Information Asymmetry and Digital Illiteracy

Data is shaping the way we live; hence it is called the Digital Age (Plesner & Husted, 2019). Data is affecting organizations, states, governments, citizens, and more. We have therefore entered the data economy, where search and transaction cost are reduced and data could be used as a facilitating tool within medical and scientific research, which in the end leads to higher efficiency.

Data is even used within public organs to deliver more efficient services and better social welfare (UN, 2019).

The amount of data produced and left behind by users online is vast in size, as 6,2 billion Google searches are conducted each day, as 238,7 billion emails are sent every day, etc. We are producing 5,8 billion gigabytes of data each day at the current rate, meaning enormous amounts of data to be used for tracking purposes. These enormous amounts of data are however dispersed over the entire web and are very messy, meaning complex methods of data processing is needed for the data to offer insights (UN, 2019).

The data economy is currently very uneven, equaling asymmetric information power between organization-organization, organization-consumer and organization-state relationships. The unique property of data makes these asymmetries very hard to reduce, as data depends on very complex infrastructure and monopolistic positions to gain the best possible insights, as is the case with Facebook, Google, Microsoft etc. Smaller firms in the field of data competition have no way to compete with the established firms due to the complexity. From a political economy perspective, these concentrations of power might increase the chance of “regulatory capture”, which is “a situation where policymakers or enforcement agencies are in a constant state of being influenced by powerful firms” (Hempling, 2014:5). The power of these organizations in both the economic and political perspective might therefore impede the freedom of the user and be a barrier for democracy.

The initial private organizational data tracking was based on an advertising incentive, i.e. targeting specific individuals with specific products. The business model this was based on, was as previously described based on a broader social agreement between the public and organizations of a monetarily free product in exchange for being exposed to advertising. This development within online behavioural advertising (OBA) has allowed for systems capable of covertly surveying consumer preferences. Due to lacking regulation within this arena, internet users have no control over this surveillance and could again be impeding freedom of choice and democracy (Libert & Nielsen, 2018).

OBA represents an extensive shift in the balance within society, which is caused by the concept information asymmetry. Information asymmetry is defined as a “situation that favors the more knowledgeable party in a transaction” according to the business dictionary (BD, 2020). An example of information asymmetry is the access to the free to use service Google Maps. This service has become very valuable for individuals as it offers detailed location mapping. It is important to emphasize the trade-off between the individual and Google, as Google gains tremendous insights into very specific information such as location of parking spaces, most popular parking spaces and roads, availability of parking spaces, etc. This allows google to offer very specific services for its users due to aggregation through algorithms and big data. This transaction is illustrated in the figure below.

Data asymmetry and the resulting imbalance of power is often raised in the context of personal data according to Dodds (2017) and Libert & Nielsen (2018). Organizations are empowered at the expense of the users. This imbalance is giving organizations and governments increased knowledge and hereby power over citizens. The current situation is therefore organizations knowing more about citizens than citizens possessing information about organizations hence the information asymmetry (Libert & Nielsen, 2018).

The information asymmetry is further enhanced by the concept information illiteracy also called digital illiteracy. Literacy is defined by the OECD “as the ability to understand and use information to expand one’s capacity” (Margerie, 2018). Digital illiteracy on the other hand is defined as “Digital gap emerged in certain social groups that have been left out of this technological process derived from their maladjustment to new technological developments” (IGI Global, 2020). In the context of

digital illiteracy, the OECD found in a study from 2018 that 70% of the population between 16 and 65 lack expertise within basic computer science (Margerie, 2018).

Digital illiteracy has become more evident than ever before, as the world is increasingly becoming digitalized. Digital illiteracy has created the digital divide, also called the “participatory gap”, which states that even individuals with computers, smartphones, internet, etc., lack the skills, education and familiarity to leverage the opportunities of the digital age. The differences in digital literacy have been correlated to patterns of social exclusion in society according to Warren (2007), Lee et al., (2015) and Mossberger et al., (2012) in Thakuriah et al., (2017). The current social divide is not a result of the generation divide, it is however a result of socioeconomic status (Thakuriah et al., 2017)

With the general adoption of the concept e-government, we are witnessing how public sectors are increasingly digitalized and hereby reliant on digital technology, navigate public web pages, electronic documentation and other important digital skills in the public sector. The participatory gap or digital illiteracy will undoubtedly increase complexity for individuals, organizations, etc., who are forced to access these public web pages (Thakuriah et al., 2017).

2.5 Stakeholder Theory

The purpose of our stakeholder analysis is to provide an overview of the different stakeholders relevant to the TPT on Danish public web pages and to provide an overview of the relations and interdependencies between the different stakeholders. There are several different definitions of a stakeholder, such as the definition by Freeman (1984) stating that stakeholders are individuals or groups who affect or are affected by an organization’s objectives. Classical stakeholder theory usually applies a neoclassical private organizational perspective, viewing the stakeholder from a specific organization’s point of view (Mitchel, Agle & Wood, 1997). The point of view in our study is more of a general view. We are going to be evaluating the stakeholders based on whether they contribute negatively, positively or neutrally to the ecosystem as, e.g. TPSs associated with malware would be seen contributing negatively, whereas experts of tracking would be contributing more positively.

We therefore draw on Scholl (1970) as the article provides an overview of applying stakeholder theory to public sectors and hereunder the e-government. The public sector of today is more of a multi-jurisdictional and multi-sector endeavor, meaning that public-private collaboration could lead to different governance issues (Scholl, 1970). We therefore draw on a combination of Mitchell et al.,

(1997)’s concept of stakeholder identification, i.e. power, legitimacy and urgency and on Blair &

Whitehead’s (1988) diagnostic topology of a stakeholder’s potential for collaboration vs. potential for threat. This theoretical combination is according to Scholl (1970) an optimal solution for public sector stakeholder analysis. Power should be understood as the power of influencing towards an objective and according to Mitchell et al., (1997) allows for three different kinds of power, i.e. political power, resource power, and normative power. Legitimacy should be understood as actions being appropriate within the accepted system. Legitimacy in our case means actions being appropriate to the protection of the individual. Urgency should be understood as the urgency for attention, i.e. time sensitivity and criticality (Mitchell et al., 1997). The diagnostic topology also takes relative power and resources into consideration and the stakeholder’s ability to either threaten or cooperate.

We are therefore drawing on the theories described above, hereby looking at the different stakeholders of the TPT ecosystem through the above described attributes and in relation to each other. We are going to be analyzing the following stakeholders, as these are the once we found interesting throughout our analysis: