Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side Stephen Marsh1 and Mark R. Dibben2 1
National Research Council Canada, Institute for Information Technology
[email protected] 2 Lincoln University, New Zealand
[email protected]
Abstract. There has been a lot of research and development in the field of computational trust in the past decade. Much of it has acknowledged or claimed that trust is a good thing. We think it’s time to look at the other side of the coin and ask the questions why is it good, what alternatives are there, where do they fit, and is our assumption always correct? We examine the need for an addressing of the concepts of Trust, Mistrust, and Distrust, how they interlink and how they affect what goes on around us and within the systems we create. Finally, we introduce the phenomenon of ‘Untrust,’ which resides in the space between trusting and distrusting. We argue that the time is right, given the maturity and breadth of the field of research in trust, to consider how untrust, distrust and mistrust work, why they can be useful in and of themselves, and where they can shine.
1
Introduction
Computers, and the world they touch, are interesting. For example, issues of IT security mean that, to coin a phrase, everyone is distrusted equally, but some are distrusted more equally than others1 , while ‘trusted computing’ would have us believe that we are capable of trusting our computers and our networks, as it were, with just a little more effort in the design and implementation process. ECommerce vendors compete for the trust of consumers, tweaking websites, designing online experiences and generally falling over themselves in their eagerness to put right what has been pointed out as wrong (a major research area in its own right, that of trust in online experiences, see for example [1, 2, 3, 4, 5, 6]), which is odd considering that distrust is an important motive force in such transactions as result [7]. A great deal of excellent research has gone into computational trust, trust management, online trust, and so on in the past decade or so, and now, we find ourselves at a crossroads. 1
As an aside, we believe that the use of the term ‘trust’ in IT security requires much more careful thought, but that’s a story, and a recurrent argument, for another time.
P. Herrmann et al. (Eds.): iTrust 2005, LNCS 3477, pp. 17–33, 2005. c Springer-Verlag Berlin Heidelberg 2005
18
S. Marsh and M.R. Dibben
There is, in the literature and the world, an overwhelming consideration that trust is a fundamentally positive force that, when applied in many different areas, from society to computation, will bear positive fruit. As trust researchers, we tend to agree, but there’s a caveat – Trust has a ‘darker’ side, Distrust, and this is almost uniformly ignored, or glossed over as something to be addressed at another time. Invariably, distrust causes problems with computational formulae – what exactly is it, how does it get represented and, when it is represented, what does it really mean? Just as invariably, we promise we’ll think about it another time and head off with a greater understanding of trust and none of distrust. The time is right to examine the darker side of trust. Distrust is not a simple reversal of the concept, although it is tightly coupled [8]. It’s also not Mistrust or Untrust, although again it’s related. To our knowledge, the question of how it’s related, where, and to what extent it comes into play, and how one can become another, has not been adequately addressed in the computational sciences literature ([7, 9, 10] notwithstanding). For the sake of a complete understanding, it’s time this was done. Finally, it’s also time to discuss what the space between trusting and distrusting is, and how it works. This paper serves as a next step in that process, as a call to arms to the Trust researchers and developers to turn their thoughts to Untrust, Distrust and Mistrust, to consider them as unique entities in their own right, and to develop systems and architectures that utilise their strengths in a concrete manner that acknowledges where one ends and another begins. The organisation of this paper is as follows. Firstly, we believe that it is necessary to understand our terms of reference before we proceed. Accordingly, section 2 presents and discusses definitions of trust, untrust, distrust, and mistrust, and by doing so creates a concrete foundation from which to move into our explorations. To discuss the concepts further, in section 3 we expand the formalisation in [11] to include explicit consideration of distrust and mistrust, and to make it more applicable to computational trust as it now stands. Section 4 discusses why the phenomena of untrust, distrust and mistrust are important, where they can be used and why, and how they contribute to trust research and the ultimate conception of trust as a positive thing.Finally, we apply the new formalisation and end with a call to arms for understanding and further work in this area in section 5.
2
Definitional Issues and Discussions
A short review of trust literature in the social sciences reveals an increasing interest in distrust. What was once regularly considered as a side-effect of trust violation [12, 13], rather than necessarily a construct of its own, has now assumed more significance. Most understandings of distrust appear to take their cue from Luhmann’s [14] suggestion that those who choose not to trust “must adopt another negative strategy to reduce complexity” [15–page 24] and that Golembiewski and McConkie’s ‘self-heightening cycle of trust’ [16] applies in the opposite way to its supposed corollary [17–page 38]. The significance of distrust as a separate concept is brought into stark relief when coupled with ideas
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
19
from risk management and social, or public, trust – and this is an area we will develop later. Suffice to say that from the perspective of risk communication, public distrust is a ‘cultural tendency’ [18–page 60], ameliorated by better information [19] which recognises that “lay-people’s conceptions of risk reflect a richer and broader rationality” [20–page 130]. That is to say, distrust is a human response to a lack of information. Thus, distrust is often considered as the “negative mirror-image of trust” [21–page 26], a “confident negative expectation regarding anothers conduct” [22–page 439] in a situation entailing risk to the trusting party. Mistrust, for its part, can be considered as “either a former trust destroyed, or former trust healed” [21–page 27]. While we’ve mentioned (and criticised) before [23] that it seems that every paper in computational trust at least seems to have its own need for a definition of trust, that’s certainly true here. Not only that, but we also need definitions for distrust untrust, and mistrust. Importantly, we argue that in fact they are not the same. In many ways, this paper represents an evolution from [11], where we discussed distrust and ignorance. There, we stated that distrust was negative of trust. Here, we’re evolving that definition because of the work that has been done in the area, and a greater understanding of the concept because of this work. That given, it’s still surprisingly difficult to find definitions of distrust that don’t use mistrust as synonymous (even the otherwise excellent [9] confuses the two). In fact, we believe this is a mistake because it removes a tool for trust researchers to be able to focus on what they are researching. We use a corollary with information as a pointer to the direction we will take. From the Oxford English Dictionary, we find that the term ‘misinformation’ can be taken to mean information that is incorrect. This can be a mistake on the part of the informer, and generally speaking, it can be spotted after the fact. The term ’disinformation’ removes all doubt – it’s information that is deliberately false and intended to deceive. That is, disinformation is misinformation that is deliberately and knowingly planted. From this, we can move to a better understanding of distrust and mistrust, and what untrust is. A simple comparison between the concepts is probably necessary. For the sake of argument, following [24, 25, 26, 27, 14, 11], let’s say that trust, in general, is taken as the belief (or a measure of it) that a person (the trustee) will act in the best interests of another (the truster) in a given situation, even when controls are unavailable and it may not be in the trustee’s best interests to do so. Given this, we can now examine untrust, distrust and mistrust in the following ways. Given that Misinformation is passive in some form (that is, it may or may not be intentional, and is a judgment usually attained after the fact), we conjecture that Mistrust is misplaced trust. That is, in a situation where there was a positive estimation of the trustee and trust was betrayed, we can say that trust has been misplaced (not always ‘betrayed,’ since the trustee may not have had bad intentions). Thus, the truster mistrusted the trustee. Thus, as we see in [28] mistrust is defined so “When a trustee betrays the trust of the truster, or,
20
S. Marsh and M.R. Dibben
in other words, defaults on trust, we will say that a situation of mistrust has occured, or that the truster has mistrusted the trustee in that situation.” (p.47). Somewhere between distrust and trust there is a potentially large gap. In this gap exists ‘Untrust’. Untrust is a measure of how little the trustee is actually trusted. That is to say that if we say a trustee is untrusted, then the truster has little confidence (belief, faith) in the trustee acting in their best interests in that particular situation. This is not quite the same as being the opposite of trust. In [11] the concept of untrust, while not explicitly acknowledged as such at the time, is covered in the situation of Situational Trust being less than Cooperation Threshold – I trust you, but not enough to believe you’ll be of any help in this situation if push comes to shove. Thus, untrust is positive trust, but not enough to cooperate. In this instance, as has been noted elsewhere [9], it is possible to put into place measures that can help increase trust, or at least remove the need to rely on the trustee. These can include legal necessities such as contracts, or verification techniques, for example observation until the truster is satisfied, and so on: “Trust, but verify,” as Reagan said. Distrust, by comparison is a measure of how much the truster (we obviously use the term loosely here!) believes that the trustee will actively work against them in a given situation. Thus, if I distrust you, I expect you’ll work to make sure the worst (or at least not the best) will happen in a given situation. Interestingly, while trust (and mistrust and untrust) are situational, it’s hard to imagine many examples where a distrusted person can be trusted by the same truster in a different situation, but there may well be some. Again, [28] defines distrust as “to take an action as if the other agent is not trusted, with respect to a certain situation or context. To distrust is different from now having any opinion on whether to trust or not to trust . . . Although distrust is a negative form of trust, it is not the negation of trust” (p.47, my emphasis). As will be seen in section 3, it is possible to represent distrust as negative trust, which is not the same as the negation of trust. For further clarification, consider the statements ‘I mistrusted the information John just gave me,’ ’I don’t trust the information Bill just handed me’ and ’I distrust what Paula just told me’ – in the first, the information was trusted but revealed to be incorrect, in the second, it may or may not be correct, but what we’re saying is that we’d need more assurance before trusting it. In the third case, we are actively sure that the information is incorrect; moreover, that Paula intended it to be incorrect. Mis- versus dis-information relates here to misversus dis-trust. Luhmann [14] states that distrust is functionally equivalent to trust. That is, it is possible to imagine distrust working in a complex situation to the detriment of the (dis)truster. Distrust results in the need for evidence, verification, and so on, and thus increases the complexity of a situation (where, as Luhmann claims, trust reduces that complexity). While Untrust is passive in the sense that it allows the truster to know that a trustee may be trustworthy in a situation, but isn’t for this truster, Distrust is active, and allows the (dis)truster to know that
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
21
Fig. 1. The Continuum: From Distrust to Trust
a trustee is not to be trusted in this situation. Untrust is a measure of how much a person is trusted (and is a positive measure), Distrust is a negative measure. Figure 1 illustrates how untrust, mistrust and trust conceptually relate. With some thought, it can be seen that there are still avenues in need of work (what is a trust value of zero anyway?). However, the diagram serves to illustrate where our definitions of Untrust, Distrust and Trust lie. Mistrust doesn’t fit on this diagram because it’s a misplaced value that was positive and misplaced. As such, it would usually be in the trust section of the graph before cooperation. Distrust, and untrust, are important not because of what they potentially stop, but because of what they can allow to continue. Thus, while I may mistrust or distrust you, this gives me a measure of what it is necessary for me to do or for you to undertake before I can be comfortable relying on you. This can include recourse to legal niceties, but can also include guarantees or other personal activities. Mistrust is important because of what it tells a truster after everything goes horribly wrong. There is evidence to suggest that distrust, untrust2 and mistrust are at least as important as trust, for example in E-Commerce [7], in government and organizations [29, 30], and in life [14, 8]. In fact, we conjecture, given the recent drops in trust in government, for example in the US [29], that distrust has become a more prevalent way to manage relationships that are at arms length than trust. That is to say, trust is the grease in the wheels of personal, private relationships, while distrust is the means by which every other relationship is measured and controlled. While this may seem to be something of a dark conjecture, it holds a certain amount of promise. Distrust (and its cousins) really can be important in high risk situations [7], limiting exposure, being more risk averse, and exposing more gradually in risky situations than trust would result in. Since the spiral of trust can hopefully lead to more exposure and more trust as trustworthy behaviour is exhibited [11, 16], it is reasonable to assume that untrust, placed 2
Although no-one calls it that, in fact, no-one calls it anything.
