents an interesting case study of the problem
of evaluation in the digital age. On the one hand, by
abandoning and pretence at impartiality, it violates the traditional
professional codes of journalistic practice. But on
the other hand, it can be seen as part of a spectrum of
content in which all ‘news’ and all information is irrevocably
partial and biased either in selection or presentation,
and reflects the political motivations of those creating, disseminating
and to a lesser degree consuming it. The existence
of this spectrum from publications of record to
Business Information Review
2017, Vol. 34(4) 172–175
ª The Author(s) 2017
Reprints and permission:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/0266382117743370
journals.sagepub.com/home/bir
outright fabrications means that naive notions of securing
both journalistic standards and evaluation of content
against undisputed facts, unbiased reportage or political
balance break down. Fake news plays to the bias of its
audience by reinforcing their existing values and beliefs
and discrediting information that might challenge those
values and beliefs, yet fake news is not always easy to
identify from its source alone. Swaine has observed that:
readers are now being confronted with an even tougher challenge:
decoding the work of writers whose track records of
faulty reporting are occasionally interrupted by stories that are
actually true. (Swaine, 2017)
The challenge of inaccurate information and misinformation
on the Internet is therefore more significant than it
appears at first glance. There is no clear-cut differentiation
between reliable and unreliable sources; no blanket tests
that we can apply; all sources of information on the web
blend truths and mistruths to varying degrees and each has
to be taken on its own merits; and all claims over the
veracity of particular sources will themselves be contested.
And this widespread assault on questions of truth and trustworthiness
in digital culture makes evaluation both more
vital and more problematic.
Truth, lies and human reasoning
There is however a more fundamental reason why analytical
approaches to evaluation sometimes fail. Humans are
spectacularly bad at reasoning. Although individuals may
vary in their ability to reason effectively, we are all similar
in our inability to recognize bias in our thought processes.
The ways in which human reasoning fails are relatively
predictable and well understood. Some of the most common
biases in our thinking habits relevant to information
evaluation are outlined below (cognitive biases have been
widely researched and written about, but a useful overview
is provided by Sutherland (1992):
Ambiguity effect: The tendency to perceive unambiguous,
clear and straightforward information as
more truthful than ambiguous information. Ambiguity
effect has an influence on how information is
reported and prepared for reporting; the tendency
within journalism, for example, to eradicate ambiguity
can distort the truthfulness of what has been
reported. Not only do we seek unambiguous
accounts but we are also likely to be misled by
accounts that falsely lack ambiguity.
Authority bias: The tendency to attribute more significance
to statements from authority figures even
in regard to areas beyond the scope of their authority.
We are drawn to trust the statements of figures or
organizations we perceive as authoritative and
subject them to less scrutiny than those of figures
whose authority we cannot judge or are in doubt
about.
Availability bias: We tend to overestimate the significance
of information that is easy to come by and
underestimate the significance of information that is
scarce. This is particularly a problem in any kind of
research process, including commercial information
research where much information that is readily
available may be untrustworthy. For example, a typical
approach to reputation management is to drown
out negative reporting with planted positive news
stories.
Bias blind spot: The tendency to believe that we are
individually better at spotting bias than other people
(including our own biases) and that other people are
less good at recognizing bias than we are. Everyone
does this, even people who know that everyone does
this.
Clustering illusion: The tendency to attribute false
significance to clusters within random distributions,
or to see patterns of cause and effect that are not
there. This is particularly a problem when there is
a limited amount of data available and exacerbated
in digital contexts where content providers sometimes
rely on republishing material from other
sources.
Cognitive dissonance effect: The tendency to reduce
inconsistency in our values and beliefs by exaggerating
our confidence in the choices we make
between equally weighted options and discounting
further information that contradicts those choices.
Or in other word, once we have decided on the truth
or otherwise of something, we look for reasons to
further justify that belief.
Confirmation bias: The tendency to attribute more
significance to information that confirms our existing
beliefs or that confirms what we would like to
believe than to information that disconfirms either of
those things.
Focusing effect: The tendency to explain all phenomena
through the lens of a particular issue or
belief with which we are preoccupied.
Illusory truth effect: The tendency to form the belief
that information or claims to which we have been
exposed repeatedly must be truthful.
The fact of these biases complicates the issue of information
evaluation in three ways. In the first place, these
kinds of cognitive biases exist within the resources that we
might be evaluating. Secondly, when evaluating information
we are in danger of being misled by our own intrinsic
capacity to look for patterns that do not exist. Finally, the
fact of cognitive biases is a resource to be exploited by
those who are seeking to manipulate the ways in which
Editorial 173
we think about the world, as in the case of reputation management
described above.
Cognitive bias is so ingrained in our habits that in some
ways it is a mistake to think of them as biases at all; they
are just the ways in which we make sense of the world
around us. Understanding why we think in these kinds of
ways may help us develop new ways of approaching
information evaluation. In a recent series of research,
Mercier and Sperber (2011, 2017) account for the welldocumented
failures of reason by framing its evolution in
response to a social context of persuasion and social trust.
Reasoning functions, they argue, not to help us ascertain
the truths of a situation per se, but to supply us with good
reasons in advocating for particular ways of seeing the
world. In this process, the truths of the matter barely play
a part. They suggest:
The main function of reasoning is argumentative: Reasoning
has evolved and persisted mainly because it makes human
communication more effective and advantageous. (2011: 60)
One consequence of this is that the kinds of cognitive
biases discussed above can be seen as not a flaw in reasoning
but as a tool in persuasion; if, as Mercier and Sperber
imply, our task is to advocate for particular ideas, then we
are better searching for good reasons than balanced arguments.
The argumentative function of reasoning distances
evaluation from notions of truth. Thus, Sperber argues bias
in reasoning evolved to improve our reasoning processes,
making us better equipped to advocate for our beliefs a
point rather than to recognize a truth.
More important perhaps is the implication of this
social persuasive function of human reasoning is that all
reasoning is necessarily situated; there is no such thing
as a neutral argument – arguments are always seeking
to persuade us of a particular state of affairs and always
relying on rhetorical tricks in maximizing that
persuasiveness. It does not matter how trustworthy or
authoritative the source, how steeped in accolades, qualifications
or expertise, they are still trying to persuade
us to particular ways of seeing the world and truth is
only one weapon in their arsenal. It follows that there is
no such thing as neutral information; all human information
exists because it was produced for a purpose, for
specific ends, and to support specific and defined world
views, and much information exists explicitly as a part
of a process of persuading us about the truth of particular
states of affairs. This is in fact rather like what we
see in digital publishing, where the structural limitations
on disseminating information of a previous age have
largely been removed.
Understanding the flaws in human reasoning makes it
clear that analytical approaches to evaluating information can
sometimes domore harmthan good. Rather than as we might
imagine eradicating bias, they may merely give the
impression of its eradication, leaving us overconfident not
only in the choices we make but also the reasons we ascribe
to those choices.That is to say that such approaches furnish us
with a series of good reasons to defend the choiceswemake in
evaluation, while doing little to guide or aid those choices.
The analytical method is, from this perspective, another
rhetorical tool in the art of persuasion, a way of securing our
opinion against some putatively objective framework.
Nevertheless, while we are in some sense hardwired to
extrapolate from incomplete or limited information, we can
also use this understanding to our advantage. At the heart of
effective information evaluation are a series of softer skills
and competencies that are impossible to delineate, but that
arise from experience, aptitude and outlook.All evaluation in
the kinds of contexts in which commercial information professionals
work is driven by context, and an important component
in that context is the subjective outlook and experience
of the individual themselves. Mercier and Sperber’s account
of the evolution of reason contains the observation that bias
has an important function in the ways in whichwe think about
the world. Our cognitive biases are not flaws in thinking, but
advantages in advocacy, in which context reason takes on a
more pragmatic function. Good reasons become the most
persuasive reasons that we can marshal in support of an argument,
rather than necessarily the most truthful.
And there are two aspects to the ways in which cognitive
bias functions that serve us well in evaluation. The first is
the well-documented fact that we are far better at spotting
the obvious bias in other people’s arguments than we are in
our own. Mercier and Sperber note:
there is an asymmetry between the production of arguments,
which involves an intrinsic bias in favor of the opinions or
decisions of the arguer whether they are sound or not, and the
evaluation of arguments, which aims at distinguishing good
arguments from bad ones and hence genuine information from
misinformation [ . . . ] people are good at assessing arguments
and are quite able to do so in an unbiased way, provided
they have no particular axe to grind. (Mercier and Sperber,
2011: 72)
The second aspect is that where reason fails us, instinct
and intuition are often more reliable than we assume them
to be. Kahneman (2012) has distinguished between two
kinds of cognitive systems involved in deliberation which
he calls system 1 and system 2. System 1 is the fast, automatic
and emotionally driven part of cognition that we
often think of as gut feeling or instinct. System 2 is the
slow and deliberative part of cognition that we often think
of as reasoning. These two parts of our thinking processes
often come to very different conclusions about the world
and are often therefore somewhat in conflict. However, the
surprising factor is that the fast, emotionally driven system
1 in many cases proves to be more reliable than the more
deliberative system 2.
174 Business Information Review 34(4)
Emerging from this are two tests that we can apply to
digital information sources (coherence and persuasiveness),
and two habits we need to relearn: trusting our professional
instincts and experience and approaching evaluation from a
disinterested position. As outlined above, precognitive
instincts tend to be more reliable than not, especially in areas
where we can profess expertise, and have no particular
vested interest. It is in searching for good reasons to justify
our existing beliefs and desires that reasoning fails us.
The evaluation of information in the digital age is deeply
rooted in matters of trust: whether we trust what we are being
told; whether we trust those who are telling us; whether we
trust themeans bywhich this information has cometo us.And
this process involves an emotional response as much as an
intellectual response. Trust arises from applying what we
already know: our professional expertise and experience –
that tacit knowledge concerningwhat makes a reliable source
that we cannot fully articulate and that when articulated is
transformed into the kinds of reductive checklists that eradicates
the value of that expertise and reduces reliability of
provenance. This can be expressed in relation to two ideas:
The internal coherence of information: whether it
agrees with itself, whether it agrees with what we
would expect of that source and whether it agrees
with everything we already know and believe about
the topic or the wider context.
The persuasiveness of information: whether it tells
an account that – regardless of any bias we might
also be aware of – is intrinsically persuasive given
what we already know.
Checklists and analytical approaches come in perhaps
after the fact when we are seeking to persuade someone
else of the professional opinion about the veracity and
trustworthiness of the information in question.
But most importantly, the very fact of the information
professional as an individual who usually sits outside of the
contexts within which information is exploited – of is in
other words usually disinterested in the information that
they are evaluating – is a critical component in effective
evaluation. There has been in recent decades a tendency to
put research tools onto the desktops of end users. But if
research and evaluation is performed from a situation in
which there is a vested interest in the outcome then the
influence of cognitive bias will tend to increase. One series
of good reasons for the involvement of information professionals
in evaluation and research derives from both their
disinterested status and professional experience of undertaking
such evaluations.
December’s Business Information Review
December’s edition of Business Information Review contains
the usual mix of academic and professional articles.
First is an article by Judi Vernau, founding director of
Metataxis Ltd which specializes in building ontologies and
taxonomies. Entitled Using Ontology to Improve Access to
Information: The New Zealand Experience, Judi’s paper
described the development of an ontology intended to support
findability within an enterprise content management
system in the New Zealand Department of Conservation. It
explores in detail both the ontology itself and also the
comparative benefits and advantages of this approach.
Next is Ali Rezaeian and Rouhollah Bagheri’s paper
which explored knowledge networks, a means by which
to with which to support knowledge sharing and creation.
Entitled Modelling the Factors Affecting the Implementation
of Knowledge Networks, the paper looks at the state of
research around knowledge networks, and draws out the
success factors in their implementation. Next is a paper
by Antonio Mun˜oz-Can˜avate entitled Competitive Intelligence
in Spain: A Study of a Sample of Firms. This paper
reports on a survey of Spanish firms to explore the ways in
which they approach the challenges of competitive intelligence
and reveals the degree to which benchmarking and
SWOT analysis still factor as significant tools in real-world
corporate settings.
Our final article comes from Cerys Hearsey as part of the
Out-of-the-Box strand of tech-related articles. In her paper,
Cerys explores the growth of artificial intelligence in theworkplace.
Also in this issue is Martin White’s Perspectives column,
which addresses the role of meetings, remote working,
information culture and collaborative information seeking.
Luke Tredinnick and Claire Laybats
References
von Baeyer HC (2003) Information: the New Language of Science.
London: Weidenfeld & Nicolson.
Conway P (1996) Preservation in the digital world. Council on
Library and Information Resources. Available at: http://www.
clir.org/pubs/reports/conway2/ (accessed 03 May 2006).
Mance H (2016) Britain has had enough of experts, says Gove,
Financial Times. Available at: https://www.ft.com/content/
3be49734-29cb-11e6-83e4-abc22d5d108c (accessed 14
November 2017).
Mercier H, Sperber D (2011) Why do humans reason? Arguments
for an argumentative theory. Behavioral and Brain Sciences
34(2): 57–74.
Mercier H, Sperber D (2017) The Enigma of Reason: A New
Theory of Human Understanding. London: Allen Lane.
KahnemanD(2012) Thinking,Fast and Slow.London: PenguinBooks.
Sutherland S (1992/2013) Irrationality: The Enemy Within. London:
Pinter & Martin.
Swaine J (2017) New fake news dilemma: sites publish real scoops
amid mess of false reports. The Guardian. Available at: https://
www.theguardian.com/media/2017/may/16/fake-news-sites-re
ports-facts-louise-mensch (accessed 18 October 2017).
Editorial 175Editorial
Evaluating digital sources: Trust,
truth and lies
How do you evaluate the contents of a wiki, blog or
discussion forum? How do you distinguish fake news from
legitimate reporting? Information professions are often
required to evaluate the veracity of sources that have relatively
poor provenance. Yet the bases on which these judgements
are made are often poorly understood. We
sometimes fall back on established checklist approaches
to explain the decisions we have already made. But new
research into the nature and flaws of human reasoning suggests
that a more organic approach to evaluating digital
information might be better. Mercier and Sperber’s The
Enigma of Reason (2017) explores the evolution of human
reasoning as part of a social process, and perhaps suggests
new ways of understanding information evaluation.
Evaluation has a long history in library and information
science; over time the methods that have been developed
have tended to rely on analytical approaches. These analytical
approaches generally involve disaggregating source
materials into a number identifiable attributes which can
be individually evaluated and compared to ascertain the
reliability of the source material itself. These attributes are
sometimes presented in the form of a checklist, and typically
focus on characteristics such as source, accuracy,
authority, balance, content and coverage, currency and so
on. Underpinning analytical approaches are a series of
indices of quality, reliability and authority. We should prefer
current information to old information, authoritative
sources to informal sources, impartial or disinterested
information to partial or interested information, attributed
information to unattributed information, superficially accurate
information to superficially inaccurate information and
so on. In many ways, these analytical categories can be
reduced to the idea of provenance: securing the source and
its trustworthiness against characteristics that we have traditionally
associated with trustworthy sources.
This approach to evaluation reflects the habits of the
printing and broadcasting tradition. In the recent past,
information was predominantly disseminated through a
limited number of media and publishing channels. The
limited bandwidth of the information infrastructure acted
to filter information prior to publishing or broadcast. As a
consequence, provenance became synonymous with quality
and reliability.
But the digital age presents specific challenges to this
approach; the proliferation of recorded information via
digital networks complicates traditional methods of
evaluation. Over the recent past, the volume of recorded
information in existence has grown exponentially (von
Baeyer, 2003; Conway, 1996). Cheap and easy to produce,
information now flows through countless shallow channels
scored into the web, social media and mobile communications.
But while digital culture has largely moved away
from pre-filtering approaches to publication turning instead
to post-publication filtering through algorithms and user
behaviour, the vestiges of authority, authenticity and trust
established in the age of print remain. Those vestiges of
provenance have become open to appropriation by the new
digital sources of information.
One example has been the growing problem of fake
news. Designed to be disseminated via social media, fake
news is content that presents itself as traditional journalism
(either by mimicking the style and presentation of traditional
news sources or appropriating the reputation of
respected news organizations) but that presents a partial,
inaccurate and politically motivated account. It has chiefly
been associated with the right of politics. The influence of
fake news in the 2016 US presidential election and the 2016
Brexit referendum has been of widespread concern, and
many of the leading social media companies have pledged
to tackle the problem. Fake news has now also become a
political tool used to discredit reputable journalism. US
President Donald Trump and his supporters have, for example,
accused a host of mainstream news organizations of
fake news. The then education secretary Michael Gove
courted controversy when he declared in 2016 that ‘people
in this country have had enough of experts’ (Mance, 2016).
Some followers of the British Labour Party leader Jeremy
Corbyn have used the label to describe mainstream journalism
that they disagree with. Uncertainty about the veracity
of information generally is open to be used as a political
tool to discredit public scrutiny of policy, and in some sense
all claims to truth are undermined.
Fake news presents an interesting case study of the problem
of evaluation in the digital age. On the one hand, by
abandoning and pretence at impartiality, it violates the traditional
professional codes of journalistic practice. But on
the other hand, it can be seen as part of a spectrum of
content in which all ‘news’ and all information is irrevocably
partial and biased either in selection or presentation,
and reflects the political motivations of those creating, disseminating
and to a lesser degree consuming it. The existence
of this spectrum from publications of record to
Business Information Review
2017, Vol. 34(4) 172–175
ª The Author(s) 2017
Reprints and permission:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/0266382117743370
journals.sagepub.com/home/bir
outright fabrications means that naive notions of securing
both journalistic standards and evaluation of content
against undisputed facts, unbiased reportage or political
balance break down. Fake news plays to the bias of its
audience by reinforcing their existing values and beliefs
and discrediting information that might challenge those
values and beliefs, yet fake news is not always easy to
identify from its source alone. Swaine has observed that:
readers are now being confronted with an even tougher challenge:
decoding the work of writers whose track records of
faulty reporting are occasionally interrupted by stories that are
actually true. (Swaine, 2017)
The challenge of inaccurate information and misinformation
on the Internet is therefore more significant than it
appears at first glance. There is no clear-cut differentiation
between reliable and unreliable sources; no blanket tests
that we can apply; all sources of information on the web
blend truths and mistruths to varying degrees and each has
to be taken on its own merits; and all claims over the
veracity of particular sources will themselves be contested.
And this widespread assault on questions of truth and trustworthiness
in digital culture makes evaluation both more
vital and more problematic.
Truth, lies and human reasoning
There is however a more fundamental reason why analytical
approaches to evaluation sometimes fail. Humans are
spectacularly bad at reasoning. Although individuals may
vary in their ability to reason effectively, we are all similar
in our inability to recognize bias in our thought processes.
The ways in which human reasoning fails are relatively
predictable and well understood. Some of the most common
biases in our thinking habits relevant to information
evaluation are outlined below (cognitive biases have been
widely researched and written about, but a useful overview
is provided by Sutherland (1992):
Ambiguity effect: The tendency to perceive unambiguous,
clear and straightforward information as
more truthful than ambiguous information. Ambiguity
effect has an influence on how information is
reported and prepared for reporting; the tendency
within journalism, for example, to eradicate ambiguity
can distort the truthfulness of what has been
reported. Not only do we seek unambiguous
accounts but we are also likely to be misled by
accounts that falsely lack ambiguity.
Authority bias: The tendency to attribute more significance
to statements from authority figures even
in regard to areas beyond the scope of their authority.
We are drawn to trust the statements of figures or
organizations we perceive as authoritative and
subject them to less scrutiny than those of figures
whose authority we cannot judge or are in doubt
about.
Availability bias: We tend to overestimate the significance
of information that is easy to come by and
underestimate the significance of information that is
scarce. This is particularly a problem in any kind of
research process, including commercial information
research where much information that is readily
available may be untrustworthy. For example, a typical
approach to reputation management is to drown
out negative reporting with planted positive news
stories.
Bias blind spot: The tendency to believe that we are
individually better at spotting bias than other people
(including our own biases) and that other people are
less good at recognizing bias than we are. Everyone
does this, even people who know that everyone does
this.
Clustering illusion: The tendency to attribute false
significance to clusters within random distributions,
or to see patterns of cause and effect that are not
there. This is particularly a problem when there is
a limited amount of data available and exacerbated
in digital contexts where content providers sometimes
rely on republishing material from other
sources.
Cognitive dissonance effect: The tendency to reduce
inconsistency in our values and beliefs by exaggerating
our confidence in the choices we make
between equally weighted options and discounting
further information that contradicts those choices.
Or in other word, once we have decided on the truth
or otherwise of something, we look for reasons to
further justify that belief.
Confirmation bias: The tendency to attribute more
significance to information that confirms our existing
beliefs or that confirms what we would like to
believe than to information that disconfirms either of
those things.
Focusing effect: The tendency to explain all phenomena
through the lens of a particular issue or
belief with which we are preoccupied.
Illusory truth effect: The tendency to form the belief
that information or claims to which we have been
exposed repeatedly must be truthful.
The fact of these biases complicates the issue of information
evaluation in three ways. In the first place, these
kinds of cognitive biases exist within the resources that we
might be evaluating. Secondly, when evaluating information
we are in danger of being misled by our own intrinsic
capacity to look for patterns that do not exist. Finally, the
fact of cognitive biases is a resource to be exploited by
those who are seeking to manipulate the ways in which
Editorial 173
we think about the world, as in the case of reputation management
described above.
Cognitive bias is so ingrained in our habits that in some
ways it is a mistake to think of them as biases at all; they
are just the ways in which we make sense of the world
around us. Understanding why we think in these kinds of
ways may help us develop new ways of approaching
information evaluation. In a recent series of research,
Mercier and Sperber (2011, 2017) account for the welldocumented
failures of reason by framing its evolution in
response to a social context of persuasion and social trust.
Reasoning functions, they argue, not to help us ascertain
the truths of a situation per se, but to supply us with good
reasons in advocating for particular ways of seeing the
world. In this process, the truths of the matter barely play
a part. They suggest:
The main function of reasoning is argumentative: Reasoning
has evolved and persisted mainly because it makes human
communication more effective and advantageous. (2011: 60)
One consequence of this is that the kinds of cognitive
biases discussed above can be seen as not a flaw in reasoning
but as a tool in persuasion; if, as Mercier and Sperber
imply, our task is to advocate for particular ideas, then we
are better searching for good reasons than balanced arguments.
The argumentative function of reasoning distances
evaluation from notions of truth. Thus, Sperber argues bias
in reasoning evolved to improve our reasoning processes,
making us better equipped to advocate for our beliefs a
point rather than to recognize a truth.
More important perhaps is the implication of this
social persuasive function of human reasoning is that all
reasoning is necessarily situated; there is no such thing
as a neutral argument – arguments are always seeking
to persuade us of a particular state of affairs and always
relying on rhetorical tricks in maximizing that
persuasiveness. It does not matter how trustworthy or
authoritative the source, how steeped in accolades, qualifications
or expertise, they are still trying to persuade
us to particular ways of seeing the world and truth is
only one weapon in their arsenal. It follows that there is
no such thing as neutral information; all human information
exists because it was produced for a purpose, for
specific ends, and to support specific and defined world
views, and much information exists explicitly as a part
of a process of persuading us about the truth of particular
states of affairs. This is in fact rather like what we
see in digital publishing, where the structural limitations
on disseminating information of a previous age have
largely been removed.
Understanding the flaws in human reasoning makes it
clear that analytical approaches to evaluating information can
sometimes domore harmthan good. Rather than as we might
imagine eradicating bias, they may merely give the
impression of its eradication, leaving us overconfident not
only in the choices we make but also the reasons we ascribe
to those choices.That is to say that such approaches furnish us
with a series of good reasons to defend the choiceswemake in
evaluation, while doing little to guide or aid those choices.
The analytical method is, from this perspective, another
rhetorical tool in the art of persuasion, a way of securing our
opinion against some putatively objective framework.
Nevertheless, while we are in some sense hardwired to
extrapolate from incomplete or limited information, we can
also use this understanding to our advantage. At the heart of
effective information evaluation are a series of softer skills
and competencies that are impossible to delineate, but that
arise from experience, aptitude and outlook.All evaluation in
the kinds of contexts in which commercial information professionals
work is driven by context, and an important component
in that context is the subjective outlook and experience
of the individual themselves. Mercier and Sperber’s account
of the evolution of reason contains the observation that bias
has an important function in the ways in whichwe think about
the world. Our cognitive biases are not flaws in thinking, but
advantages in advocacy, in which context reason takes on a
more pragmatic function. Good reasons become the most
persuasive reasons that we can marshal in support of an argument,
rather than necessarily the most truthful.
And there are two aspects to the ways in which cognitive
bias functions that serve us well in evaluation. The first is
the well-documented fact that we are far better at spotting
the obvious bias in other people’s arguments than we are in
our own. Mercier and Sperber note:
there is an asymmetry between the production of arguments,
which involves an intrinsic bias in favor of the opinions or
decisions of the arguer whether they are sound or not, and the
evaluation of arguments, which aims at distinguishing good
arguments from bad ones and hence genuine information from
misinformation [ . . . ] people are good at assessing arguments
and are quite able to do so in an unbiased way, provided
they have no particular axe to grind. (Mercier and Sperber,
2011: 72)
The second aspect is that where reason fails us, instinct
and intuition are often more reliable than we assume them
to be. Kahneman (2012) has distinguished between two
kinds of cognitive systems involved in deliberation which
he calls system 1 and system 2. System 1 is the fast, automatic
and emotionally driven part of cognition that we
often think of as gut feeling or instinct. System 2 is the
slow and deliberative part of cognition that we often think
of as reasoning. These two parts of our thinking processes
often come to very different conclusions about the world
and are often therefore somewhat in conflict. However, the
surprising factor is that the fast, emotionally driven system
1 in many cases proves to be more reliable than the more
deliberative system 2.
174 Business Information Review 34(4)
Emerging from this are two tests that we can apply to
digital information sources (coherence and persuasiveness),
and two habits we need to relearn: trusting our professional
instincts and experience and approaching evaluation from a
disinterested position. As outlined above, precognitive
instincts tend to be more reliable than not, especially in areas
where we can profess expertise, and have no particular
vested interest. It is in searching for good reasons to justify
our existing beliefs and desires that reasoning fails us.
The evaluation of information in the digital age is deeply
rooted in matters of trust: whether we trust what we are being
told; whether we trust those who are telling us; whether we
trust themeans bywhich this information has cometo us.And
this process involves an emotional response as much as an
intellectual response. Trust arises from applying what we
already know: our professional expertise and experience –
that tacit knowledge concerningwhat makes a reliable source
that we cannot fully articulate and that when articulated is
transformed into the kinds of reductive checklists that eradicates
the value of that expertise and reduces reliability of
provenance. This can be expressed in relation to two ideas:
The internal coherence of information: whether it
agrees with itself, whether it agrees with what we
would expect of that source and whether it agrees
with everything we already know and believe about
the topic or the wider context.
The persuasiveness of information: whether it tells
an account that – regardless of any bias we might
also be aware of – is intrinsically persuasive given
what we already know.
Checklists and analytical approaches come in perhaps
after the fact when we are seeking to persuade someone
else of the professional opinion about the veracity and
trustworthiness of the information in question.
But most importantly, the very fact of the information
professional as an individual who usually sits outside of the
contexts within which information is exploited – of is in
other words usually disinterested in the information that
they are evaluating – is a critical component in effective
evaluation. There has been in recent decades a tendency to
put research tools onto the desktops of end users. But if
research and evaluation is performed from a situation in
which there is a vested interest in the outcome then the
influence of cognitive bias will tend to increase. One series
of good reasons for the involvement of information professionals
in evaluation and research derives from both their
disinterested status and professional experience of undertaking
such evaluations.
December’s Business Information Review
December’s edition of Business Information Review contains
the usual mix of academic and professional articles.
First is an article by Judi Vernau, founding director of
Metataxis Ltd which specializes in building ontologies and
taxonomies. Entitled Using Ontology to Improve Access to
Information: The New Zealand Experience, Judi’s paper
described the development of an ontology intended to support
findability within an enterprise content management
system in the New Zealand Department of Conservation. It
explores in detail both the ontology itself and also the
comparative benefits and advantages of this approach.
Next is Ali Rezaeian and Rouhollah Bagheri’s paper
which explored knowledge networks, a means by which
to with which to support knowledge sharing and creation.
Entitled Modelling the Factors Affecting the Implementation
of Knowledge Networks, the paper looks at the state of
research around knowledge networks, and draws out the
success factors in their implementation. Next is a paper
by Antonio Mun˜oz-Can˜avate entitled Competitive Intelligence
in Spain: A Study of a Sample of Firms. This paper
reports on a survey of Spanish firms to explore the ways in
which they approach the challenges of competitive intelligence
and reveals the degree to which benchmarking and
SWOT analysis still factor as significant tools in real-world
corporate settings.
Our final article comes from Cerys Hearsey as part of the
Out-of-the-Box strand of tech-related articles. In her paper,
Cerys explores the growth of artificial intelligence in theworkplace.
Also in this issue is Martin White’s Perspectives column,
which addresses the role of meetings, remote working,
information culture and collaborative information seeking.
Luke Tredinnick and Claire Laybats
References
von Baeyer HC (2003) Information: the New Language of Science.
London: Weidenfeld & Nicolson.
Conway P (1996) Preservation in the digital world. Council on
Library and Information Resources. Available at: http://www.
clir.org/pubs/reports/conway2/ (accessed 03 May 2006).
Mance H (2016) Britain has had enough of experts, says Gove,
Financial Times. Available at: https://www.ft.com/content/
3be49734-29cb-11e6-83e4-abc22d5d108c (accessed 14
November 2017).
Mercier H, Sperber D (2011) Why do humans reason? Arguments
for an argumentative theory. Behavioral and Brain Sciences
34(2): 57–74.
Mercier H, Sperber D (2017) The Enigma of Reason: A New
Theory of Human Understanding. London: Allen Lane.
KahnemanD(2012) Thinking,Fast and Slow.London: PenguinBooks.
Sutherland S (1992/2013) Irrationality: The Enemy Within. London:
Pinter & Martin.
Swaine J (2017) New fake news dilemma: sites publish real scoops
amid mess of false reports. The Guardian. Available at: https://
www.theguardian.com/media/2017/may/16/fake-news-sites-re
ports-facts-louise-mensch (accessed 18 October 2017).
Editorial 175Editorial
Evaluating digital sources: Trust,
truth and lies
How do you evaluate the contents of a wiki, blog or
discussion forum? How do you distinguish fake news from
legitimate reporting? Information professions are often
required to evaluate the veracity of sources that have relatively
poor provenance. Yet the bases on which these judgements
are made are often poorly understood. We
sometimes fall back on established checklist approaches
to explain the decisions we have already made. But new
research into the nature and flaws of human reasoning suggests
that a more organic approach to evaluating digital
information might be better. Mercier and Sperber’s The
Enigma of Reason (2017) explores the evolution of human
reasoning as part of a social process, and perhaps suggests
new ways of understanding information evaluation.
Evaluation has a long history in library and information
science; over time the methods that have been developed
have tended to rely on analytical approaches. These analytical
approaches generally involve disaggregating source
materials into a number identifiable attributes which can
be individually evaluated and compared to ascertain the
reliability of the source material itself. These attributes are
sometimes presented in the form of a checklist, and typically
focus on characteristics such as source, accuracy,
authority, balance, content and coverage, currency and so
on. Underpinning analytical approaches are a series of
indices of quality, reliability and authority. We should prefer
current information to old information, authoritative
sources to informal sources, impartial or disinterested
information to partial or interested information, attributed
information to unattributed information, superficially accurate
information to superficially inaccurate information and
so on. In many ways, these analytical categories can be
reduced to the idea of provenance: securing the source and
its trustworthiness against characteristics that we have traditionally
associated with trustworthy sources.
This approach to evaluation reflects the habits of the
printing and broadcasting tradition. In the recent past,
information was predominantly disseminated through a
limited number of media and publishing channels. The
limited bandwidth of the information infrastructure acted
to filter information prior to publishing or broadcast. As a
consequence, provenance became synonymous with quality
and reliability.
