Technology is not enough

“[A] technologically highly advanced society, containing many complex structures, some of them far more intricate and intelligent than anything that exists on the planet today—a society which nevertheless lacks any type of being that is conscious or whose welfare has moral significance [would be] an uninhabited society. It would be a society of economic miracles and technological awesomeness, with nobody there to benefit. A Disneyland without children.”

Source: Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

Data as an asset

Where data are controlled by a company as a result of past events, and this right that has the potential to produce economic benefits, the data is an asset of the company.

Since rights having the potential to produce economic benefits are not only rights over physical objects or rights to use intellectual property but ones taking many forms.

While producing economic benefits is not to be certain but possible beyond its availability to all others around.

Source: Conceptual Framework for Financial Reporting

Public officials on data ownership

“In Germany, the ministry of transport and digitalization defines the ownership of data created by automobiles as follows:

The right of disposal shall be allocated to the data supplier. In principle this means: Data and the attributed rights belong to persons—in the case of vehicle data, to the registered keeper respectively owner of the car.

Source: Ritter J. and Mayer A. Regulating data as property: a new construct for moving forward. Duke Law & Technology Review. 2018. No 16. P. 220–277.

https://www.youtube.com/watch?v=uP2Y6J0N_BM by
SAP CIS

Data Being

“‘When does data begin to exist?’

[Data] becomes real the moment it is recorded by electronic or digital means. At that point in time, something tangible exists that is new and different from the preceding moment in time.

Data creation occurs through on of two methods — either a human user inputs instructions to create a data asset (such as pressure on a keyboard creating [letters] in a digital format) or a machine executes a process that records new data of various classifications.”

Source: Ritter J. and Mayer A. Regulating data as property: a new construct for moving forward. Duke Law & Technology Review. 2018. No 16. P. 220–277.

Car owner is data owner

“This vehicle is equipped with one or more devices commonly referred to as event data recorders. These devices record [data]. This data belongs to the vehicle owner and may not be accessed by anyone else except as legally required or with the permission of the vehicle owner.”

Source: 2008 Honda Pilot Manual

Why regulating data as property

“[Advances] in scientific research, quantum mechanics, and quantum computing which confirm that information an any digital or electronic medium is, and always has been, physical, tangible matter.

[Being] an asset that is created, manufactured, processed, stored, transferred, licensed, sold, and stolen [data has become a new kind of property].

[Following] the scientific consensus that digital information is not intangible, but is physical, tangible matter [governance of data] will be best achieved by leveraging existing legal systems that govern the ownership, use, and transactions of the physical assets.

[A property rules construct proposes that] a right to own digital information arises upon creation (whether by keystroke or machine)”

Source: Ritter J. and Mayer A. Regulating data as property: a new construct for moving forward. Duke Law & Technology Review. 2018. No 16. P. 220–277.

Data quality is context dependent

“The information that can be extracted from data depends on the quality of the data. Poor-quality data will therefore almost always lead to poor results (‘garbage in, garbage out’).

[Information] is context dependent, and as a result data quality will typically depend on the intended use of the data: data that are of good quality for certain applications can thus be of poor quality for other applications (Lohr, 2014).”

Source: OECD (2015), Data-Driven Innovation: Big Data for Growth and Well-Being, OECD Publishing, Paris.

Data-driven decision making responsibility

“The use of data and analytics does not come without limitations […]. There are considerable risks that the underlying data and analytic algorithms could lead to unexpected false results. […]

Users should be aware of these limitations; otherwise they may (unintentionally) cause social and economic harm (costs), to themselves as well as to third parties.

The risk of social and economic costs to third parties (including individuals) raises important questions related to the attribution of responsibility for inappropriate decisions.”

Source: OECD (2015), Data-Driven Innovation: Big Data for Growth and Well-Being, OECD Publishing, Paris.

Decision-making process while using data analytics

Data-driven decision making it its extreme

“Decision makers do not necessarily need to understand the phenomenon before they act on it.

In other words: first comes the analytical fact, then the action, and last, if at all, the understanding.

For example, [a retail company] may change the product placement in its stores based on correlations without the need to know why the change will have a positive impact on its revenue.

As Anderson (2008) explains: ‘Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity.’”

Source: OECD (2015), Data-Driven Innovation: Big Data for Growth and Well-Being, OECD Publishing, Paris.

If something is free then what is the product?

The question is rephrasing of ‘if something is free, you are the product’ statement. And the answer can be extracting from the following:

“The existence of a free good signals that there is a companion good [across the multi-sided market], that firms consider both products simultaneously in maximizing profit, and that commonly used methods of [analysis] probably need to be adjusted to properly analyze two inextricably linked products. (Evans, 2011)”

Source: OECD (2015), Data-Driven Innovation: Big Data for Growth and Well-Being, OECD Publishing, Paris.

Artem Taranowski

A lawyer. Focusing on data from the legal point of view in the context of big data. Still crazy about doing legal analysis.

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