22
S. Marsh and M.R. Dibben
correctly, can lead to trust. There exist more problems with distrust, of course, that we will address below.
3
Introductory Formalisations
Several formalisations of trust (and distrust) exist. Rahman’s thesis documents them particularly well [28], and in fact his own formalisation is one of the more flexible ones. However, we’re less interested in how such models work with trust, but how it is possible to represent distrust, and/or untrust. Bearing in mind that distinct trust levels are ambiguous at best (at least in terms of semantics and subjectivity [28–p.124]), we’ll use them anyway. We believe benefits far outweigh their disadvantages, and include the ability to narrow down and discuss subconcepts (as is shown below), (computational) tractability and the ability to discuss and compare to some extent, and given a limited amount of space here, we’ll argue the point at length elsewhere. From [11] we use the notation shown in table 1. For more information discussions on the use of values and their ultimate frailties, see [11, 31, 32], amongst others. The formalisations in [11] attempted to answer questions about trust in cooperative situations. That is, given the choice between cooperation and noncooperation, whether to cooperate with a specific trustee or not. Two formulae are used, the first being to estimate Situational Trust. To estimate situational trust, x uses: (1) Tx (y, α) = Ux (α) × Ix (α) × T x (y) The second formulae considers a Cooperation Threshold: Cooperation Thresholdx (α) =
Perceived Riskx (α) Perceived Competencex (y, α) + T x (y)
× Ix (α)
Table 1. Summary of notation (‘Actors’ are truster, trustee and others) Description Situations Actors Set of Actors Societies of Actors
Representation Value Range α, β, . . . a, b, c, . . . A S1 , S 2 . . . Sn ∈ A Knowledge (e.g., x knows y) Kx (y) True/False Importance (e.g., of α to x) Ix (α) [0, +1] Utility (e.g., of α to x) Ux (α) [−1, +1] Basic Trust (e.g., of x) Tx [−1, +1) General Trust (e.g., of x in y) Tx (y) [−1, +1) Situational Trust (e.g., of x in y for α) Tx (y, α) [−1, +1)
(2)
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
23
Finally we state that, Tx (y, α) ≥ Cooperation Thresholdx (α) ⇒ Will Cooperate(x, y, α) The specifics of the formulae are not overly relevant here. What we are considering is a situation where, given some information, knowledge, and experience, x has to decide whether to cooperate or not with y. While a simplification, we have always seen this as a decision founded on trust. The next question that naturally arises is ‘what if the thresholds are too high?’ That is, what if x doesn’t trust y enough in a situation, or what if the resultant values are negative. These are, respectively, situations of untrust and distrust. 3.1
Modeling Untrust
For a situation of mistrust, the following must be true: Tx (y, α) > 0 & Tx (y, α) < Cooperation Thresholdx (α) ⇒ Untrust(x, y, α) (3) That is, if Tx (y, α) is less than the Cooperation Threshold but larger than 0, x is in a state of untrust in y. That is, x ‘doesn’t trust’ y. Generally speaking, that means x will not enter into cooperation with y in this situation. In fact, this is somewhat simplistic because of course there may be little choice but for x to rely on y in α (note that it is possible to rely on someone without trusting them [28]). As has been noted above, this puts x into an interesting situation. She knows that y is not trusted enough to cooperate with (but note that y is trusted to some extent) but there’s not much of a choice about who else to work with. As will be seen, there are answers to this dilemma. 3.2
Modeling Distrust
Distrust, as discussed above, is an active judgment in the negative intentions of the other. That is to say: Tx (y, α) < 0 ⇒ Distrust(x, y, α)
(4)
Because of the way the formulae work, this can occur in situations where there is a negative importance or utility for α. This is a potential shortcoming of the formalisation that has already been pointed out (see [11] for indepth discussions), but is easily checked in computational trust. However, while outside the scope of this article, it is worth thinking about what negative importance or negative utility might actually mean. Whatever the case, a negative situational trust value can be taken to mean that the truster expects the trustee to behave contrary to their best interests in the situation. Clearly, the truster should not then enter into the situation. Again, questions arise as to what happens if there is no choice. Of course, we argue that distrust in this circumstance gives one a choice – it may be better not to enter in and face the consequences than to jump into the situation with the trustee, and distrust can give a measure of whether or not the consequences
24
S. Marsh and M.R. Dibben
of not entering into the situation are worse than those of entering into it and a (subjectively estimated) subsequent betrayal. Ultimately, this can be a question of risk, consequences, utility and so on. Consider an example. A security program controls access to data warehouse that is queried by an autonomous agent searching for information. To attain access to the information, the agent must be given some security clearance. Calculations suggest a distrust (negative trust) in the agent, but if the program does not grant access, there may be legal costs involved, or the reputation of the data warehouse could be adversely affected, so what to do? The program could grant access, knowing that the other will steal or perhaps alter valuable information, or it could deny access, with the resultant negative effects. Importantly, knowing that there may be a violation of trust means the security program can create defences (backing up data more frequently, for example). The resultant damage to the reputation of the repository could well be more damaging than the cost of making ready for violations of trust. As another example, consider my need to fly to Europe to give a talk. In an examination of sub-goals, I can calculate that I do not trust (in fact, this could be distrust or untrust, depending somewhat on my notions of a global baggage handler conspiracy!) the baggage handlers to get my luggage to me correctly (perhaps something can be damaged or stolen, or simply routed wrongly). The costs are potentially minimal, but could include the loss of all my clothes for the week I am in Europe. The cost of not going is loss of reputation when I cancel last minute, subsequent shame, and so on. Despite the fact I mistrust baggage handlers, I consider that the cost of losing reputation is higher than that of a t-shirt and a pair of socks. I board the plane with a change of underwear in my carry on bag. . . 3.3
Dealing with Lack of Trust: Making x Comfortable
One of the most important aspects of trust is that it enables a decision maker to act in situations of doubt, distrust, or untrust [33]. In equation 3, x is in a state of mistrust in y for situation α. As we’ve noted, there is still the possibility of x having no choice but to rely on y, or perhaps of yy, despite a low trust value, being the most trusted of several alternatives3 . This, or other similar situations where x is constrained, being the case, it falls to x and y to negotiate a way in which x can become comfortable enough to enter into α with y. Because of the way in which the formulae above work, we can examine some options4 : – – – – 3 4
Reduce the Perceived Risk inherent in α Reduce the Importance of α Increase the Perceived Competence of y Reduce the potential Utility of α for x
Note here that the main strength of using values, whether subjective or not, is this inherent ability to perform such rankings internally to the actor. Given other formalisations, this list would alter. What is important to us is that a list is available for the actors to work through.
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
25
Examining these, we can come up with solutions for the dilemma x finds herself in. We consider some (a non-exhaustive list) now. To reduce risk, x xan get some assurances from y that y will behave carefully, or be bound in some way. To increase the perceived competence, y could present credentials or examples of previous experience. Reducing the importance of a situation, and the utility of a situation, are more interesting. In both cases, it would seem that such actions require that α in fact become a completely different situation (let’s call it β). It could also, for example, involve splitting α into two or more other situations, each of which lead toward the goal of α but each of which has less importance than α. This is of course a goal-directed approach. What if α is not workable in this way? Then, other considerations must be made. Conceptually, it’s easy to understand this dilemma. In practice, it’s often difficult for an actor to work through solutions. The use of the formalisation allows an actor to at least see the considerations. From there, they can make alternative plans. 3.4
When It All Goes Horribly Wrong: Mistrust
As discussed above, Mistrust is misplaced trust, that is trust that was placed and was subsequently betrayed in some way. In [11, 34], we briefly examined how betrayal of trust affects the general trust of the trustee by the truster, and determined that the disposition of the truster had an effect on both general trust and subsequent adjustments of how much the trustee is trusted from them on. Put simply, there is an adjustment to make to trust in the trustee following the conclusion of a situation. For time t: Tx (y)t+1 = Tx (y)t + ∆(Tx (y))
(5)
What the ∆ is here is what is of interest. Much work remains to be done in this area, but briefly consider two circumstances and how this can affect trust subsequently. In the first instance, the trustee betrayed the trust of the truster but did not intend to (this can be as a result of lack of competence, circumstances outside the control of the trustee, and so forth). In other words, they should have been untrusted. In this circumstance, the ∆ can be a small percentage of original Tx (y)t . However, if it turns out that the trustee was disposed to betray the truster before the situation took place, in other words should have been distrusted, then the ∆ would be a great deal larger. This is in keeping with the behaviour of trust that has been observed across various disciplines (see e.g. [24, 35, 14, 36]).