But the digital age presents specific challenges to this
approach; the proliferation of recorded information via
digital networks complicates traditional methods of
evaluation. Over the recent past, the volume of recorded
information in existence has grown exponentially (von
Baeyer, 2003; Conway, 1996). Cheap and easy to produce,
information now flows through countless shallow channels
scored into the web, social media and mobile communications.
But while digital culture has largely moved away
from pre-filtering approaches to publication turning instead
to post-publication filtering through algorithms and user
behaviour, the vestiges of authority, authenticity and trust
established in the age of print remain. Those vestiges of
provenance have become open to appropriation by the new
digital sources of information.
One example has been the growing problem of fake
news. Designed to be disseminated via social media, fake
news is content that presents itself as traditional journalism
(either by mimicking the style and presentation of traditional
news sources or appropriating the reputation of
respected news organizations) but that presents a partial,
inaccurate and politically motivated account. It has chiefly
been associated with the right of politics. The influence of
fake news in the 2016 US presidential election and the 2016
Brexit referendum has been of widespread concern, and
many of the leading social media companies have pledged
to tackle the problem. Fake news has now also become a
political tool used to discredit reputable journalism. US
President Donald Trump and his supporters have, for example,
accused a host of mainstream news organizations of
fake news. The then education secretary Michael Gove
courted controversy when he declared in 2016 that ‘people
in this country have had enough of experts’ (Mance, 2016).
Some followers of the British Labour Party leader Jeremy
Corbyn have used the label to describe mainstream journalism
that they disagree with. Uncertainty about the veracity
of information generally is open to be used as a political
tool to discredit public scrutiny of policy, and in some sense
all claims to truth are undermined.
Fake news presents an interesting case study of the problem
of evaluation in the digital age. On the one hand, by
abandoning and pretence at impartiality, it violates the traditional
professional codes of journalistic practice. But on
the other hand, it can be seen as part of a spectrum of
content in which all ‘news’ and all information is irrevocably
partial and biased either in selection or presentation,
and reflects the political motivations of those creating, disseminating
and to a lesser degree consuming it. The existence
of this spectrum from publications of record to
Business Information Review
2017, Vol. 34(4) 172–175
ª The Author(s) 2017
Reprints and permission:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/0266382117743370
journals.sagepub.com/home/bir
outright fabrications means that naive notions of securing
both journalistic standards and evaluation of content
against undisputed facts, unbiased reportage or political
balance break down. Fake news plays to the bias of its
audience by reinforcing their existing values and beliefs
and discrediting information that might challenge those
values and beliefs, yet fake news is not always easy to
identify from its source alone. Swaine has observed that:
readers are now being confronted with an even tougher challenge:
decoding the work of writers whose track records of
faulty reporting are occasionally interrupted by stories that are
actually true. (Swaine, 2017)
The challenge of inaccurate information and misinformation
on the Internet is therefore more significant than it
appears at first glance. There is no clear-cut differentiation
between reliable and unreliable sources; no blanket tests
that we can apply; all sources of information on the web
blend truths and mistruths to varying degrees and each has
to be taken on its own merits; and all claims over the
veracity of particular sources will themselves be contested.
And this widespread assault on questions of truth and trustworthiness
in digital culture makes evaluation both more
vital and more problematic.
Truth, lies and human reasoning
There is however a more fundamental reason why analytical
approaches to evaluation sometimes fail. Humans are
spectacularly bad at reasoning. Although individuals may
vary in their ability to reason effectively, we are all similar
in our inability to recognize bias in our thought processes.
The ways in which human reasoning fails are relatively
predictable and well understood. Some of the most common
biases in our thinking habits relevant to information
evaluation are outlined below (cognitive biases have been
widely researched and written about, but a useful overview
is provided by Sutherland (1992):
Ambiguity effect: The tendency to perceive unambiguous,
clear and straightforward information as
more truthful than ambiguous information. Ambiguity
effect has an influence on how information is
reported and prepared for reporting; the tendency
within journalism, for example, to eradicate ambiguity
can distort the truthfulness of what has been
reported. Not only do we seek unambiguous
accounts but we are also likely to be misled by
accounts that falsely lack ambiguity.
Authority bias: The tendency to attribute more significance
to statements from authority figures even
in regard to areas beyond the scope of their authority.
We are drawn to trust the statements of figures or
organizations we perceive as authoritative and
subject them to less scrutiny than those of figures
whose authority we cannot judge or are in doubt
about.
Availability bias: We tend to overestimate the significance
of information that is easy to come by and
underestimate the significance of information that is
scarce. This is particularly a problem in any kind of
research process, including commercial information
research where much information that is readily
available may be untrustworthy. For example, a typical
approach to reputation management is to drown
out negative reporting with planted positive news
stories.
Bias blind spot: The tendency to believe that we are
individually better at spotting bias than other people
(including our own biases) and that other people are
less good at recognizing bias than we are. Everyone
does this, even people who know that everyone does
this.
Clustering illusion: The tendency to attribute false
significance to clusters within random distributions,
or to see patterns of cause and effect that are not
there. This is particularly a problem when there is
a limited amount of data available and exacerbated
in digital contexts where content providers sometimes
rely on republishing material from other
sources.
Cognitive dissonance effect: The tendency to reduce
inconsistency in our values and beliefs by exaggerating
our confidence in the choices we make
between equally weighted options and discounting
further information that contradicts those choices.
Or in other word, once we have decided on the truth
or otherwise of something, we look for reasons to
further justify that belief.
Confirmation bias: The tendency to attribute more
significance to information that confirms our existing
beliefs or that confirms what we would like to
believe than to information that disconfirms either of
those things.
Focusing effect: The tendency to explain all phenomena
through the lens of a particular issue or
belief with which we are preoccupied.
Illusory truth effect: The tendency to form the belief
that information or claims to which we have been
exposed repeatedly must be truthful.
The fact of these biases complicates the issue of information
evaluation in three ways. In the first place, these
kinds of cognitive biases exist within the resources that we
might be evaluating. Secondly, when evaluating information
we are in danger of being misled by our own intrinsic
capacity to look for patterns that do not exist. Finally, the
fact of cognitive biases is a resource to be exploited by
those who are seeking to manipulate the ways in which
Editorial 173
we think about the world, as in the case of reputation management
described above.
Cognitive bias is so ingrained in our habits that in some
ways it is a mistake to think of them as biases at all; they
are just the ways in which we make sense of the world
around us. Understanding why we think in these kinds of
ways may help us develop new ways of approaching
information evaluation. In a recent series of research,
Mercier and Sperber (2011, 2017) account for the welldocumented
failures of reason by framing its evolution in
response to a social context of persuasion and social trust.
Reasoning functions, they argue, not to help us ascertain
the truths of a situation per se, but to supply us with good
reasons in advocating for particular ways of seeing the
world. In this process, the truths of the matter barely play
a part. They suggest:
The main function of reasoning is argumentative: Reasoning
has evolved and persisted mainly because it makes human
communication more effective and advantageous. (2011: 60)
One consequence of this is that the kinds of cognitive
biases discussed above can be seen as not a flaw in reasoning
but as a tool in persuasion; if, as Mercier and Sperber
imply, our task is to advocate for particular ideas, then we
are better searching for good reasons than balanced arguments.
The argumentative function of reasoning distances
evaluation from notions of truth. Thus, Sperber argues bias
in reasoning evolved to improve our reasoning processes,
making us better equipped to advocate for our beliefs a
point rather than to recognize a truth.
More important perhaps is the implication of this
social persuasive function of human reasoning is that all
reasoning is necessarily situated; there is no such thing
as a neutral argument – arguments are always seeking
to persuade us of a particular state of affairs and always
relying on rhetorical tricks in maximizing that
persuasiveness. It does not matter how trustworthy or
authoritative the source, how steeped in accolades, qualifications
or expertise, they are still trying to persuade
us to particular ways of seeing the world and truth is
only one weapon in their arsenal. It follows that there is
no such thing as neutral information; all human information
exists because it was produced for a purpose, for
specific ends, and to support specific and defined world
views, and much information exists explicitly as a part
of a process of persuading us about the truth of particular
states of affairs. This is in fact rather like what we
see in digital publishing, where the structural limitations
on disseminating information of a previous age have
largely been removed.
