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Almost everyone has at least once experienced the situation in which a website asked a question along the following line: “do you allow us to store your information”. People then choose either to accept or decline this request. Personally, I mostly accept, although I am not sure why.  However, I do see that my ads follow my browsing history. Therefore, I would like to show you how this collaboration between cookies and ads works.

The Nationale Omroep Stichting (NOS), the ‘Dutch BBC’, has made a graphical illustration of the process, which I will use to clarify the sequence of events. (Note: the numbers below do not correspond with the numbers in the NOS image).

1. You give permission to a website to extract the you leave on the website.
2. A data package with this information is made.
3. This bundle will travel to a so-called advertisement agency, which will sell it on the advertisement market.
4. Hundreds of bidders will place a bid on your information. The price is determined by supply and demand. Mostly the bidder with whom you match best, will win the action.
5. The winner’s advertisement (yellow line and building) then appears on your screen.

As shown above, your cookie information is sold on an online auction. Of course, there are billions of them and individually they are not significant. Still, I think that it is important to be aware of this phenomenon.

Interestingly, Google also has an opinion on this matter. They suggest that there is a win-win situation because you will see relevant advertisements and the ad will be given to the advertiser who values you the most. I think differently. First, I feel being spied as a search on my phone will result in the corresponding ads on my laptop a few seconds later. I understand the mechanics, but it just feels creepy. Secondly, Google (and other organizations) use you as product without paying for your ‘services’.  Compare it with Google entering your house, stealing your chairs and selling them. To make this even more awkward, all the time you were holding the door open for Google.

Although this example is a bit extreme, I wonder what your opinion is on this matter.

References

NOS. (2019). Zo ziet de veiling achter een cookiemelding eruit. [online] Available at: https://nos.nl/op3/artikel/2305556-zo-ziet-de-veiling-achter-een-cookiemelding-eruit.html [Accessed 10 Oct. 2019].

Support.google.com. (2019). About the ad auction – AdSense Help. [online] Available at: https://support.google.com/adsense/answer/160525?hl=en [Accessed 10 Oct. 2019

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According to Oracle, around the year 2005 people start noticing the amounts of data generated by Facebook and YouTube. Since then, the buzzword ‘big data’ had taken off. The on-going definition is still the one formulated by Gartner: “big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity”.

In many industries, this development has had an enormous impact. The healthcare industry was also promised benefits, however there is still no substantial value delivered by big data and its analytics (Dhindsa, Bhandari and Sonnadara, 2018). In this blog, the challenges of big data in the healthcare industry will be covered.

The big data is not a big as it seems

Even the largest publicly available data set of an intensive care unit, the Medical Information Mart for Intensive Care, has insufficient data according to Adibuzzaman et al. (2018). The authors explain that in medical research, clinical questions require such specific information from small cohorts in the data set, that they are mostly insufficient in providing statistical confidence.

Privacy

Although there could be willingness to analyze healthcare data, researchers are not always granted access to information easily because of the privacy sensitive nature of the data. Even if data is anonymized, “a query to find any patient who is of Indian origin and has some specific cancer diagnosis with a residential zip code 3-digit prefix ‘479’ may result in only one subject; thus exposing the identity of the individual” (Adibuzzaman et al 2018).

Acceptation

In other (mostly tech) industries, big data analytics is changing whole business models (BCG, 2019). However, due to the risk aversive nature of the healthcare industry, change is harder to achieve here. For example: the adoption of beta blockers to prevent hart failures took 25 years from the point that the research paper was published (Smith, 2013). Another factor is that many machine learning algorithms work as a ‘black box’, which further complicates acceptation as it is difficult to trace back the findings of big data analytics (Adibuzzaman et al., 2018).

The three issues mentioned above form a challenge for the healthcare industry in terms of its pursuit of big data analytics. Still, Adibuzzaman et al. (2018) conclude that if more institutions share complete, temporal and precise data, and if regulatory institutions find ways to overcome privacy and acceptation issues, then there will be a bright future for big data analytics in the healthcare industry.

 

References:

Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2018). Big data in healthcare – the promises, challenges and opportunities from a research perspective: A case study with a model database. AMIA … Annual Symposium proceedings. AMIA Symposium, 2017, 384–392.

BCG. (2019). [online] Available at: https://www.bcg.com/capabilities/big-data-advanced-analytics/transforming-business-models.aspx [Accessed 6 Oct. 2019].

Dhindsa, K., Bhandari, M. and Sonnadara, R. (2018). What’s holding up the big data revolution in healthcare?. BMJ, p.k5357.

Gartner IT Glossary. (2019). What Is Big Data? – Gartner IT Glossary – Big Data. [online] Available at: https://www.gartner.com/it-glossary/big-data [Accessed 6 Oct. 2019].

Oracle.com. (2019). What Is Big Data? | Oracle. [online] Available at: https://www.oracle.com/big-data/guide/what-is-big-data.html [Accessed 6 Oct. 2019].

Smith, M. (2013). Best care at lower cost. Washington, D.C.: National Academies Press.