Evaluating the EC Private Data Sharing Principles: Setting a Mantra for Artificial Intelligence Nirvana?

Author:Begoña Gonzalez Otero
Position:In-house Consultant at Latin America IPR SME Helpdesk; bgotero@gmail.com.
Pages:65-83
SUMMARY

On April 25, 2018, the European Commission (EC) published a series of communications related to data trading and artificial intelligence. One of them called “Towards a Common European Data Space”, came with a working document: “Guidance on Sharing Private Sector Data in the European Data Economy”. Both the Communication and the guidance introduce two different sets of general principles... (see full summary)

 
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Evaluating the EC Private Data Sharing Principles
2019
65
1
Evaluating the EC Private Data
Sharing Principles
Setting a Mantra for Artificial Intelligence Nirvana?
by Begoña Gonzalez Otero*
© 2019 Begoña Gonzalez Otero
Everybody may disseminate this ar ticle by electronic m eans and make it available for downloa d under the terms and
conditions of the Digital P eer Publishing Licence (DPPL). A copy of the license text may be obtain ed at http://nbn-resolving.
de/urn:nbn:de:0009-dppl-v3-en8.
Recommended citation: Be goña Gonzalez Otero, Evaluating the EC Pr ivate Data Sharing Principles: S etting a Mantra for
Artificial Intelli gence Nirvana?, 10 (2019) JIPITEC 65 para 1.
Keywords: Artificial intelligence; best practices; data access; data re-use; data sharing; standard contract terms;
the internet of things; self-regulation
artificial intelligence development. This article fo-
cuses on the first action, the “Guidance on Sharing
Private Sector Data in the European Economy”. First,
because it is one of its kind. Second, although these
principles do not qualify as soft law (lacking bind-
ing force but having legal effects) the Commission’s
communications set action plans for future legisla-
tion. Third, because the ultimate goal of these prin-
ciples is to boost European artificial intelligence (AI)
development. However, do these principles set a vi-
able legal framework for data sharing, or is this pub-
lic policy tool merely a naïve expectation? Moreover,
would these principles set a successful path toward
a thriving European AI advancement? In this contri-
bution, I try to sketch some answers to these and re-
lated questions.
Abstract: On April 25, 2018, the European
Commission (EC) published a series of communica-
tions related to data trading and artificial intelligence.
One of them called “Towards a Common European
Data Space”, came with a working document: “Guid-
ance on Sharing Private Sector Data in the European
Data Economy”. Both the Communication and the
guidance introduce two different sets of general prin-
ciples addressing data sharing, contractual best prac-
tices for business-to-business (B2B), and business-
to-government (B2G) environments. On the same
day, the EC also published a legislative proposal to re-
view the Public Sector (PSI) Directive. These two si-
multaneous actions are part of a major package of
measures, which aim to facilitate the creation of a
common data space in the EU and foster European
A. Introduction
1
On April 25, 2018, the European Commission (EC)
published a series of communications related to data
trading and articial intelligence. One of them called
“Towards a Common European Data Space”,1 came
with a working document: “Guidance on Sharing
* In-house Consultant at Latin America IPR SME Helpdesk;
bgotero@gmail.com.
1 Commission, “Towards a Common European Data Space”
(Communication) COM (2018) 232 nal.
Private Sector Data in the European Data Economy”.
2
Both the Communication and the guidance introduce
two different sets of general principles addressing
data sharing contractual best practices for business-
to-business (B2B) and for business-to-government
(B2G) environments. On the same day, the EC also
published a legislative proposal to review the Public
Sector (PSI) Directive.3 These two simultaneous
2 Commission, “Guidance on Sharing Private Sector Data in
the European Data Economy” (Staff Working Document)
SWD (2018) 125 nal.
3 See the announcement at <https://ec.europa.eu/digital-
single-market/en/proposal-revision-public-sector-
information-psi-directive> (accessed on October 15, 2018).
2019
Begoña Gonzalez Otero
66
1
actions are part of a major package of measures
aiming to facilitate the creation of a common
data space in the EU and foster European articial
intelligence technologies’ development.
2
This article focuses on the rst action, the “Guidance
on Sharing Private Sector Data in the European
Economy”. First, because it is one of its kind. So far,
the discussion on data sharing in Europe has been less
intense than for data transfer; perhaps because the
legal basis for a transfer can be a sale, lease, rental,
while a data sharing legal basis is more intricate,
as we are looking at network structures and co-
operation. Second, although these principles do not
qualify as soft law (lacking binding force but having
