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Institute of Cognitive Sciences and Technologies, CNR, Rome
The introductive chapter is really excellent. It clarifies the book's goals and introduces the main arguments for a general overview of the different methodological approaches. The reader easily realise that this is not a book on the theoretical debate on trust. Although certain conceptual themes on trust are addressed, the book privileges empirical issues.
The division of the book into three parts (conceptual issues and empirical approaches, qualitative methods and quantitative methods) reflects the need of providing a rationale to the field more than satisfying the practical aspects of investigation, in which sometimes qualitative and quantitative methods are mixed. This is also reflected in the book structure. Each contribution is concisely presented in about ten pages, unfortunately at the expense of detail. On the one hand, the book provides a good overview on the qualitative and quantitative methods to study trust in the social sciences, so filling a void in the specialist literature. On the other hand, this would be better if combined with attention to analytic foundations.
In the first part of the book (conceptual issues) different scales (micro, organizational and societal levels) are presented where trust may have an impact on outcomes. In particular, three principal chapters (chapters 5, 6, and 7) focus on the micro, meso and societal scale, respectively. A set of interesting conceptual questions are evaluated in this first part as follows: the difference between trust and perceived trustworthiness; trust as a process deeply embedded in social relationships; trust as a main element of the decision-making processes; trust and distrust as independent constructs; the role of the context in trust-building. About this last problem, the chapter 2 (by Kramer) shows the utility of the trust game method in identifying cognitive and affecting elements of trust, but it also underlines the need for coping with more natural and organizational contexts (outside of the laboratory) to evaluate the “social and contextual variables that influence choice in real-world settings” (page 26). I agree with the Editors that this first "ontological" part is an essential premise for a better understanding of the methodological issues presented in the other parts.
It is interesting to note that usually the literature about the methodological approaches keeps qualitative and quantitative methods separated. This book includes various cases where these methods are mixed, such as, for example, chapters 11, 12, 13, and 14. The qualitative researches are mainly based on interviews about trust, with all the problems related to sensitive issues (the "access" problem). Chapter 11 shows how the use of card sort could help to simplify the relationship between interviewer and interviewee, allowing to conduct in-depth interviews. Other qualitative methods are also presented, such as observation, observation mixed with interviews ( critical incident technique, chapter 16), and hermeneutic method (historical records and diaries, chapter 15).
The quantitative researches, included in the third part, touch upon different aspects of trust, presenting various scales and measures: trusting attitudes or moralistic trust (Uslaner, see chapter 7, analyses the question: "can people be trusted?"), specific trust, which is related to a specific person, and measures of trusting interaction. A classical example of the quantitative method of trust is the trust game (interactive experiment based on trust) that is played in a laboratory setting. Chapter 3 presents a review of the trust games, while in chapter 2, Kramer underlines the importance of integrating the trust game with other methods outside of the laboratory. Other measures of trust are related with the response to facial characteristics (chapter 3) or the associations with trust concept on the basis of the response to stimuli (chapter 22). One of the more relevant problems with the quantification approaches is the challenge of converging and replying different measures and scales to allow for extensive comparison.
In their excellent introduction, the editors point out five specific challenges that can be identified in the whole volume: "the dynamic process of trust; researching tacit elements of trust; conceptualizing and describing trust in different cultures; the role of researchers in shaping the trust situation they are researching; and research ethics of trust". Each of these themes is really interesting and they are all eventually addressed in different chapters of the book. Concerning these themes, the more stimulating works, in my view, are those dealing with the temporal analysis of trust (chapters 16 and 21) and the complex and interfering trust relationship between researcher and the researched (chapters 8 and 10).
This book is a successful attempt of overcoming the disciplinary borders, exploiting the methodological approaches as tools to coordinate different competencies and professions. Indeed, trust has a strongly multi-disciplinary, intimate nature, whose understanding involve effort by scholars from psychology, sociology, economics, management, and so on.
This said, in this difficult challenge, I have to underline an omission in this book (excluded a reference of the chapter 4), on which any JASSS reader would agree. In the last twenty years, studies on trust have bypassed the boundaries of the social sciences and have crept into other areas, identifying new methodological tools, more appropriate to these disciplinary areas. I am referring, in particular, to neurosciences (e.g., Zak, Kurzban, Matzner 2004; King-Casas et al. 2005; Kosfeld et al. 2005) and artificial intelligence (e.g., Marsh 1994; Shneiderman 2000; Falcone and Castelfranchi 2004; Sabater and Sierra 2005; Castelfranchi and Falcone 2010).
This propagation of trust study has increased the knowledge about this phenomenon, at the same time answering questions coming from the new technologically advanced social environments in which (robotic or virtual, individual or distributed) machines do not perform just a simply instrumental function, but assume increasingly intelligent roles, including features like adaptation, autonomy, reasoning and so on. This determined a shift in the focus: there is not only the problem of understanding more deeply the trust of humans in this new pervasive machines (and towards other humans mediated through these artificial systems), but also to study the modality for transferring to the new artificial autonomous systems properties that allow them to become trustworthy and understand the trustworthiness of the other interacting agents. This means considering the collaborative dimension.
To sum up, I can say that this book accomplishes several tasks:
- it presents a very relevant overview about the research methods used in the social sciences for studying trust (“even if not all areas of research methods on trust have been included”, page 3);
- it identifies new potential directions and trends in the research on trust, by providing discussions about the fruitful methodological developments, the challenges and innovation.
- it pushes scholars of various scientific areas (and using different methods) to converge and integrate their efforts.
FALCONE, R., Castelfranchi, C. (2004). Trust Dynamics: How Trust is influenced by direct experiences and by Trust itself. Proceedings of the 3rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-04), New York, 19-23 July 2004, ACM-ISBN 1-58113-864-4, pp. 740-747.
KING-CASAS, Tomlin, B D., Anen, C., Camerer, C. F., Quartz, S. R., Montague, P. R. (2005). Getting to know you: Reputation and Trust in a Two-Person Economic Exchange. Science 308, 78.
KOSFELD, M., Heinrichs, M., Zak, P. J., Fischbacher, U., Fehr, E. (2005). Oxytocin Increases Trust in Humans. Nature, 435, 673.
MARSH, S. (1994). Formalizing Trust as a Computational Concept. PhD Thesis, University of Stirling, Department of Computer Science and Mathematics.
SABATER, J. and Sierra, C. (2005). Review on computational trust and reputation models. Artificial Intelligence Review, 24, pp. 22-60.
SHNEIDERMAN, B. (2000). Designing trust into online experiences. Communications of the ACM 43(12), pp. 57-59.
ZAK, P. J., Kurzban R., Matzner W. T. (2004). The Neurobiology of Trust. Annals of the New York Academy of Sciences, 1032, pp. 224-227.
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