4
Related Work, Discussions and Pointers
Thus far we have raised the issue of distrust (i.e. a ‘confident negative expectation. . . ’ as opposed to trust’s ‘confident positive expectation. . . ’) and untrust (i.e. insufficient trust of the other party in the particular situation under consideration) as concepts certainly not as well recognised in computer science as in
26
S. Marsh and M.R. Dibben
social science. Recognising the need to develop information systems modelling that more accurately reflects the behaviour of human agents, we have then put together a formalisation of the impact of distrust and untrust on the co-operative behaviour of autonomous agents. This, however, is only a first step. Our purpose in the remainder of the paper is to move the discussion forward by considering what implications recent advances in the understanding of trust, confidence and distrust in specific branches of the social sciences (most notably public policy, health care and management studies) may have for ‘information systems trust management’ (iTrust). We do this by briefly (1) critically comparing the formalism with Lewicki et als formal distinctions between trust and distrust [22]; and (2) exploring the almost taken-for-granted association between confidence and trust arising out of the adoption of Luhmanns [8] connection between the two concepts (that Lewicki et al also adopt), in the light of what has been termed the problem of ‘public sector accountability’ through clinical governance and performance indicators (e.g. [37, 38]). Such discussions lend themselves to areas for further research. 4.1
Questioning the Bi-polar Construct Principle
The formalism we have developed thus far is characterised by an understanding that trust relationships are both situation specific (i.e. they are mutlifaceted) and that they are processual (i.e. ever-changing; [39]). This is in contrast to more normative views arising largely out of traditional sociologies of exchange (e.g. [40, 41]) that see trust relationships as rather more homeostatic and consistent states [42, 43]. However, the formalism does entertain an assumption that trust and distrust can be described as one bi-polar construct. This assumption has its basis in early psychological research that viewed them as being at opposite ends of a single continuum [44]). This has a natural implication for co-operation in terms of no co-operation arising from distrust and co-operation arising from trust (e.g. [45, 46, 47]). While we have already said here and elsewhere [11, 48, 49] that such a stark distinction is perhaps misleading and that no co-operation might be more indicative of insufficient trust (‘untrust’) rather than any active distrust, the inherent bi-polar construct principle has been brought into question by [22]. Basing their thinking on Luhmanns [14] argument that both trust and distrust simplify the social world by allowing actors to (differently) manage social uncertainty (the principle of functional equivalency), Lewicki et al suggest that in fact trust and distrust are entirely separate dimensions. This is because “low distrust is not the same as high trust, and high distrust is not the same as low trust” [22–page 445]. They argue that it is perfectly possible to have conditions of a) simultaneous low trust and low distrust, b) simultaneous high trust and low distrust, c) simultaneous low trust and high distrust and d) simultaneous high trust and high distrust. This rendering can be seen as a description of the history of the relationship between two actors, as perceived from one actors perspective. For example, low trust, low distrust is characteristic of a relationship where there are no grounds for either high trust or high distrust in a situation, most common in newly established relationships. We wonder whether this may be an
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
27
extension of the notion of blind trust, or even Meyerson et al’s swift trust [50]. High trust, low distrust is characteristic of a relationship in which the actor has a situational trust that has been rewarded with positive experiences and few, if any, instances of trust violation. Low trust, high distrust is perhaps the most difficult relationship to manage, according to Lewicki et al, since “they must find some way to manage their distrust” [22–page 447]. Most often, this is achievable by the establishment of clearly identified and defined parameters within which the relationship proceeds, and through which “constrained trust relations that permit functional interaction within the constraints” (ibid.) can emerge and be fruitful. High trust, high distrust relations are characterised by actors having some conflicting and some shared objectives. This leads to many positive experiences and many negative experiences, reinforcing both trust and distrust. In these circumstances, the relationship can be managed by limiting the actors dependence to those situations that reinforce the trust and strongly constrain those situations that engender distrust, to the extent that the outcome can be contained, if not entirely predicted. The importance of such a rendering of trust and distrust as co-existing to our understanding of artificial intelligence agents and their operation in (for example) search engines, may lie in the practical importance of building and maintaining trust relationships with sources of information while at the same time treating with suspicion much of the information received from those sources. Lewicki et al argue that dysfunction in relationships arises not from distrust, but rather from trust without distrust and from distrust without trust. They argue that it is the “dynamic tension” between trust and distrust that allows relationships between actors to be productive, in the best interests of both confiding parties and as a source of long-lasting stability for relationships [22–page 450]. This dynamic tension is certainly evident in studies of doctor patient relations (e.g. [39], where the blind faith in a doctors ability to cure illness is replaced – often after considerable trust violation – with what has been termed a relationship of ‘guarded alliance’ [51, 52]. This is one in which the patient recognises the limitations of the doctor and works within them to manage their illness while seeking (or not) a cure. We wonder: – Whether and how it would be possible to model such trust and distrust relations in more formal (computational) terms; – What impact this may have on the behaviour of such agents; and – Whether such behaviour would be productive from a user perspective – even if it were more ‘realistic,’ i.e. closer to the experience of human relations. 4.2
The Confidence Problem – And Carole Smith’s Solution
The complexity and risk-laden nature of health care scenarios has also led to a re-evaluation of the nature and role of confidence in human interaction. While at the heart of much trust research, the understanding (often associated with Luhmann; [43]) of confidence in terms of an association with willingness to confide in another, or have a positive belief about another party, has recently been implicitly called into question through a quite different interpretation of the
28
S. Marsh and M.R. Dibben
