The wisdom nexus: Guiding information systems research, practice, and education

Ethical Dilemmas and Big Data

Using big data in organizations has the potential to improve innovation, accuracy, and efficiency. Big data is also connected with risks for both the organization and society at large. It is therefore vital to improve our understanding of the potential consequences of implementing and using big data. The researchers studied the Swedish Transport Administration to understand their attitude towards implementing big data to predict, for example, the need for road maintenance. The analysis identified four moral dilemmas that the organization deals with in connection to big data. The researchers discuss these dilemmas from the perspective of practical wisdom. Practical wisdom is manifested in context-dependent actions connected to open-mindedness, reflection and judgment. It can be summed up as “the reasonable thing to do” in a unique situation where “not-knowing” is a helpful resource when making wise decisions. This paper seeks to shed light on the importance of practical wisdom when implementing big data.

From data mining to wisdom mining

The knowledge gained from data mining is highly dependent on the experience of an expert for further analysis to increase effectiveness and wise decision-making. This mined knowledge requires actionability enhancement before it can be applied to real-world problems. The literature highlights the reasons that emerged the need to incorporate human wisdom in decision-making for complex problems. To solve this problem, a domain called ‘Wisdom Mining’ is recommended, proposing a set of algorithms parallel to the algorithms proposed by the data mining. In wisdom mining, a process to extract wisdom needs to be defined with less influence from an expert. This review proposed improvements to data mining techniques and their applications in the real world and emphasised the need to seek ways to harness wisdom from data. This study covers the diverse definitions and different perspectives of wisdom within philosophy, psychology, management and computer science. This comprehensive literature review served as a foundation for constructing a wise decision framework that aided in identifying the wisdom factors like context, utility, location and time. The inclusion of these wisdom factors in existing data mining algorithms makes the transition from data mining to wisdom mining possible. This research includes the relationship between these two mining process that facilitated further elucidation of the wisdom mining process. Potential research trends in the domain are also seen as a potential endeavour to improve the analysis and use of data.