Heavily influenced by the work of Jean Nicolas Druey and Herbert Burkert, among others, I’ve been working on information quality issues in various contexts for the past 8 years or so. Today, I have the pleasure to attend the Yale Information Society Project’s conference on Reputation Economies in Cyberspace and contribute to a panel on reputational quality and information quality. Essentially, I would like to share three observations that are based on previous research projects. The three points I will talk about later today are:
- From both a theoretical and empirical viewpoint, information quality is a horse that is difficult to catch. As a complicating factor, information quality in the context of reputation systems is a meta-question, concerning the quality of statements about the qualities of a person, service, advice, or the like. As such, it is important to be specific about the particular aspect of the quality challenge that is up for discussion in a given quality discourse. A taxonomy of quality problems/issues in the context of online reputation might be a good first step. Such a taxonomy needs to conceptualize informational quality of reputation as a composite of syntactic (data), semantic (meaning), and pragmatic (effects) factors. [We will present an initial draft of such a taxonomy at the conference]
- While addressing specific quality issues, it’s important to consider the full range of possible approaches (“tools”) that are available. The role of market-based approaches (“pricing”, “incentives”) has already been explored in detail in the context of reputation systems. We also have a growing understanding about the social norms at work (research on online identity). As far as technology (“platform design”) is concerned, insights from social signaling theory might be a source of inspiration (e.g. conditions to foster honest signaling). Largely unexplored, by contrast, is the substantive (e.g. privacy) or procedural (e.g. due process) role that law may play in the context of a blended approach.
- Information quality conflicts can’t be avoided, only managed. Each “regulatory” approach mentioned before comes at costs and has inherent (factual and/or normative) limitations. A general limitation is the contextual and subjective nature of human information processing and decision-making processes (e.g. buying a digital camera) in which the quality of statements about quality (reputation) plays a role. The case of “teenagers” might be illustrative given our knowledge about the neurobiological state of development of brain areas (prefrontal cortex) involved in information selection, interpretation, and evaluation. But also cognitive biases of adults mark the limits on what can be achieved at the level of governance of reputation systems.
Comments, as always, welcome.