Social theory faces new challenges as society changes. The question is not only if social theory can keep up with –and account for– social transformations, but also if it can avail of social changes (in this case, the current dominance of digital media) in order to reinvent itself. The most attracting features of modern digital resources, such as Big Data, lies on their tools of analysis. But it just might be that the most promising contribution to social theory resides in the epistemological foundations backing these developments and the conceptual tools they can offer to rephrase epistemological issues. In this sense, the function debuggers play with regard to their target programs could shed new light not only on the process of knowledge formation, but also on the process of theory-improvement/ updating. The present contribution intends to show how theory-debugging might work, by taking the sociology of Niklas Luhmann as a target program to be debugged by fractal geometry with the goal of delivering an enhanced version of system theory. It concludes by arguing for the plausibility of describing communication as a natural fractal susceptible of being modelled by some kind of fractal set, and for how communication media are responsible for the fractal structure of communication along sociocultural evolution.

Introduction

Once algorithms were an abstract and weird idea developed by philosophers of mathematics and few people knew about them and what the word actually meant; nowadays it is hard to think of someone who have not heard the word at least once, not to mention the fact that, unlike in the past, algorithms are doing things for us all the time. A data revolution has shaken the world changing in unexpected ways how we interact with other human beings and with this new ecology of artificial forms of intelligence (an interface some call Global Brain (Heylighen and Lenartowicz, 2017)), how we do business, how we teach and how we learn, how we read the news, how we search for information, in short, everything we know, the things we do (Mayer-Schonberger and Cukier, 2013) and even the pace of life (Wajcman, 2008). And science, of course, is not the exception. Doing science in an information society brings many questions to the fore. To what extent are Big Data, Data Science, AI, Deep Learning, among others, changing the way science constructs knowledge, (i.e. to put forward and test hypothesis, construct theories and deal with the problem of the nature of knowledge and the foundation of knowledgeclaiming statements, create concepts and objects of knowledge, and so on)? (Berthon et al., 2000; Boyd and Crawford, 2012; Kitchin, 2014; Lash, 2002) Can algorithms make the scientific method obsolete? (Anderson, 2008) Can algorithms substitute humans in the process of abduction by suggesting the researcher an array of emergent patterns out of his data base? Are the new statistical tools of Data Science reinforcing and radicalizing empiricism?

In this article, it is argued that social theory must be renewed to comprehend the new power constellations and new challenges to aesthetic and intellectual ways of life that are being shaped by digital transformation. However, while social theory has to renew its tools in order to grasp previously unknown realities, it also runs the risk of being assimilated into the very process that it seeks to understand, or to assimilate so much of the dominant belief system that it loses its critical and creative potential. The aim of this article is to propose a particular, renewed social theory that consists in a recasting some social theoretic insights to be able to preserve aesthetic and intellectual potentials of critique and negation. Through the lens of this renewed social theory, digital transformation is understood as a form of economic domination, which, as this article shows, is sustained by un-enlightenment, that is, by fraudulent myths and misplaced metaphors.

Introduction

Digital transformation is generally theorized as a process by which social existence is increasingly affected by digital processes, digital tools, and abundance of information (Lindgren, 2017). As a result, a new hybrid world arises, in which experience is constituted by the merging of the physical world with the digital world. In the digital age, digital processes are so deeply embedded in the daily life of information capitalism that people barely realize they interact with devices and operate machines (Van de Boomen, 2014; Lupton, 2015; Turkle, 2015; Hess and Davisson, 2018). It is evident that hermeneutic social theory needs to take digital transformation into account (Ossewaarde, 2018; Schroeder, 2018). A renewed hermeneutic social theory is necessary to understand the new age initiated by digital technologies and algorithmic modernization. “Classical” social theory arose in a context of industrialization, where the pervasive effects of automatization were known but those of digitalization were as yet unknown. Given the transformation of the industrial context, hermeneutic social theory has to renew its tools in order to grasp previously unknown realities (cf. Fuchs, 2017a). However, in this process of renewing, hermeneutic social theory runs the risk of being assimilated into the very process that it seeks to understand, or to assimilate so much of the digital age’s dominant language and belief system that it loses its poetic sensibility and its critical, interpretative, and creative potential. In order to understand the “digital transformation of social theory”, it is argued in this article, that digital transformation is, to a high extent, a Silicon Valley-driven process that impacts on hermeneutic social theory’s intellectual potentials. It must be emphasized that the type of social theory that is discussed, and renewed, in this article is a particular social theory that has emerged from the Weberian and hermeneutic traditions. In what follows, the argument of this paper is constructed in seven steps.

