Global Data Law
Aaron Perzanowski and Jason Schultz, The End of Ownership (2016), chapter 8: 'The
Internet of Things You Don't Own'. - ANS-The internet of things refers to a range of devices
that generally combine embedded software, network connectivity, microscopic sensors, and
large-scale data analytics. So many objects are now computers, e.g., phones, cars, light
bulbs, etc. and are therefore susceptible to external limitations and controls of other digital
goods. This has implications for ownership and consumer welfare (see example of smart
thermostat being discontinued, pp. 140-141).
Possible beginning of IoT → The iPhone as a walled garden approach - can only install
software Apple allows, can only configure settings Apple gives access too, etc. This sparked
a practice of jailbreaking to install software, replace operating system, and customize the
phone. In legal battle that followed, Apple argued that iPhone users are licensees, not
owners, of the OS. Copyright Office ruled in favor of right to jailbreak phones but
sidestepped the issue of ownership.
Farm example: Monsanto sold the herbicide Roundup, but this also damaged crops. They
manufactured crops resistant to roundup and "licensed [them] for a single season" to
farmers, so farmers couldn't replant the following year, instead they had to buy new seeds.
John Deere imposed a software layer between farmers and tractors in order to force farmers
to have equipment serviced by authorized John Deere dealers. John Deere claimed it owned
the code in tractors it sold to farmers and farmers had an implied license for the life of the
vehicle. This raises the price for farmers and also impacts innovation.
Modern cars (GM, Mercedes-Benz) : Also contains tools that weaken the property interests
of owners, including DRM that prevents repair and customization, soft- ware that monitors
and controls your driving, even restrictions on vehicle resale. Again argued that underlying
computer software was licensed
\Ada Lovelace Institute, Exploring legal mechanisms for data stewardship (March 2021), pp.
12-14 (overview), pp. 41-47 (data trusts), 54 (data cooperatives versus data commons),
60-66 (data cooperatives). - ANS-Data Trusts
What is the purpose of the trust and how is consent reached?
What is the role of the trustee?
How will they be monitored?
How will they be funded? Why will people choose to join them? Different answers to this will
determine which trusts become more popular and thus have more bargaining power.
How would organizations interact with trusts? Could they sponsor them?
,What is the difference between a data commons and a data cooperative? In the case of
data, the cooperative model would imply that data was brought to and withdrawn from the
cooperative as members joined and left. A data commons implies a body of data whose
growth or decline would be independent of the identity and number of stakeholders.
Aim of Data Cooperatives: e the
balance between 1) complete privacy and 2) the potential benefits to the individual from
collecting and processing personal data and communicating the insights to the individual,
and 3) in those individuals then being able to better influence the market and receive a better
division of the economic benefits (e.g. through selling the data and/or insights).
Challenges:
Uptake: resonance challenge, mobilisation challenge, trust challenge, capacity challenge
Advocates potentially using contentious situations to create specialized data trusts. E.g.,
outrage by gig economy workers to create a worker owned and controlled data set.
Scale:
democratic control and shared ownership conflict in terms of efficiency - may require a
constitution to smooth over disagreements.
Rights, accountability, and governance must be established.
Cooperatives don't lend themselves to outside sources of funding, so they may have to fall
back on internal funding. Without funding, they may find it difficult to recruit good
administrators, so will be forced to elect a board from the members.
\Alexandra Giannopoulou, Understanding Open Data Regulation: An Analysis of the
Licensing Landscape, in Open Data Exposed (Bastiaan van Loenen, Glenn
Vancauwenberghe, & Joep Crompvoets eds., 2018) - ANS-The Berne Convention Article 2.1
determines the definition of literary and artistic works, thus requiring that data must pass the
originality test to be copyrightable. Article 2.5 permits the copyrighting of collections of data
(also supported by the WIPO Copyright Treaty of 1996 and Article 1013 of the Agreement on
Trade Related Aspects of Intellectual Property Rights of 1994).
European Court of Justice: ""it is only through the choice, sequence and combination of
those words that the author may express his creativity in an original manner and achieve a
result which is an intellectual creation."
