Data, AI, and the Expendability of Privacy

As is the case with  most calls to innovation in western societies, the main driver behind the growth and development of the open market is the private sector, regardless of legislation or regulation introduced by parliament or government.

To do this, companies throughout the world continuously strive to learn more and more about the people that pay for their product, or even those that may potentially do so in the future. Whereas in the past one had people whose job it was to gather information and collate it in a way that can be used by the company, modern advancements in artificial intelligence and big data mean that millions of variables from an even larger sample of people can be stored, processed and exploited to appeal to an ever-growing number of citizens in an increasingly competitive market.

As time goes by, the privacy debate finds itself shifting into an increasingly internet-centric area. The reason is simple enough – in the past most of the information we shared about ourselves was because of government-related documents and interpersonal relationships, with most marketing and advertising methods being one-way, flowing to the consumer. Nowadays in contrast, all that has been devoured by the internet, which is what has brought about a two-way age where data is much more easily accessible and in significantly larger amounts. This age is aptly named The Information Age. To this end, we ask, does one have the right to make use of your data for one’s profit? If so, until what point can one do so? Is it even considered a breach of the individual’s privacy, hence giving said individual the right to oppose the data harvesting concerning him/her?

Every day, an incalculable amount of individuals make use of services and buy objects or commodities. In simple terms, people constantly spend money. Of course, we spend money according to their prices, so the price of what one buys determines how much money one must spend to acquire it. From the  capitalistic perspective, one has relative control over the prices that consumers face. That is, naturally, assuming that the consumer is an anonymous individual and that, while all consumers are heterogeneous in nature, the capitalist commands a monopoly over what is being consumed, so that the only determiner of the price is that which results in the highest profit.

So, what if one could remove the barrier of anonymity, and identify those consumers who have consumed in the past, and price discriminate to both develop new ways of attracting consumers, and of retaining them?  Whatif one could go further than simply identifying a consumer, and also learn that individual’s tendencies or preferences as a customer, and pushing said preferences towards them so that one can take as much money spent from the person as possible?

Firms can do all of this. The more time passes, the more they increase their ability to automate, collate and collect information. Perfect examples of companies that have exploited this most effectively are the likes of Google, Capital One etc, all of which have seen vast amounts of profit simply based on their ability to process consumer information to improve their product.[1]

First, it would be useful to delve into how information is currently harvested from individuals through the open market, its path to becoming data, and how that is used to profit the provider. Of course, before continuing, it should be noted that the aim here is not to put the system of capitalism itself in a negative, expository light. It is to describe how it works, often with your consent, and the implications it has on our idea of privacy.

Largely, information harvesting is regulated by the EU’s Data Protection Directive (95/46/EC) and Privacy and Electronic Communications Directive ((2002/58/EC), amended by (2009/135/EC)). Proof of how Malta specifically legislates in a way that respects the mentioned directive are provisions (Ex. Clause 8D(e) of the Electronic Commerce Act) which enforce the General Data Protection Regulation (EU) 2016/679 (an act superseding directive (95/46/EC)) against any potential violations implied by any part of the act. Their effectiveness is another question for another investigation.

As was mentioned earlier, we are currently experiencing the information age. As such, our economies are based on information.[2] Now, this may seem obvious and self-explanatory, but the reality is that it conceals a  operational system that one might not find apparent through the superficial term, ‘information economy’.

The  operational system mentioned is that by which the capitalist harvests data from its “farm” of individuals, to discriminate the aforementioned individuals and extract as much out of them as possible, mostly in the form of money, naturally. That very metaphor is what highlights the problem with the common presentation of modern capitalism as one which aims to best suit the consumer. This is because that declaration is based on the assumption that data is being gathered to achieve the best result for the consumer.

That said, when you take the activity in itself, you’re left with the reality that the capitalist acts as the “farmer” who harvests data from his sample of individuals and either sell that data for profit or uses that data to garner a yield from his sample that is more vast, with a better result for the same individuals being merely a by-product of that activity. The danger here is that while the farmer profits by harvesting yield from crops that are his own, that would mean that the data being harvested for profit by the same capitalist, is his property, which it naturally is not.

This line of thought leads us to ask two questions; Why is permission not asked before harvesting information, and even if permission is asked, why is the individual not repaid for that which is his own? Those questions, especially the latter, can be seen as branches into another three questions; Is the information you provide your own, to what extent is it your own, and what type of relationship does giving permission for one to make use of your information, provide?

It is noteworthy that collecting and processing data has been part of humanity’s arsenal of innovation since the early days of civilisation. Looking back at the Hellenistic period one will find the revolutionary  invention referred to as the Antikythera Mechanism.[3] The Antikythera mechanism was a mechanically powered ‘clock’, so to speak, which consisted of “two concentric scales representing the zodiac, divided into 12 zodiacal signs totalling 360 degrees, and the Egyptian calendar, divided into 365 days. A single pointer then, which revolved once in a solar year, is likely to have indicated both the day in the Egyptian year and the place of the sun in the zodiac”.[4]

Now what’s interesting about this is that although several historians have linked it to simply an attempt to mathematically demonstrate an (astronomical) argument, those specialising in technology point out the fact that, if this mechanism were to be considered as an ‘analogue computer’, then that would mean that what we think of as the analogue-digital demarcation of the post-1940s has its beginnings placed within the second century BC.[5] This would prove in some ways humanity’s never-ending mission to use computer processing to gather data.

Just as this mechanism was used to predict astronomical positions and eclipses for astrological purposes, personal data is used to predict expenditure for economic purposes. This is done by gathering all sorts of data, from one’s health records, social security numbers, social media posts, location history, query-based search engine results, to banking details and even cursor movements or the way you swipe through your phone.[6]

Of course, this is often done entirely with your consent, but the details of what you have consented to are often smothered in lengthy service agreements. What may come to mind when reading this is companies which offer their services for free, in return for your permission to gather and monetise your data. In other words, the price we mentioned earlier, is your data.

But here we are discussing another type of relationship, one that most of the time happens after your data has been collected (be it by services, applications, stores, businesses etc). This involves those businesses whose sole purpose is to amass data about all the behaviours and sources of information of millions of individuals, and re-selling that to the very companies that collected some of it so that they can form the aforementioned tailored strategies. How then can we begin to address the question of what can be done to protect one’s privacy in the environment we have just described?

Of course an option, probably at the extremely conservative end of the argument, would be to impose and enforce blanket anonymity for all consumers, fighting against the data world (that is, of course, assuming that considering an end to the internet economy for the sake of protecting individual privacy, is out of reach).[7] In their study, Conitzer, Taylor and Wagman, find that when the consumer is allowed to anonymise freely, the grand majority if not all individuals would choose to do so.[8] The peculiar thing about this is that it seems to be the option that also results in the highest profit for the provider.[9]

That said, peculiar as it may be, it is also understandable, in the sense that it breaks a law of Physics, in some ways <this sentence needs to be reworded. Almost every law of Physics ends with the assumption that no external forces are applied. In fact, free choice of anonymity introduces a gargantuan external force into the theory that more data equals more ability to coerce,( and therefore more profit),. That external force is trust.[10][11] A downside to extensive personal data collection is that trust decreases and so the consumer has a lower probability of spending. Whereas, with the option of free anonymity, the consumer has much higher trust, and is hence significantly more likely to spend, even enough to outweigh the previously mentioned strategy. This is a major cause for the several offers and premiums one is used to seeing, whereby that lack of trust is countered by temporarily lower prices.[12]

So why doesn’t each company simply offer free anonymity? Well, it, as we said in the beginning, assumes that one occupies a monopoly. In a competitive market, data will eventually propel the competition further.[13] Then, of course, we are forgetting to mention the strategic consumer, who will exploit corporate strategies to predict pricing patterns, and only make purchases when prices are lowered. This returns the firm to a negative consequence, much like price discrimination did.

Till now, if we split the field into consumer vs capitalist, we find that in an ideal world, free anonymity would be best for the capitalist (although due to the aforementioned? hierarchy, not necessarily the best for all consumers) and society in general. And here is the culmination of why I chose to refer to this study[14] as a principal foundation in this article (as opposed to older, more established articles like Acquisti and Varian,[15] collectively including principles from Fudenberg and Villas-Boas,[16] Farr et al[17] and Armstrong et al,[18] which were used as more of consultancy sources). This choice was taken because we can see a striking difference to past literature where privacy is a beneficial element to profit rather than a hindrance and where anonymisation benefits both parties.  But of course, it would be dangerous to assume this to be true, neglecting all other studies which we mentioned. I think this last bit also needs a rewrite

  To this end, it is evident that the avenues open to us are plentiful in number and vast in width for the most part. Unfortunately, an article such as this one can only go so far as to briefly mention them along with their repercussions. On the one hand, data harvesting may hold the key to unlocking some of humanity’s deepest mysteries by delving into our conceptions of reality through embracing the long-term tool of powerful social science, a power described best by Seth Stephens-Davidowitz in his book, ‘Everybody lies’.[19]

On the other hand, one must first understand the side-effects of uncovering said secrets, namely, the realisation that the invisible constructs of all facets of society and psyche are what makes people, individuals. Therefore,  if in understanding the individual, one ends up risking losing the same individuality, is it worth it?

What one can do is attempt an outlining as to where we ought to go. For this, arguably one of the most moderately balanced sets of guidelines is the 1980 OECD Guidelines on the protection of Privacy and Transborder Flows of Personal Data, along with their updated version, so much so that they laid the foundations for the European Data Protection Directive (Directive 95/46/EC).

The general path forward is provoked (what?), that regulation is not there to liberalise or to restrict, but to introduce and ensure transparency, clearly evident in the European Cookie tracking regulation (2009/135/EC), so that whatever process decided by national legislation, provides the consumer with the power of consent, the clear knowledge as to what they are consenting to, and the continuous control over the data they consented to be used.

[1] James Campbell,  Avi Goldfarb,  Catherine Tucker, ‘Privacy Regulation and Market Structure’ (2015) Volume 24 Journal of Economics & Management Strategy 1. Introduction Par 1.

[2] Vincent Conitzer, Curtis R. Taylor and Liad Wagman, ‘Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases’ (2012) Volume 31 Marketing Science 277 1. Par 1.

[3] Konstantina Dritsa, Dimitris Mitropoulos,, Diomidis Spinellis, ‘Aspects of the History of Computing in Modern Greece’ Volume 40 IEEE Annals of the History of Computing Par 2.

[4] James Evans & Christián C. Carman, ‘Babylonian Solar Theory on the Antikythera Mechanism’ Archive for History of Exact Sciences Introduction Par 1.

[5] Konstantina Dritsa, Dimitris Mitropoulos,, Diomidis Spinellis (n 3).

[6] Louise Matsakis, ‘The WIRED Guide to Your Personal Data’ (WIRED) <;.

[7] Vincent Conitzer, Curtis R. Taylor and Liad Wagman, ‘Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases’ (2012) Volume 31 Marketing Science 278 Par 7.

[8] Vincent Conitzer, Curtis R. Taylor and Liad Wagman, ‘Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases’ (2012) Volume 31 Marketing Science 278 Par 5.

[9] J. Miguel Villas-Boas, ‘Consumer Learning, Brand Loyalty, and Competition’ (2004) Vol. 23 Marketing Science pp. 134.

[10] R. H. Coase, ‘Industrial Organization: A Proposal for Research’ (1972) 3, Policy Issues and Research Opportunities in Industrial Organization Economic Research: Retrospect and Prospect 59.

[11] SonjaGrabner-Kräutera, Ewald A.Kaluscha, ‘Empirical Research in On-Line Trust: A Review and Critical Assessment’ (2003) 58 International Journal of Human-Computer Studies 783.

[12] Vincent Conitzer, Curtis R. Taylor and Liad Wagman, ‘Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases’ (2012) Volume 31 Marketing Science 278 Par 6.

[13] PatrickMcColea, ElaineRamsey, JohnWilliams, ‘Trust Considerations on Attitudes towards Online Purchasing: The Moderating Effect of Privacy and Security Concerns’ (2010) 63 Journal of Business Research 1018.

[14] Vincent Conitzer, Curtis R. Taylor and Liad Wagman, ‘Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases’ (2012) Volume 31 Marketing Science 277.

[15] Alessandro Acquisti and Hal R. Varian, ‘Conditioning Prices on Purchase History’ (2005) 24 Marketing Science 367.

[16] Fudenberg, D. and J.M. Villas‐Boas, ‘Behavior Based Price Discrimination and Customer Recognition’ 1 Handbooks in Information Systems 377.

[17] Farr, S.J., C. Horton Tremblay, and V.J. Tremblay, ‘The Welfare Effect of Advertising Restrictions in the U.S. Cigarette Industry’ 18 Review of Industrial Organization 147.

[18] Armstrong, M., J. Vickers, and J. Zhou, ‘Consumer Protection and the Incentive to Become Informed’ 7 Journal of the European Economic Association 399.

[19] Seth Stephens-Davidowitz, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are.


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