Recently, the relationship between reputation and altruism has gained significant attention. The present study examined whether the relationship between rejection avoidance and altruism differs according to social norms. A total of 320 participants completed an online survey with questions concerning rejection avoidance and altruism in situations where either a prosocial or non-prosocial norm was present. As predicted, people with higher levels of rejection avoidance displayed less altruism only in the context of non-prosocial norms. This result corresponds with previous evidence that suggests that altruism can be evaluated negatively by others when it deviates from social norms. These findings shed a new light on the relationship between reputation and altruism.

Introduction

Individuals sometimes display altruism, which is the tendency to act on behalf of others, even at one’s own expense (Fehr & Fischbacher, 2003). Altruism has been shown to be affected by reputation (for a review, see Barclay, 2012). For example, people behave more altruistically when their behavior is being observed by others (Barclay & Willer, 2007). Both laboratory (e.g., Andreoni & Petrie, 2004; Barclay & Willer, 2007) and field (e.g., Lacetera & Macis, 2010) studies have repeatedly shown that situational factors that trigger concern for reputation promote altruism. Based on these studies, it is probable that individual differences in the sensitivity to reputation (i.e., reputational concern) also relate positively to altruism; in other words, individuals with a high concern for their reputation would display more altruism. However, a recent study has shown that this relationship is not always positive. Kawamura and Kusumi (2018) examined how praise seeking, the tendency to seek a good reputation, and rejection avoidance, the tendency to avoid a bad reputation (Wu, Balliet, & Van Lange, 2016), were related to altruism toward various recipients (i.e., family members, friends/acquaintances, and strangers). As predicted, individuals with higher levels of praise seeking displayed more altruism; however, individuals with higher levels of rejection avoidance displayed less altruism toward strangers. Given that many studies have shown that reputational cues promote altruism, it is important to explore the contextual factors that negatively impact the relationship between reputational concerns and altruism. One possible explanation of this counterintuitive negative relationship is related to social norms. Sometimes altruism deviates from what most others do in a group (i.e., social norm). For example, when a group of co-workers are rushing because they are running late for a train, they may not help a stranger who appears to be searching for lost item at the station platform; in this situation, helping the person is regarded as a non-normative behavior in the group. Some studies suggest that altruism can be negatively evaluated when altruistic behavior is not normative. For example, Parks and Stone (2010) demonstrated that a person who excessively contributed more toward public goods than others was negatively evaluated by other group members. This finding is in line with Kawamura and Kusumi (2018) who measured altruism toward strangers, which is less normative compared to altruism toward more familiar recipients. Taken together these studies suggests that, when altruism is not evaluated as normative, people with high rejection avoidance may inhibit altruistic behavior in fear of possible negative evaluation from others. Thus, individuals who tend to fear rejection from others may inhibit altruism, when altruism was not perceived as normative. However, as Kawamura and Kusumi (2018) did not directly manipulate social norms in their study, this notion needs to be empirically investigated. In the present study, we conducted an online survey to investigate whether the relationship between reputational concern and altruism differed according to social norms. Participants read several vignettes depicting different scenarios, which either provided cues about a prosocial norm or a non-prosocial norm. We predicted that people with high rejection avoidance would inhibit altruism only in the context of non-prosocial norms.

مقاله سال 2016

 مجله امگا – Omega

The development of modern technologies has created gaps between technologies used for civilian life purposes and military applications. Technologies that civilians use in the daily life (e.g., global positioning system and the Internet) are initially developed and applied for the purpose of national defense. In other words, the driving force prompting developments in the emerging industries such as the information and communications technology (ICT) and semi-conductor industries is the development of technologies in military. Overall, this trend leads to the development of dual-use technologies, i.e. technologies for civilians and militaries.

According to an analysis conducted by Benoit [1], a U.S. national defense economist, at least 40 percent of successful military technologies contribute in improving people’s economic wellbeing. Specifically, military technologies are able to enhance a country’s security and the overall national economy [2-4]. By incorporating military technologies into the private industries, countries not only transfer military innovations or inventions to civilian livelihood that create incomes, but also help upgrade technologies in the private industries, which in turn actively participate in the construction of national defense.

Because of limited budgets and resources, governments of various countries would stringently review the use of defense expenditures and actively conduct performance evaluation. For example, the United States announced the Government Performance and Results Act in 1993, stipulating that public departments (including institutions involved in the research and development (R&D) of technologies) must assess their performance; in 1997, Japan approved the Practical Guide to the Evaluation of National R&D, which serves as the basic architecture of technology evaluation, and proposes that technologies should be evaluated based on their level of importance. However, adopting traditional financial reports to measure the efficiency of implementing a dual-use technology development program (DuTDP) will cause evaluators to overlook external benefits. Note that resource allocation and long-term development of the social economy are dependent on the performance of DuTDPs. If the direct benefits for R&D institutions (e.g., academic and technological outcomes and R&D revenues) and indirect benefits for the social economy (e.g., the number of technology transfer, the output value generated from investments, and the number of treasury transfers produced by R&D results) are considered in assessing performance, the actual performance of DuTDPs can be more accurately assessed.