What is obtrusive analytics

We keep hearing that analytics is going to change the world in a big way and in fact it is already affecting firms and organisations in a way that could not have been visualised earlier.  What is increasingly becoming prominent is that today is not the world where knowledge laden information can be stored free.
There is a serious cost of storing any information in any data repository so as to provide you some beneficial services for free. So often to many social scientists the bigger question comes as where does privacy and personal data gets compromised. Is my security of my identity getting affected in anyway? How is all the data and information captured about me getting really used by your organisation which is capturing my data and more importantly shared with other organisations who may also be using my data and information with or without my knowledge and sometimes even not delivering me any benefit but creating a nuisance value for me.
This is where the multidimensional nature of privacy issues comes into the picture where the data been captured  maybe reveal highly sensitive and personal information about me. Does this analysis also captured information about me anything different entities that may have been capturing information about me and integrating the news and views to give a 360 degree version of me which may or may not be the right view.

The execution of analytical systems need more and more to assure the user that details about an individual is being anonymized to an extend that individual privacy and security is not compromised under any circumstances. The week it is been shared needs to also be controlled. If it is been shared with other organisations before sharing permission is needed to be taken explicitly from the user in a way that user explicitly understands for what purpose the permission is being requested and for what purpose the information will be shared and what will be the outcome of sharing information.

Some European regulations do try to ensure these policies being implemented. However in many developing and emerging economies such policies are not in place which will protect and individuals’ privacy and security concerns. Audits are needed to ensure that the needs of the people are getting captured, in a way that is consistent with the Expectations.

Policies of information management and analytics of personal data has to be unobtrusive. Period. There can be no second thoughts about that data and information use should be used as it is desired by the people and expected by the people when the information is getting captured. Anonymity of the data would be of prime concern under such a circumstance. Obtrusive relationships if captured should request permission from the user before reporting it for further usage by organisations especially if it is being captured by private organisations and different organisations which may have different profit motive.

With the Internet of things coming in a big way such data capture would be synchronous,  continuous, and often without the knowledge of the individual. Such Smart Technologies need to communicate more with you say how the data is going to be captured and how the data is going to be converted into meaningful information. Social scientists need to investigate more into this paradigm of problems which will be initiated by the implementation of millions of sensors and billions of smart devices connected to each other sharing information about all activities including that of individuals which may or may not include personalize data. Use of personalized data in fact needs to be carefully monitor under such a system of connected devices and smart sensors. Social rules rather than business rules needs to govern how the information is being captured and analysed from these devices and How such information will be shared and reported to other organisations for the delivery of services and facilitating public administration.

So what you think of these Technologies which are going to come in a big way implementing Analytics as well as Big Data Analytics collecting information from sensors without really asking for your permission individually. Do let us know your thoughts on the subject.

Key References

  1. Tene, Omer, and Jules Polonetsky. “Big data for all: Privacy and user control in the age of analytics.” Nw. J. Tech. & Intell. Prop. 11 (2012): xxvii.
  2. Badii, Atta, et al. “Visual context identification for privacy-respecting video analytics.” Multimedia Signal Processing (MMSP), 2012 IEEE 14th International Workshop on. IEEE, 2012.
  3. Zheleva, Elena, and Lise Getoor. “Privacy in social networks: A survey.” Social network data analytics. Springer US, 2011. 277-306.
  4. Kar, A. K. “Using Fuzzy Neural Networks and Analytic Hierarchy Process for supplier classification in e-procurement.” Working Papers on Information Systems (2009): 9-23.

  5. Heath, Jennifer. “Contemporary privacy theory contributions to learning analytics.” test 1.1 (2014): 140-149.
  6. Kar, A. K., and A. Rakshit. “Pricing of Cloud IaaS Based on Feature Prioritization-A Value Based Approach.” Recent Advances in Intelligent Informatics. Springer International Publishing, 2014. 321-330.
  7. Thomas, James J., and Kristin A. Cook. “A visual analytics agenda.” Computer Graphics and Applications, IEEE 26.1 (2006): 10-13.
  8. Cardenas, Alvaro A., Pratyusa K. Manadhata, and Sreeranga P. Rajan. “Big data analytics for security.” IEEE Security & Privacy 6 (2013): 74-76.
  9. Kar, A. K., A. Kumar Pani, and S. Kumar De. “A study on using business intelligence for improving marketing efforts.” Business Intelligence Journal 3.2 (2010): 141-150.
  10. Jensen, Meiko. “Challenges of privacy protection in big data analytics.” Proceedings-2013 Ieee International Congress on Big Data, Bigdata 2013. IEEE, 2013.
  11. Kar, A. K. “A Decision Support System for Website Selection for Internet Based Advertising and Promotions.” Emerging Trends in Computing and Communication. Springer India, 2014. 453-457.
  12. Tene, Omer, and Jules Polonetsky. “Privacy in the age of big data: a time for big decisions.” Stanford Law Review Online 64 (2012): 63.
  13. Bose, Ranjit. “Advanced analytics: opportunities and challenges.” Industrial Management & Data Systems 109.2 (2009): 155-172.
  14. Kar, A. K., and Priyal Singh. “A conceptual model to cross sell value added services in telecom industry.” Proceedings of the International Conference on Technology and Management, Hyderabad, India. 2011.
  15. Moore, Barrington. “48. Privacy: Studies in Social and Cultural History.” (2016).
  16. Andrienko, Gennady, and Natalia Andrienko. Privacy issues in geospatial visual analytics. Springer Berlin Heidelberg, 2012.
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