Understanding the flaws in human reasoning makes it
clear that analytical approaches to evaluating information can
sometimes domore harmthan good. Rather than as we might
imagine eradicating bias, they may merely give the
impression of its eradication, leaving us overconfident not
only in the choices we make but also the reasons we ascribe
to those choices.That is to say that such approaches furnish us
with a series of good reasons to defend the choiceswemake in
evaluation, while doing little to guide or aid those choices.
The analytical method is, from this perspective, another
rhetorical tool in the art of persuasion, a way of securing our
opinion against some putatively objective framework.
Nevertheless, while we are in some sense hardwired to
extrapolate from incomplete or limited information, we can
also use this understanding to our advantage. At the heart of
effective information evaluation are a series of softer skills
and competencies that are impossible to delineate, but that
arise from experience, aptitude and outlook.All evaluation in
the kinds of contexts in which commercial information professionals
work is driven by context, and an important component
in that context is the subjective outlook and experience
of the individual themselves. Mercier and Sperber’s account
of the evolution of reason contains the observation that bias
has an important function in the ways in whichwe think about
the world. Our cognitive biases are not flaws in thinking, but
advantages in advocacy, in which context reason takes on a
more pragmatic function. Good reasons become the most
persuasive reasons that we can marshal in support of an argument,
rather than necessarily the most truthful.
And there are two aspects to the ways in which cognitive
bias functions that serve us well in evaluation. The first is
the well-documented fact that we are far better at spotting
the obvious bias in other people’s arguments than we are in
our own. Mercier and Sperber note:
there is an asymmetry between the production of arguments,
which involves an intrinsic bias in favor of the opinions or
decisions of the arguer whether they are sound or not, and the
evaluation of arguments, which aims at distinguishing good
arguments from bad ones and hence genuine information from
misinformation [ . . . ] people are good at assessing arguments
and are quite able to do so in an unbiased way, provided
they have no particular axe to grind. (Mercier and Sperber,
2011: 72)
The second aspect is that where reason fails us, instinct
and intuition are often more reliable than we assume them
to be. Kahneman (2012) has distinguished between two
kinds of cognitive systems involved in deliberation which
he calls system 1 and system 2. System 1 is the fast, automatic
and emotionally driven part of cognition that we
often think of as gut feeling or instinct. System 2 is the
slow and deliberative part of cognition that we often think
of as reasoning. These two parts of our thinking processes
often come to very different conclusions about the world
and are often therefore somewhat in conflict. However, the
surprising factor is that the fast, emotionally driven system
1 in many cases proves to be more reliable than the more
deliberative system 2.
174 Business Information Review 34(4)
Emerging from this are two tests that we can apply to
digital information sources (coherence and persuasiveness),
and two habits we need to relearn: trusting our professional
instincts and experience and approaching evaluation from a
disinterested position. As outlined above, precognitive
instincts tend to be more reliable than not, especially in areas
where we can profess expertise, and have no particular
vested interest. It is in searching for good reasons to justify
our existing beliefs and desires that reasoning fails us.
The evaluation of information in the digital age is deeply
rooted in matters of trust: whether we trust what we are being
told; whether we trust those who are telling us; whether we
trust themeans bywhich this information has cometo us.And
this process involves an emotional response as much as an
intellectual response. Trust arises from applying what we
already know: our professional expertise and experience –
that tacit knowledge concerningwhat makes a reliable source
that we cannot fully articulate and that when articulated is
transformed into the kinds of reductive checklists that eradicates
the value of that expertise and reduces reliability of
provenance. This can be expressed in relation to two ideas:
The internal coherence of information: whether it
agrees with itself, whether it agrees with what we
would expect of that source and whether it agrees
with everything we already know and believe about
the topic or the wider context.
The persuasiveness of information: whether it tells
an account that – regardless of any bias we might
also be aware of – is intrinsically persuasive given
what we already know.
Checklists and analytical approaches come in perhaps
after the fact when we are seeking to persuade someone
else of the professional opinion about the veracity and
trustworthiness of the information in question.
But most importantly, the very fact of the information
professional as an individual who usually sits outside of the
contexts within which information is exploited – of is in
other words usually disinterested in the information that
they are evaluating – is a critical component in effective
evaluation. There has been in recent decades a tendency to
put research tools onto the desktops of end users. But if
research and evaluation is performed from a situation in
which there is a vested interest in the outcome then the
influence of cognitive bias will tend to increase. One series
of good reasons for the involvement of information professionals
in evaluation and research derives from both their
disinterested status and professional experience of undertaking
such evaluations.
December’s Business Information Review
December’s edition of Business Information Review contains
the usual mix of academic and professional articles.
First is an article by Judi Vernau, founding director of
Metataxis Ltd which specializes in building ontologies and
taxonomies. Entitled Using Ontology to Improve Access to
Information: The New Zealand Experience, Judi’s paper
described the development of an ontology intended to support
findability within an enterprise content management
system in the New Zealand Department of Conservation. It
explores in detail both the ontology itself and also the
comparative benefits and advantages of this approach.
Next is Ali Rezaeian and Rouhollah Bagheri’s paper
which explored knowledge networks, a means by which
to with which to support knowledge sharing and creation.
Entitled Modelling the Factors Affecting the Implementation
of Knowledge Networks, the paper looks at the state of
research around knowledge networks, and draws out the
success factors in their implementation. Next is a paper
by Antonio Mun˜oz-Can˜avate entitled Competitive Intelligence
in Spain: A Study of a Sample of Firms. This paper
reports on a survey of Spanish firms to explore the ways in
which they approach the challenges of competitive intelligence
and reveals the degree to which benchmarking and
SWOT analysis still factor as significant tools in real-world
corporate settings.
Our final article comes from Cerys Hearsey as part of the
Out-of-the-Box strand of tech-related articles. In her paper,
Cerys explores the growth of artificial intelligence in theworkplace.
Also in this issue is Martin White’s Perspectives column,
which addresses the role of meetings, remote working,
information culture and collaborative information seeking.
Luke Tredinnick and Claire Laybats
References
von Baeyer HC (2003) Information: the New Language of Science.
London: Weidenfeld & Nicolson.
Conway P (1996) Preservation in the digital world. Council on
Library and Information Resources. Available at: http://www.
clir.org/pubs/reports/conway2/ (accessed 03 May 2006).
Mance H (2016) Britain has had enough of experts, says Gove,
Financial Times. Available at: https://www.ft.com/content/
3be49734-29cb-11e6-83e4-abc22d5d108c (accessed 14
November 2017).
Mercier H, Sperber D (2011) Why do humans reason? Arguments
for an argumentative theory. Behavioral and Brain Sciences
34(2): 57–74.
Mercier H, Sperber D (2017) The Enigma of Reason: A New
Theory of Human Understanding. London: Allen Lane.
KahnemanD(2012) Thinking,Fast and Slow.London: PenguinBooks.
Sutherland S (1992/2013) Irrationality: The Enemy Within. London:
Pinter & Martin.
Swaine J (2017) New fake news dilemma: sites publish real scoops
amid mess of false reports. The Guardian. Available at: https://
www.theguardian.com/media/2017/may/16/fake-news-sites-re
ports-facts-louise-mensch (accessed 18 October 2017).
Editorial 175Editorial
Evaluating digital sources: Trust,
truth and lies
How do you evaluate the contents of a wiki, blog or
discussion forum? How do you distinguish fake news from
legitimate reporting? Information professions are often
required to evaluate the veracity of sources that have relatively
poor provenance. Yet the bases on which these judgements
are made are often poorly understood. We
sometimes fall back on established checklist approaches
to explain the decisions we have already made. But new
research into the nature and flaws of human reasoning suggests
that a more organic approach to evaluating digital
information might be better. Mercier and Sperber’s The
Enigma of Reason (2017) explores the evolution of human
reasoning as part of a social process, and perhaps suggests
new ways of understanding information evaluation.