A sui generis database right exists in Europe, it gives the creator of the database 15 years
exclusive copyright in order to protect the economic investment put into creating the
database (NOT creating the data). Public databases are theoretically also covered, but some
courts have ruled against them.
Transnational Open Data Licensing Models:
,Creative Commons: American NGO that has created a set of free, easy to use copyright
licenses. All licenses are based on four elements: Attribution (BY) (requires licensee to
indicate the name of the author on every distribution), No derivatives (ND) (forbids altering
the licensed material), No commercial uses (NC) (forbids commercial use), and Share Alike
(SA) (allows derivatives but requires the derivative work to be licensed under the same type
of license as the original).
"The licenses exist in three different formats or "layers". The license is first delivered as a
summary of its core elements, called the commons deed or human readable license. Then,
the second layer is the legally binding license called the legal deed, and third is the
machine-readable license, which describes the permissions and restrictions of the license in
a form of digital-rights expression making it easier
\ALI-ELI principles for a Data Economy - Data Transactions and Data Rights, pages
124-128; 156-158; 162-165; 166-170. - ANS-See article for US and EU cases/examples of
each principle.
Principle 16: Data rights. Data is a non-rivalrous resource, and data rights are not tied to
ownership or property principles.
Principle 21: Desistance from data activities with regard to co-generated data. A party should
have the right to demand a data controller desist use of and/or delete data, if the data could
reasonably cause harm to the party or if "the purpose of the data activities is inconsistent
with the way that party contributed to the generation of the data"
Principle 23: Economic share in profits derived from co-generated data. Parties usually are
not entitled to profits made from data except for when there is a contract or agreement for
the sharing of said profits, UNLESS: "(a) that party's contribution to the generation of the
data (i) was sufficiently unique that it cannot, from an economic point of view, be substituted
by contributions of other parties; or (ii) caused that party significant effort or expense; and (b)
profits derived by the controller are exceptionally high; and (c) the party seeking an
economic share was, when its contribution to the generation of the data was made, not in a
position to bargain effectively for remuneration."
"Principle 24: Justification for data rights and obligations (1) The law should afford data rights
for the public interest, and for similar reasons independent of the share that the party to
whom the rights are afforded had in the generation of the data, only if the encroachment on
the controller's or any third party's legitimate interests is necessary, suitable and
proportionate to the public interest pursued."
\ALI-ELI principles for a Data Economy - Data Transactions and Data Rights, Part II, Chapter
B (Contracts for Supply or Sharing of Data) - ANS-Provides default rules for Contracts for
Supply or Sharing of Data.
Principle 7: Contracts for transfer of data
What is it? Supplier undertakes to put the recipient in control of particular data by
transferring the data to a medium within the recipient's control.
Important terms? Access, Representations that Data Fits Purpose, Representations that
Supplier puts Recipient in Control of Data (over IP Claims, Non-IP Claims), Contract Term
Principle 8: Contracts for Simple Access to Data
, What is it? A contract for simple access to data is one under which the supplier undertakes
to provide to the recipient access to particular data on a medium within the supplier's control
and which is not a contract for the transfer of data under Principle 7.
Important Terms?
Source must provide R with tools to access; Source must make the data accessible in a
structured and machine-readable format; Source must enable the data to be accessed
remotely by R unless there are security concerns; same "fit for purpose" and control
obligations as for transfer
Recipient may only process for purposes consistent with or agreed to in contract; May port
on same conditions; May read, process or port including by auto means as many times as R
wishes during contract term
Principle 9: Contracts for exploitation of a data source
What is it? A contract for exploitation of a data source is one under which the supplier
undertakes to provide to the recipient access to data by providing access to a particular
device or facility by which data is collected or otherwise generated (the 'data source')
enabling
the recipient to read the data, process or port data from the data source.
Important Terms:
S must provide access in real time. S does not provide a warranty as it pertains to quantity
or quality
R may port all data
(Not covered in class) Principle 10: Con
\ALI-ELI principles for a data economy, Part III, Chapter C (Data Rights in the Public
Interest). - ANS-ALI-ELI: "(1) The law should afford data rights for the public interest, and for
similar reasons independent of the share that the party to whom the rights are afforded had
in the
generation of the data, only if the encroachment on the controller's or any third party's
legitimate interests is necessary, suitable and proportionate to the public interest pursued."