legal effects) the Commission’s communications set
action plans for future legislation. Third, because the
ultimate goal of these principles is to boost European
articial intelligence (AI) development. However,
do these principles set a viable legal framework for
data sharing, or is this public policy tool merely a
naïve expectation? Moreover, would these principles
set a successful path toward a thriving European AI
advancement? In this contribution, I try to sketch
some answers to these and related questions.
3 It is crucial to mention that EC private data sharing
principles evaluation has clear connections to the
data ownership debate.4 This paper will neither
re-examine this aspect nor the introduction of
other possible doctrines,5 nor review any other
ramications, such as the right to information
privacy and personal data protection.
6
Finally, the
assessment of these principles will also stay away
from specic consumer law issues related to the use
of personal data, including “counter performance”
4 For an overview on the data “ownership” debate see: T.
Hoeren, “A New Approach to Data Property?” (2018) 2018/2
AMI p. 58-60 <https://www.ami-online.nl/art/3618/a-
new-approach-to-data-property> (accessed on October 15,
2018); B. Hugenholtz, “Data property: Unwelcome guest in
the Houes of IP”, 2018 <https://www.ivir.nl/publicaties/
download/Data_property_Muenster.pdf> (accessed on
October 15, 2018); J. Drexl, “Designing Competitive Markets
for Industrial Data - Between Propertisation and Access”
(2017) 8(4) JIPITEC p. 257; H. Zech, “A Legal Framework for a
Data Economy in the European Digital Single Market: Rights
to Use Data” (2016) 11 Journal of Intellectual Property Law
& Practice, p. 460-470.
5 For an overview see: M. Dorner, “Big Data und
Dateneingentum” (2014) Computer und Recht, p. 617-628;
Osborne Clarke LLP, Legal Study on Ownership and Access to
Data (2016) Study prepared for the European Commission
DG Communications Networks, Content & Technology
<https://publications.europa.eu/en/publication-detail/-/
publication/d0bec895-b603-11e6-9e3c-01aa75ed71a1/
language-en> (accessed on October 15, 2018).
6 See N. Purtova, “Do property rights in personal data make
sense after the Big Data turn? Individual control and
transparency”, (2017) 10(2) Journal of Law and Economic
Regulation November; Tilburg Law School Research
Paper No. 2017/21 <https://ssrn.com/abstract=3070228>
(accessed on October 15, 2018).
as proposed in the Digital Content Directive.7
4 This contribution is structured as follows: the rst
part will present the problems at stake: what is
the current state of AI development in Europe, the
availability of data for AI and the Internet of Things
(IoT) research and development, and the current
legal framework of data trading. The second part will
evaluate the principles from an overall perspective
focusing on their underlying goals. The evaluation
will be addressed separately: rst, the principles for
business-to-business (B2B); and next, the principles
for business-to-government (B2G) data trading
will be considered. Last, the paper will conclude
by answering the question of whether this public
policy tool is merely an unrealistic expectation or
whether it sets a favorable regulatory approach for
a successful development of AI enabled technologies
in the single market.
B. The Problems at Stake
I. The Status Quo of AI
Development in Europe
5 Investment in articial intelligence (AI) has rapidly
increased in the last ve years at the international
level. According to a study presented in early 2018,
which used basic research and market capitalization
to track where AI is done, China leads the former
statistic, with the U.S. behind and long followed by
the UK, Germany, France and Italy.8 When looking
at market capitalization, the rst four largest public
companies with AI exposure are Apple, closely
followed by Alphabet, Microsoft and Amazon,9 all of
which are headquartered outside Europe yet running
business in the single market. Then, why is Europe
behind the US and China with regards to capturing
the opportunities of articial intelligence?10
7 Proposal for a Directive of the European Parliament and of
the Council on Certain Aspects Concerning Contracts for
the Supply of Digital Content, COM (2015) 634 nal; see A.
Metzger, “Data as Counter-Performance – What Rights and
Duties do Parties Have?” (2017) 8(2) JIPITEC p. 2; A. Metzger,
Z. Efroni, L. Mischau, J. Metzger, “Data-Related Aspects of
the Digital Content Directive” (2018) 9(1) JIPITEC p. 1.
8 A. Goldfarb, D. Treer, “AI and International Trade” (2018)
National Bureau of Economic Research, Working Paper
24254, <http://www.nber.or/papers/w24254> (accessed on
October 15, 2018), p. 2.
9 Ibid. p. 3.
10 See J. Manyika, “10 imperatives for Europe in the age of AI
and automation” (2017) Report McKinsey Globarl Institute,
October 2017 <https://www.mckinsey.com/featured-
insights/europe/ten-imperatives-for-europe-in-the-age-
of-ai-and-automation> (accessed on October 15, 2018).

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