Evaluation has a long history in library and information
science; over time the methods that have been developed
have tended to rely on analytical approaches. These analytical
approaches generally involve disaggregating source
materials into a number identifiable attributes which can
be individually evaluated and compared to ascertain the
reliability of the source material itself. These attributes are
sometimes presented in the form of a checklist, and typically
focus on characteristics such as source, accuracy,
authority, balance, content and coverage, currency and so
on. Underpinning analytical approaches are a series of
indices of quality, reliability and authority. We should prefer
current information to old information, authoritative
sources to informal sources, impartial or disinterested
information to partial or interested information, attributed
information to unattributed information, superficially accurate
information to superficially inaccurate information and
so on. In many ways, these analytical categories can be
reduced to the idea of provenance: securing the source and
its trustworthiness against characteristics that we have traditionally
associated with trustworthy sources.
This approach to evaluation reflects the habits of the
printing and broadcasting tradition. In the recent past,
information was predominantly disseminated through a
limited number of media and publishing channels. The
limited bandwidth of the information infrastructure acted
to filter information prior to publishing or broadcast. As a
consequence, provenance became synonymous with quality
and reliability.
But the digital age presents specific challenges to this
approach; the proliferation of recorded information via
digital networks complicates traditional methods of
evaluation. Over the recent past, the volume of recorded
information in existence has grown exponentially (von
Baeyer, 2003; Conway, 1996). Cheap and easy to produce,
information now flows through countless shallow channels
scored into the web, social media and mobile communications.
But while digital culture has largely moved away
from pre-filtering approaches to publication turning instead
to post-publication filtering through algorithms and user
behaviour, the vestiges of authority, authenticity and trust
established in the age of print remain. Those vestiges of
provenance have become open to appropriation by the new
digital sources of information.
One example has been the growing problem of fake
news. Designed to be disseminated via social media, fake
news is content that presents itself as traditional journalism
(either by mimicking the style and presentation of traditional
news sources or appropriating the reputation of
respected news organizations) but that presents a partial,
inaccurate and politically motivated account. It has chiefly
been associated with the right of politics. The influence of
fake news in the 2016 US presidential election and the 2016
Brexit referendum has been of widespread concern, and
many of the leading social media companies have pledged
to tackle the problem. Fake news has now also become a
political tool used to discredit reputable journalism. US
President Donald Trump and his supporters have, for example,
accused a host of mainstream news organizations of
fake news. The then education secretary Michael Gove
courted controversy when he declared in 2016 that ‘people
in this country have had enough of experts’ (Mance, 2016).
Some followers of the British Labour Party leader Jeremy
Corbyn have used the label to describe mainstream journalism
that they disagree with. Uncertainty about the veracity
of information generally is open to be used as a political
tool to discredit public scrutiny of policy, and in some sense
all claims to truth are undermined.
Fake news presents an interesting case study of the problem
of evaluation in the digital age. On the one hand, by
abandoning and pretence at impartiality, it violates the traditional
professional codes of journalistic practice. But on
the other hand, it can be seen as part of a spectrum of
content in which all ‘news’ and all information is irrevocably
partial and biased either in selection or presentation,
and reflects the political motivations of those creating, disseminating
and to a lesser degree consuming it. The existence
of this spectrum from publications of record to
Business Information Review
2017, Vol. 34(4) 172–175
ª The Author(s) 2017
Reprints and permission:
sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/0266382117743370
journals.sagepub.com/home/bir
outright fabrications means that naive notions of securing
both journalistic standards and evaluation of content
against undisputed facts, unbiased reportage or political
balance break down. Fake news plays to the bias of its
audience by reinforcing their existing values and beliefs
and discrediting information that might challenge those
values and beliefs, yet fake news is not always easy to
identify from its source alone. Swaine has observed that:
readers are now being confronted with an even tougher challenge:
decoding the work of writers whose track records of
faulty reporting are occasionally interrupted by stories that are
actually true. (Swaine, 2017)
The challenge of inaccurate information and misinformation
on the Internet is therefore more significant than it
appears at first glance. There is no clear-cut differentiation
between reliable and unreliable sources; no blanket tests
that we can apply; all sources of information on the web
blend truths and mistruths to varying degrees and each has
to be taken on its own merits; and all claims over the
veracity of particular sources will themselves be contested.
And this widespread assault on questions of truth and trustworthiness
in digital culture makes evaluation both more
vital and more problematic.
Truth, lies and human reasoning
There is however a more fundamental reason why analytical
approaches to evaluation sometimes fail. Humans are
spectacularly bad at reasoning. Although individuals may
vary in their ability to reason effectively, we are all similar
in our inability to recognize bias in our thought processes.
The ways in which human reasoning fails are relatively
predictable and well understood. Some of the most common
biases in our thinking habits relevant to information
evaluation are outlined below (cognitive biases have been
widely researched and written about, but a useful overview
is provided by Sutherland (1992):
Ambiguity effect: The tendency to perceive unambiguous,
clear and straightforward information as
more truthful than ambiguous information. Ambiguity
effect has an influence on how information is
reported and prepared for reporting; the tendency
within journalism, for example, to eradicate ambiguity
can distort the truthfulness of what has been
reported. Not only do we seek unambiguous
accounts but we are also likely to be misled by
accounts that falsely lack ambiguity.
Authority bias: The tendency to attribute more significance
to statements from authority figures even
in regard to areas beyond the scope of their authority.
We are drawn to trust the statements of figures or
organizations we perceive as authoritative and
subject them to less scrutiny than those of figures
whose authority we cannot judge or are in doubt
about.
Availability bias: We tend to overestimate the significance
of information that is easy to come by and
underestimate the significance of information that is
scarce. This is particularly a problem in any kind of
research process, including commercial information
research where much information that is readily
available may be untrustworthy. For example, a typical
approach to reputation management is to drown
out negative reporting with planted positive news
stories.
Bias blind spot: The tendency to believe that we are
individually better at spotting bias than other people
(including our own biases) and that other people are
less good at recognizing bias than we are. Everyone
does this, even people who know that everyone does
this.
Clustering illusion: The tendency to attribute false
significance to clusters within random distributions,
or to see patterns of cause and effect that are not
there. This is particularly a problem when there is
a limited amount of data available and exacerbated
in digital contexts where content providers sometimes
rely on republishing material from other
sources.
Cognitive dissonance effect: The tendency to reduce
inconsistency in our values and beliefs by exaggerating
our confidence in the choices we make
between equally weighted options and discounting
further information that contradicts those choices.
Or in other word, once we have decided on the truth
or otherwise of something, we look for reasons to
further justify that belief.
Confirmation bias: The tendency to attribute more
significance to information that confirms our existing
beliefs or that confirms what we would like to
believe than to information that disconfirms either of
those things.
Focusing effect: The tendency to explain all phenomena
through the lens of a particular issue or
belief with which we are preoccupied.
Illusory truth effect: The tendency to form the belief
that information or claims to which we have been
exposed repeatedly must be truthful.
The fact of these biases complicates the issue of information
evaluation in three ways. In the first place, these
kinds of cognitive biases exist within the resources that we
might be evaluating. Secondly, when evaluating information
we are in danger of being misled by our own intrinsic
capacity to look for patterns that do not exist. Finally, the
fact of cognitive biases is a resource to be exploited by
those who are seeking to manipulate the ways in which
Editorial 173
we think about the world, as in the case of reputation management
described above.
Cognitive bias is so ingrained in our habits that in some
ways it is a mistake to think of them as biases at all; they
are just the ways in which we make sense of the world
around us. Understanding why we think in these kinds of
ways may help us develop new ways of approaching
information evaluation. In a recent series of research,
Mercier and Sperber (2011, 2017) account for the welldocumented
failures of reason by framing its evolution in
response to a social context of persuasion and social trust.
Reasoning functions, they argue, not to help us ascertain
the truths of a situation per se, but to supply us with good
reasons in advocating for particular ways of seeing the
world. In this process, the truths of the matter barely play
a part. They suggest:
The main function of reasoning is argumentative: Reasoning
has evolved and persisted mainly because it makes human
communication more effective and advantageous. (2011: 60)
One consequence of this is that the kinds of cognitive
biases discussed above can be seen as not a flaw in reasoning
but as a tool in persuasion; if, as Mercier and Sperber
imply, our task is to advocate for particular ideas, then we
are better searching for good reasons than balanced arguments.