\Amy Kapcynski, The Law of Informational Capitalism, 129 YALE LAW JOURNAL 1460,
1480-1515 (Parts II and III). - ANS-Legal realism, formulated in response to laissez-faire,
powerfully repudiated its description of the relationship between law and markets. There was
a lie at the heart of laissez-faire: markets do not exist outside of law, so as to make state
regulation an unjust incursion into a natural order
o Big idea of Karl Polanyi
- Companies may be hungry for data as a means of price discrimination e.g., Amazon shows
each of us the price that we're individually willing to pay
- Law has a fear of interfering with its "fetish" of innovation
o Moore v. Regents case about cell line for leukemia and fear of destroying economic
incentive for important research
- Primary sources of power for Google, Facebook, financial algorithmic sector, etc. are...
o Trade-Secret Rights
§ IP scholars have fought hard against recognizing property rights in personal data or
databases of personal information
§ Copyright law does not cover facts and databases can rarely be protected by copyright
o Contract Law
§ Blessing of "click-wrap" agreements
Aaron Perzanowski and Jason Schultz, The End of Ownership (2016), chapter 8: 'The
Internet of Things You Don't Own'. - ANS-The internet of things refers to a range of devices
that generally combine embedded software, network connectivity, microscopic sensors, and
large-scale data analytics. So many objects are now computers, e.g., phones, cars, light
bulbs, etc. and are therefore susceptible to external limitations and controls of other digital
goods. This has implications for ownership and consumer welfare (see example of smart
thermostat being discontinued, pp. 140-141).
Possible beginning of IoT → The iPhone as a walled garden approach - can only install
software Apple allows, can only configure settings Apple gives access too, etc. This sparked
a practice of jailbreaking to install software, replace operating system, and customize the
phone. In legal battle that followed, Apple argued that iPhone users are licensees, not
owners, of the OS. Copyright Office ruled in favor of right to jailbreak phones but
sidestepped the issue of ownership.
Farm example: Monsanto sold the herbicide Roundup, but this also damaged crops. They
manufactured crops resistant to roundup and "licensed [them] for a single season" to
farmers, so farmers couldn't replant the following year, instead they had to buy new seeds.
John Deere imposed a software layer between farmers and tractors in order to force farmers
to have equipment serviced by authorized John Deere dealers. John Deere claimed it owned
the code in tractors it sold to farmers and farmers had an implied license for the life of the
vehicle. This raises the price for farmers and also impacts innovation.
Modern cars (GM, Mercedes-Benz) : Also contains tools that weaken the property interests
of owners, including DRM that prevents repair and customization, soft- ware that monitors
and controls your driving, even restrictions on vehicle resale. Again argued that underlying
computer software was licensed
\Ada Lovelace Institute, Exploring legal mechanisms for data stewardship (March 2021), pp.
12-14 (overview), pp. 41-47 (data trusts), 54 (data cooperatives versus data commons),
60-66 (data cooperatives). - ANS-Data Trusts
What is the purpose of the trust and how is consent reached?
What is the role of the trustee?
How will they be monitored?
How will they be funded? Why will people choose to join them? Different answers to this will
determine which trusts become more popular and thus have more bargaining power.
How would organizations interact with trusts? Could they sponsor them?
,What is the difference between a data commons and a data cooperative? In the case of
data, the cooperative model would imply that data was brought to and withdrawn from the
cooperative as members joined and left. A data commons implies a body of data whose
growth or decline would be independent of the identity and number of stakeholders.
Aim of Data Cooperatives: e the
balance between 1) complete privacy and 2) the potential benefits to the individual from
collecting and processing personal data and communicating the insights to the individual,
and 3) in those individuals then being able to better influence the market and receive a better
division of the economic benefits (e.g. through selling the data and/or insights).
Challenges:
Uptake: resonance challenge, mobilisation challenge, trust challenge, capacity challenge
Advocates potentially using contentious situations to create specialized data trusts. E.g.,
outrage by gig economy workers to create a worker owned and controlled data set.