concept. In sum, this interpretation, having a risk and operations management basis derived from the need to achieve clinical governance and public sector accountability, suggests that the search for confidence is indicative of – at best – insufficient trust in the other party [53]. More likely, it is indicative of the need to explicitly and critically compare the performance of others rather than take their word for it [37] – something which in our eyes seems more akin to distrust. We shall now proceed to examine this definitional problem more closely. It is interesting to note that Luhmann drew a very clear distinction between trust and confidence that calls into question research suggesting trust is a ‘confident expectation. . . ’ Luhmann suggested that confidence is indicated by a lack of consideration for the risks involved [whereas] trust is indicated by a consideration of the risks involved [8–pages 97–103]; see also [48–page 274] for further discussion). We may ask how confidence can then be a part of trust at all? To complicate matters further, there is also the issue of self-trust, the trust of the trusting agent in itself to act in the best interests of itself. To avoid an explicitly psychological emphasis that would lead one away from an account of the situation and the other party, we have previously handled this in terms of perceptions of self-competence [48]; i.e. as a co-operation criterion). In other words, a more complete account of the behaviour of the trusting agent requires an estimation of that agents confidence in itself to act in its best interests according to its recognised abilities in the situation, and as compared with its perceived competence of the other agent. In sum, therefore, we can surmise four different interpretations of competence. First, confidence as concerning a trust of another party sufficient to be willing to confide in that party (e.g. [10]). Second, confidence as being confident in ones own decision to place trust (or distrust) in another (e.g. [24]. Third, confidence as self-assuredness to the extent of acting without consideration for risk [8]. Fourth, confidence in oneself as an agent based on ones assessment of ones own competence, as a conceptual proxy for self-trust [48]. Is there any new means by which to better clarify the distinction between trust and confidence? One contentious, but potentially helpful way of understanding the difference has been proposed by Carole Smith as a result of studying social work and the public sector accountability of such activity. Research in public policy and management has revealed the need to better comprehend how trust sustains wellfunctioning organisations, ‘especially those agencies in the public sector that lack market discipline [54, 38, 55, 56]. The impact of public trust comes to the fore in such circumstances, as it has an impact on the nature and extent of the accountability systems put in place by public sector managers (e.g., [57, 58, 51]). Such accountability systems are intended to provide appropriate reassurance to the public and enable effective corrective action to be taken to ensure public safety. These accountability systems, however, rely largely on explicit measurement of individual performance and organisational outcomes to establish confidence intervals that can be proven to be an accurate account of the organisation and the work of its employees. Such intense focus on performance measurement, coupled with a range of potential indictments for any failure to meet organisational
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
29
objectives has,[53] argues, eroded the trust between employees and managers necessary for effective professional relationships, such as those found in hospitals. In this sense, therefore the drive for public accountability through the establishment of explicit quantitative measures of performance standards, i.e. the drive for the establishment of public confidence, is in direct conflict with interpersonal trust [59]. To unpack this problematic, Smith [53] draws a stark distinction between trust and confidence, suggesting the two concepts are indeed very different, but not in the way Luhmann proposed. For Smith, trust concerns uncertainty about outcomes, an ambiguity of objective information and the exercise of discretion about action. It is also an internal attribution, a moral exercise of free will that assumes most significance in situations where there is a lack of regulation or means of coercion. Confidence, on the other hand, concerns the establishment of explicitly predictable outcomes, information is objective, standardised and scientific and there is little opportunity or even need to exercise discretion about action. In this sense, therefore, systemic confidence is seen an external attribution lacking morality that assumes most significance in situations where there are extensive regulatory mechanisms and / or opportunities for coercion of individual agents. In sum, according to Carole Smith, the institutional or managerial search for confidence is indicative of a lack of trust, perhaps even genuine distrust. Further, such a search for confidence may in fact have a tendency to instil distrust among professional colleagues, as a result of the increased sense of scrutiny and critical peer comparison. This is clearly a very different interpretation of what is mean by confidence. We wonder: – Whether and how it would be possible to model such trust vs. confidence distinctions and inter alia impact in more formal (computational) terms; – What impact this may have on the behaviour of such agents; and again – Whether such behaviour would be productive from a user perspective – even if it were more realistic, i.e. closer to the experience of human relations.
5
Conclusions and a Call to Arms
We have noticed in recent literature that, some notable exceptions aside, there is an overarching acceptance that trust is a positive phenomenon that should be encouraged, for example to get people to buy more stuff, or get jobs done, or share information. While lack of trust is paid attention to, it is seen more as a byproduct of the trust phenomenon everyone has to adhere to. We argue that Distrust and Untrust, respectively negative and ‘not enough Trust,’ allied under the wider umbrella of trust, are valuable and positive means to achieving concrete foundations to action in environments of uncertainty and doubt. We argue that there are ways to estimate and work with values for these phenomena that allow autonomous agents or other actors to behave sensibly in such situations. This behaviour can include, but is not limited to, recourse
30
S. Marsh and M.R. Dibben
to other authorities, adjustment of resources or expectations, manipulation of situations to achieve comfort, and so on. Finally, we argue that Mistrust, the misplacing of trust, can tell an agent a great deal more about who to trust next time, or what went wrong, when allied with Untrust and Distrust information or conjecture. To an extent, this paper represents something of a ‘call to arms’ to trust researchers to examine the phenomena and strengths and weaknesses of trust, untrust, distrust and mistrust to achieve their goals in a more rounded way. This includes the need for better models of the darker side of trust. We have made a first effort at this discussion and look forward to much more detailed explorations in the research to come. For our part, we are examining how the phenomena work in multi-agent systems and information sharing architectures to allow partial access, modified access, or simply curtailed access to information, for example in CSCW, P2P architectures or community-based information sharing agents (cf [60]). Taking the concept further, we are examining how the related phenomenon of forgiveness can work in conjunction with trust and its darker components to create a gentler side to the security ‘arms race’ we find ourselves embroiled in.
References 1. Nielsen, J.: Trust or bust: Communicating trustworthiness in web design. Alertbox (http://www.useit.com/alertbox/990307.html) (1999) 2. Cheskin/Studio Archetype: Ecommerce trust (available online at: http://www. cheskin.com/p/ar.asp?mlid=7&arid=40&art=0). Technical report (1999) 3. Cheskin/Studio Archetype: Trust in the wired americas (available online at: http://www.cheskin.com/p/ar.asp?mlid=7&arid=12&art=0). Technical report (2000) 4. Head, M., Hassan, K.: Building online trust through socially rich web interfaces. In Marsh, S., ed.: Proceedings of PST 2004, International Conference on Privacy, Security and Trust (http://dev.hil.unb.ca/Texts/PST/). (2004) 5. Egger, F.: From Interactions to Transactions: Designing the Trust Experience for Business-to-Consumer Electronic Commerce. PhD thesis, Eindhoven University of Technology (2003) 6. Sillence, E., Briggs, P., Fishwick, L., Harris, P.: Trust and mistrust of online health sites. In: Proceedings of the 2004 conference on Human factors in computing systems. (2004) 663–670 7. McKnight, D.H., Kacmar, C., Choudhury, V.: Whoops... Did I use the Wrong concept to Predict E-Commerce Trust? Modeling the Risk-Related Effects of Trust versus Distrust Concepts. In: 36th Hawaii International Conference on Systems Sciences. (2003) 8. Luhmann, N.: Familiarity, confidence, trust: Problems and alternatives. In Gambetta, D., ed.: Trust. Blackwell (1990) 94–107 9. McKnight, D.H., Chervany, N.L.: Trust and distrust definitions: One bite at a time. In Falcone, R., Singh, M., Tan, Y.H., eds.: Trust in Cyber-Societies. Volume 2246 of Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin, Heidelberg (2001)
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
31
10. Lewicki, R.J., McAllister, D.J.B., Bies, R.J.: Trust and distrust: New relationships and realities. Academy of Management Review 23 (1998) 438–458 11. Marsh, S.: Formalising Trust as a Computational Concept. PhD thesis, Department of Computing Science, University of Stirling (1994) Available online via http://www.stephenmarsh.ca/Files/pubs/Trust-thesis.pdf. 12. Kramer, R.M.., Tyler, T.R.: Trust in Organisations: Frontiers of Theory and Research. Thousand Oaks: Sage (1996) 13. Hollis, M.: Trust Within Reason. Cambridge University Press (1998) 14. Luhmann, N.: Trust and Power. Wiley, Chichester (1979) 15. Lane, C., Bachmann, R., eds.: Trust Within and Between Organisations: Conceptual Issues and Empirical Applications. Oxford University Press (1998) 16. Golembiewski, R.T., McConkie, M.: The centrality of interpersonal trust in group processes. In Cooper, C.L., ed.: Theories of Group Processes. Wiley (1975) 131–185 17. Sydow, J.: Understanding the constitution of interorganisational trust. In Lane, C., Bachmann, R., eds.: Trust Within and Between Organisations. Oxford University Press (1998) 18. Cvetkovich, G.: The attribution of social trust. In Cvetkovich, G., Lofstedt, R., eds.: Social Trust and the Management of Risk. London: Earthscan (1999) 53–61 19. Earle, T.C., Cvetkovich, G.: Social trust and culture in risk management. In Cvetkovich, G., Lofstedt, R.E., eds.: Social Trust and the Management of Risk. London: Earthscan (1999) 9–21 20. Gowda, M.V.R.: Social trust, risk management and culture: Insights from native america. In Cvetkovich, G., Lofstedt, R.J., eds.: Social Trust and the Management of Risk. London: Earthscan (1999) 128–139 21. Sztompka, P.: Trust: a Sociological Theory. Cambridge University Press (1999) 22. Lewicki, R.J., McAllister, D.J., Bies, R.J.: Trust and distrust: New relationships and realities. The Academy of Management Review 23 (1998) 438–458 23. Marsh, S., Briggs, P., Wagealla, W.: Enhancing collaborative environments on the basis of trust. Available online at http://www. stephenmarsh.ca/Files/pubs/CollaborativeTrust.pdf (2004) 24. Boon, S.D., Holmes, J.G.: The dynamics of interpersonal trust: resolving uncertainty in the face of risk. In Hinde, R.A., Groebel, J., eds.: Cooperation and Prosocial Behaviour. Cambridge University Press (1991) 190–211 25. Low, M., Srivatsan, V.: What does it mean to trust an entrepreneur? In Birley, S., MacMillan, I.C., eds.: International Entrepreneurship. Routledge, London (1995) 59–78 26. Noteboom, B., Berger, H., Noordehaven, N.: Effects of trust and governance on relational risk. Academy of Management Journal 40 (1997) 308–338 27. Deutsch, M.: Cooperation and trust: Some theoretical notes. In Jones, M.R., ed.: Nebraska Symposium on Motivation, Nebraska University Press (1962) 28. Abdul-Rahman, A.: A Framework for Decentralised Trust Reasoning. PhD thesis, Department of Computer Science, University College London (2004 (Submitted)) 29. Nye, Jr., J.S., Zelinkow, P.D., King, D.C., eds.: Why People Don’t Trust Government. Harvard University Press (1997) 30. Kramer, R.M.: Trust and distrust in organizations: Emerging perspectives, enduring questions. Annual Review of Psychology 50 (1999) 569–598 31. Mui, L.: Computational Models of Trust and Reputation: Agents, Evolutionary Games, and Social Networks. PhD thesis, Massechusetts Institute of Technology, Department of Electrical Engineering and Computer Science (2002)