The argumentative function of reasoning distances
evaluation from notions of truth. Thus, Sperber argues bias
in reasoning evolved to improve our reasoning processes,
making us better equipped to advocate for our beliefs a
point rather than to recognize a truth.
More important perhaps is the implication of this
social persuasive function of human reasoning is that all
reasoning is necessarily situated; there is no such thing
as a neutral argument – arguments are always seeking
to persuade us of a particular state of affairs and always
relying on rhetorical tricks in maximizing that
persuasiveness. It does not matter how trustworthy or
authoritative the source, how steeped in accolades, qualifications
or expertise, they are still trying to persuade
us to particular ways of seeing the world and truth is
only one weapon in their arsenal. It follows that there is
no such thing as neutral information; all human information
exists because it was produced for a purpose, for
specific ends, and to support specific and defined world
views, and much information exists explicitly as a part
of a process of persuading us about the truth of particular
states of affairs. This is in fact rather like what we
see in digital publishing, where the structural limitations
on disseminating information of a previous age have
largely been removed.
Understanding the flaws in human reasoning makes it
clear that analytical approaches to evaluating information can
sometimes domore harmthan good. Rather than as we might
imagine eradicating bias, they may merely give the
impression of its eradication, leaving us overconfident not
only in the choices we make but also the reasons we ascribe
to those choices.That is to say that such approaches furnish us
with a series of good reasons to defend the choiceswemake in
evaluation, while doing little to guide or aid those choices.
The analytical method is, from this perspective, another
rhetorical tool in the art of persuasion, a way of securing our
opinion against some putatively objective framework.
Nevertheless, while we are in some sense hardwired to
extrapolate from incomplete or limited information, we can
also use this understanding to our advantage. At the heart of
effective information evaluation are a series of softer skills
and competencies that are impossible to delineate, but that
arise from experience, aptitude and outlook.All evaluation in
the kinds of contexts in which commercial information professionals
work is driven by context, and an important component
in that context is the subjective outlook and experience
of the individual themselves. Mercier and Sperber’s account
of the evolution of reason contains the observation that bias
has an important function in the ways in whichwe think about
the world. Our cognitive biases are not flaws in thinking, but
advantages in advocacy, in which context reason takes on a
more pragmatic function. Good reasons become the most
persuasive reasons that we can marshal in support of an argument,
rather than necessarily the most truthful.
And there are two aspects to the ways in which cognitive
bias functions that serve us well in evaluation. The first is
the well-documented fact that we are far better at spotting
the obvious bias in other people’s arguments than we are in
our own. Mercier and Sperber note:
there is an asymmetry between the production of arguments,
which involves an intrinsic bias in favor of the opinions or
decisions of the arguer whether they are sound or not, and the
evaluation of arguments, which aims at distinguishing good
arguments from bad ones and hence genuine information from
misinformation [ . . . ] people are good at assessing arguments
and are quite able to do so in an unbiased way, provided
they have no particular axe to grind. (Mercier and Sperber,
2011: 72)
The second aspect is that where reason fails us, instinct
and intuition are often more reliable than we assume them
to be. Kahneman (2012) has distinguished between two
kinds of cognitive systems involved in deliberation which
he calls system 1 and system 2. System 1 is the fast, automatic
and emotionally driven part of cognition that we
often think of as gut feeling or instinct. System 2 is the
slow and deliberative part of cognition that we often think
of as reasoning. These two parts of our thinking processes
often come to very different conclusions about the world
and are often therefore somewhat in conflict. However, the
surprising factor is that the fast, emotionally driven system
1 in many cases proves to be more reliable than the more
deliberative system 2.
174 Business Information Review 34(4)
Emerging from this are two tests that we can apply to
digital information sources (coherence and persuasiveness),
and two habits we need to relearn: trusting our professional
instincts and experience and approaching evaluation from a
disinterested position. As outlined above, precognitive
instincts tend to be more reliable than not, especially in areas
where we can profess expertise, and have no particular
vested interest. It is in searching for good reasons to justify
our existing beliefs and desires that reasoning fails us.
The evaluation of information in the digital age is deeply
rooted in matters of trust: whether we trust what we are being
told; whether we trust those who are telling us; whether we
trust themeans bywhich this information has cometo us.And
this process involves an emotional response as much as an
intellectual response. Trust arises from applying what we
already know: our professional expertise and experience –
that tacit knowledge concerningwhat makes a reliable source
that we cannot fully articulate and that when articulated is
transformed into the kinds of reductive checklists that eradicates
the value of that expertise and reduces reliability of
provenance. This can be expressed in relation to two ideas:
The internal coherence of information: whether it
agrees with itself, whether it agrees with what we
would expect of that source and whether it agrees
with everything we already know and believe about
the topic or the wider context.
The persuasiveness of information: whether it tells
an account that – regardless of any bias we might
also be aware of – is intrinsically persuasive given
what we already know.
Checklists and analytical approaches come in perhaps
after the fact when we are seeking to persuade someone
else of the professional opinion about the veracity and
trustworthiness of the information in question.
But most importantly, the very fact of the information
professional as an individual who usually sits outside of the
contexts within which information is exploited – of is in
other words usually disinterested in the information that
they are evaluating – is a critical component in effective
evaluation. There has been in recent decades a tendency to
put research tools onto the desktops of end users. But if
research and evaluation is performed from a situation in
which there is a vested interest in the outcome then the
influence of cognitive bias will tend to increase. One series
of good reasons for the involvement of information professionals
in evaluation and research derives from both their
disinterested status and professional experience of undertaking
such evaluations.
December’s Business Information Review
December’s edition of Business Information Review contains
the usual mix of academic and professional articles.
First is an article by Judi Vernau, founding director of
Metataxis Ltd which specializes in building ontologies and
taxonomies. Entitled Using Ontology to Improve Access to
Information: The New Zealand Experience, Judi’s paper
described the development of an ontology intended to support
findability within an enterprise content management
system in the New Zealand Department of Conservation. It
explores in detail both the ontology itself and also the
comparative benefits and advantages of this approach.
Next is Ali Rezaeian and Rouhollah Bagheri’s paper
which explored knowledge networks, a means by which
to with which to support knowledge sharing and creation.
Entitled Modelling the Factors Affecting the Implementation
of Knowledge Networks, the paper looks at the state of
research around knowledge networks, and draws out the
success factors in their implementation. Next is a paper
by Antonio Mun˜oz-Can˜avate entitled Competitive Intelligence
in Spain: A Study of a Sample of Firms. This paper
reports on a survey of Spanish firms to explore the ways in
which they approach the challenges of competitive intelligence
and reveals the degree to which benchmarking and
SWOT analysis still factor as significant tools in real-world
corporate settings.
Our final article comes from Cerys Hearsey as part of the
Out-of-the-Box strand of tech-related articles. In her paper,
Cerys explores the growth of artificial intelligence in theworkplace.
Also in this issue is Martin White’s Perspectives column,
which addresses the role of meetings, remote working,
information culture and collaborative information seeking.
Luke Tredinnick and Claire Laybats
References
von Baeyer HC (2003) Information: the New Language of Science.
London: Weidenfeld & Nicolson.
Conway P (1996) Preservation in the digital world. Council on
Library and Information Resources. Available at: http://www.
clir.org/pubs/reports/conway2/ (accessed 03 May 2006).
Mance H (2016) Britain has had enough of experts, says Gove,
Financial Times. Available at: https://www.ft.com/content/
3be49734-29cb-11e6-83e4-abc22d5d108c (accessed 14
November 2017).
Mercier H, Sperber D (2011) Why do humans reason? Arguments
for an argumentative theory. Behavioral and Brain Sciences
34(2): 57–74.
Mercier H, Sperber D (2017) The Enigma of Reason: A New
Theory of Human Understanding. London: Allen Lane.
KahnemanD(2012) Thinking,Fast and Slow.London: PenguinBooks.
Sutherland S (1992/2013) Irrationality: The Enemy Within. London:
Pinter & Martin.
Swaine J (2017) New fake news dilemma: sites publish real scoops
amid mess of false reports. The Guardian. Available at: https://
www.theguardian.com/media/2017/may/16/fake-news-sites-re
ports-facts-louise-mensch (accessed 18 October 2017).
Editorial 175

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