Role and Challenges of Crowdsourcing and Citizen Science in the Context of the Data Revolution
* Master Thesis: In The Crowd We Trust - Role and Challenges of Crowdsourcing and Citizen Science in the Context of the Data Revolution: An Interdisciplinary Approach. Ana von Teschenhausen. Universitat Leipzig / Universitat Wien, 2015
The Main Argument:
"Despite of persistent efforts from the part of organizations aiming to solve or to alleviate the world’s most challenging issues, there are limitations of the current problem-solving system based on hierarchical bureaucratic models. These are mainly related to the powerlessness of the professional sector when, alone, facing global issues of ever increasing complexity and uncertainty. The current context often called “the network age” has in turn, supported and enhanced systems which serve as means for coping with these complex and uncertain scenarios, such as the concept of distributed cognition that leads (in its positive aspects) to collaborative, participatory and peer-to-peer common oriented processes, including the emergence of decentralized systems as well as the gradual empowerment of the civil society (overlapping with the latter); forming altogether, the background of latent paradigm shifts. Concurrently there is the political discourse (driven by the UN) on Sustainable Development Goals (SDGs) and of a Data Revolution, where the claim is that the latter is indispensable for achieving the former. The Data Revolution’s main purpose is to fill data gaps in order to leave no one behind and its realization is also crucial for unlocking other latent paradigm shifts. This thesis introduces the core concepts of such a paradigm shifts whilst focusing on two collaborative ap-proaches for data collection and analysis: crowdsourcing and citizen science; most specifically on their role and challenges in the context of the current data revolution. Crowdsourcing and citizen science (also citizen journalism and other participatory monitoring activities) are not just part of the context of latent paradigm shifts, but do play a major role for the realization of a data revolution, once professionals and machines do not currently suffice to fill those data gaps. This hinders proper accounting, planning and distribution of resources and hence spoils efforts to tackle the critical issues involved in the SDGs. Unfortunately there is wide reluctance from the part of the institutions (UN, INGOs and governments) in adopting these approaches as valid data/information sources. The main goal of this MA thesis is to identify the reason behind this reluctance, shedding light on deadlocks hampering the consolidation of a data revolution. In order to do so, the problematic was approached from multiple perspectives, characterizing a truly interdisciplinary inquiry, which, based on the approach of the “informed grounded theory”, presents the main challenges of crowdsourcing and citizen science in multiple levels and from multiple perspectives. From a pragmatic perspective, issues related with data quality as well as the issue of little understanding have been the most cited. Withal the fact that both issues are not exclusive to crowdsourcing or citizen science has shown to be crucial for the present inquiry, although widely neglected in the literature. Thus for this and other important reasons to be further discussed throughout chapters 3 and 4, an alternative to the “quality-centred” approach towards crowdsourcing and citizen science is appropriate, nevertheless the quality issue should not be disregarded, as it is reasonable, but eventually addressed in a different manner as part of the problematic, but not as “the problematic” itself.
In addition, prejudice from the part of professionals has been cited by some expert interviewees as the “real” reason behind the reluctance vis-à-vis crowdsourcing and citizen science as valid data/information sources. Analysis has shown that prejudice is omnipresent with regards to new technologies or any novel approach. For there is no time to wait for wider acceptance, given the urgency of matters, and as prejudice shows to result from ignorance linked to the clash of paradigms, this thesis also focuses on the question of what lays behind prejudice. In order to answer this question, other crucial parts of the problematic encompassing constrained profes-sional autonomy, risk and blame aversion are discussed throughout the thesis, forming altogether a hypothesis advocating that the resistance from the part of institutions towards crowdsourcing and citizen science is not just rooted on prejudice, but also on lack of trust in society; being both resultants of excess of accountability which has been ultimately delineated by public discourse. After a rough analysis, the latter has shown to be in unbalance, overemphasizing the need for accountability and consequently (based on the premise of a necessary balance between trust and control/accountability), inadvertently, undermining trust. Paradoxically the overdose of accountability in public discourse reflects an attempt to restore trust in society. This paradox can be found also within the discourse on the data revolution, hindering this and other latent paradigm shifts of thriving, as for them all mutual trust is a requisite. If there is no trust from the part of organizations towards the public, there will be no room (acceptance) for approaches relying on citizen-generated data, leaving data gaps and many people and countries behind. The outcomes of this analysis are useful for those stakeholders contributing to the discourses on the fundamental role of a data revolution, as they should reframe the latter giving more weight to “top-down” trust, if we are to see the realization of such a shift."
Outline of The Thesis:
"The thesis starts with a brief description of the subject which is placed within the current technological and socio-political contexts, as well as with the presentation of the main research question:
“What lays behind the phenomenon of the reluctance of organizations to embrace crowdsourcing and citizen science approaches for data collection and analysis?”
Subsequently, the following sub-questions are elaborated:
(1)“Which of the three actor groups of concern in this study (NGOs, UN and governments) is more likely to act positively toward crowdsourcing and citizen science approaches and why?”
(2) “Which are the most frequently named issues of these approaches that may be hampering wider acceptance and adoption, and what are the proposed respective potential solutions?”
Chapter 2 presents the applied methodology, where an explanation of the method of analysis “[partial] informed grounded theory” is provided along with a rationalization of the choice. Then the researcher’s position is discussed, bringing up some personal motivations and experiences which may have played a role in shaping the present work. Subsequently one finds a literature review and methodological approaches, including a detailed description of the interviewing process and the analytical strategy.
The theoretical framework is presented in chapter 3, drawing on theories and theoretical frameworks such as: the philosophy of language, semiotics and Searle’s social ontology; organizational theories, including Weber’s theory of bureaucracy, incentive theories, risk avoidance and transfer, as well as a more detailed approach concerning the roles of IOs, INGOs and NGOs in the global arena, as well as power relations appertain to these organizations; philosophy on accountability, trust and control; Foucault’s stand on power and knowledge as well as his conception of genealogies and subjugated knowledge; data quality in uncertain scenarios; and Hutchin’s theory of distributed cognition; will show to be fundamental to the full understanding of the rationale of this this thesis as well as for supporting argumentation throughout the work.
The core concepts of the thesis “crowdsourcing and citizen science” (also citizen journalism and other participatory activities for data collection and analysis), as well as a conceptual framework, presented as an overview of the multi-modal scenario regarding latent paradigm shifts based on mutual trust is discussed in chapter 4, followed in chapter 5, by the analysis of the data/information gathered through interviews and its relation to other sources, and of suggestions for overcoming the mentioned challenges.
Chapter 6 summarises the final hypothesis and considers how to resolve the deadlock pro- voking the phenomenon in question."