32
S. Marsh and M.R. Dibben
32. Seigneur, J., Jensen, C.D.: The role of identity in pervasive computational trust. In Robinson, P., Vogt, H., Wagealla, W., eds.: Privacy, Security and Trust within the Context of Pervasive Computing. Volume 780 of Kluwer International Series in Engineering and Computer Science. Kluwer (2005) 33. Kramer, R.M.: Trust rules for trust dilemmas: How decision makers think and act in the shadow of doubt. In Falcone, R., Singh, M., Tan, Y.H., eds.: Trust in Cyber Societies. Springer Verlag, Lecture Notes in Artificial Intelligence, LNAI 2246 (2001) 9–26 34. Marsh, S.: Optimism and pessimism in trust. In Ramirez, J., ed.: Proceedings Iberoamerican Conference on Artificial Intelligence/National Conference on Artificial Intelligence (IBERAMIA94/CNAISE94), McGraw-Hill (1994) 35. Lagenspetz, O.: Legitimacy and trust. Philosophical Investigations 15 (1992) 1–21 36. Daughtrey, T.: Costs of trust for e-business. Quality Progress (2001) 37. Davies, H., Mannion, R.: Clinical governance: Striking a balance between checking and trusting. In Smith, P.C., ed.: Reforming Markets in Health Care: An Economic Perspective. London: Open University Press (1999) 38. Davies, H.T.O.: Falling public trust in health services: Implications for accountability. Journal of Health Service Research and Policy 4 (1999) 193–194 39. Dibben, M.R.: Exploring the processual nature of trust and co-operation in orgnisations: A whiteheadian analysis. Philosophy of Management 4 (2004) 25–40 40. Blau, P.: Exchange and Power in Social Life. New York: John Wiley and Sons (1964) 41. Berger, P.: Sociology Reinterpreted. London: Penguin (1982) 42. Lewicki, R.J., Bunker, B.B.: Trust in relationships: A model of trust, development and decline. In Bunker, B.B., Rubin, J.Z., eds.: Conflict, Cooperation and Justice. San Francisco: Josey Bass (1985) 133–173 43. Lewicki, R.J., Bunker, B.B.: Developing and maintaining trust in working relationships. In Kramer, R.M., Tyler, T.R., eds.: Trust in Organizations: Frontiers of Theory and Research. Thousand Oaks: Sage (1996) 114–139 44. Rotter, J.B.: Generalized expectancies for interpersonal trust. American Psychologist 25 (1971) 443–452 45. Arrow, K.J.: The Limits of Organization. New York: Norton (1974) 46. Axelrod, R.: The Evolution of Cooperation. Basic Books, New York (1984) 47. Coleman, J.S.: The Foundations of Social Theory. The Belknap Press of the University of Harvard (1990) 48. Dibben, M.R.: Exploring Interpersonal Trust in the Entrepreneurial Venture. London: MacMillan (2000) 49. Marsh, S., Dibben, M.R.: The role of trust in information science and technology. In Cronin, B., ed.: Annual Review of Information Science and Technology. Volume 37. Information Today Inc. (2003) 465–498 50. Meyerson, D., Weick, K., Kramer, R.M.: Swift trust and temporary groups. In Kramer, R., Tyler, T., eds.: Trust in Organisations: Frontiers of Theory and Research. Thousand Oaks: Sage (1996) 166–195 51. Mechanic, D.: Changing medical organization and the erosion of trust. Millbank Quarterly 74 (1996) 171–189 52. Mechanic, D., Meyer, S.: Concepts of trust among patients with serious illness. Journal of Social Science and Medicine 51 (2000) 657–668 53. Smith, C.: Trust and confidence: Possibilities for social work in ‘high modernity’. British Journal of Social Work 31 (2001) 287–305 54. Cvetkovich, G., Lofstedt, R.E., eds.: Social Trust and the Management of Risk. London: Earthscan (1999)
Trust, Untrust, Distrust and Mistrust – An Exploration of the Dark(er) Side
33
55. Waren, M.E.: Democracy and Trust. Cambridge University Press (1999) 56. Waterhouse, L., Beloff, H., eds.: Hume Papers on Public Policy: Trust in Public Life. Volume 7 of Hume Papers on Public Policy. Edinburgh: Edinburgh University Press (1999) 57. Davies, H., Lampell, J.: Trust in performance indicators? Quality in Health Care 7 (1998) 159–162 58. Harrison, S., P. J, L.: Towards a High-Trust NHS: Proposals for Minimally Invasive Reform. London: Her Majesty’s Stationery Office (1996) 59. Dibben, M.R., Davis, H.T.O.: Trustworthy doctors in confidence-building systems. Quality & Safety in Health Care 13 (2004) 88–89 60. Marsh, S., Ghorbani, A.A., Bhavsar, V.C.: The ACORN Multi-Agent System. Web Intelligence and Agent Systems 1 (2003) 65–86