Scale:
democratic control and shared ownership conflict in terms of efficiency - may require a
constitution to smooth over disagreements.
Rights, accountability, and governance must be established.
Cooperatives don't lend themselves to outside sources of funding, so they may have to fall
back on internal funding. Without funding, they may find it difficult to recruit good
administrators, so will be forced to elect a board from the members.
\Alexandra Giannopoulou, Understanding Open Data Regulation: An Analysis of the
Licensing Landscape, in Open Data Exposed (Bastiaan van Loenen, Glenn
Vancauwenberghe, & Joep Crompvoets eds., 2018) - ANS-The Berne Convention Article 2.1
determines the definition of literary and artistic works, thus requiring that data must pass the
originality test to be copyrightable. Article 2.5 permits the copyrighting of collections of data
(also supported by the WIPO Copyright Treaty of 1996 and Article 1013 of the Agreement on
Trade Related Aspects of Intellectual Property Rights of 1994).
European Court of Justice: ""it is only through the choice, sequence and combination of
those words that the author may express his creativity in an original manner and achieve a
result which is an intellectual creation."
A sui generis database right exists in Europe, it gives the creator of the database 15 years
exclusive copyright in order to protect the economic investment put into creating the
database (NOT creating the data). Public databases are theoretically also covered, but some
courts have ruled against them.
Transnational Open Data Licensing Models:
,Creative Commons: American NGO that has created a set of free, easy to use copyright
licenses. All licenses are based on four elements: Attribution (BY) (requires licensee to
indicate the name of the author on every distribution), No derivatives (ND) (forbids altering
the licensed material), No commercial uses (NC) (forbids commercial use), and Share Alike
(SA) (allows derivatives but requires the derivative work to be licensed under the same type
of license as the original).
"The licenses exist in three different formats or "layers". The license is first delivered as a
summary of its core elements, called the commons deed or human readable license. Then,
the second layer is the legally binding license called the legal deed, and third is the
machine-readable license, which describes the permissions and restrictions of the license in
a form of digital-rights expression making it easier
\ALI-ELI principles for a Data Economy - Data Transactions and Data Rights, pages
124-128; 156-158; 162-165; 166-170. - ANS-See article for US and EU cases/examples of
each principle.
Principle 16: Data rights. Data is a non-rivalrous resource, and data rights are not tied to
ownership or property principles.
Principle 21: Desistance from data activities with regard to co-generated data. A party should
have the right to demand a data controller desist use of and/or delete data, if the data could
reasonably cause harm to the party or if "the purpose of the data activities is inconsistent
with the way that party contributed to the generation of the data"
Principle 23: Economic share in profits derived from co-generated data. Parties usually are
not entitled to profits made from data except for when there is a contract or agreement for
the sharing of said profits, UNLESS: "(a) that party's contribution to the generation of the
data (i) was sufficiently unique that it cannot, from an economic point of view, be substituted
by contributions of other parties; or (ii) caused that party significant effort or expense; and (b)
profits derived by the controller are exceptionally high; and (c) the party seeking an
economic share was, when its contribution to the generation of the data was made, not in a
position to bargain effectively for remuneration."
"Principle 24: Justification for data rights and obligations (1) The law should afford data rights
for the public interest, and for similar reasons independent of the share that the party to
whom the rights are afforded had in the generation of the data, only if the encroachment on
the controller's or any third party's legitimate interests is necessary, suitable and
proportionate to the public interest pursued."
\ALI-ELI principles for a Data Economy - Data Transactions and Data Rights, Part II, Chapter
B (Contracts for Supply or Sharing of Data) - ANS-Provides default rules for Contracts for
Supply or Sharing of Data.
Principle 7: Contracts for transfer of data
What is it? Supplier undertakes to put the recipient in control of particular data by
transferring the data to a medium within the recipient's control.
Important terms? Access, Representations that Data Fits Purpose, Representations that
Supplier puts Recipient in Control of Data (over IP Claims, Non-IP Claims), Contract Term
Principle 8: Contracts for Simple Access to Data
, What is it? A contract for simple access to data is one under which the supplier undertakes
to provide to the recipient access to particular data on a medium within the supplier's control
and which is not a contract for the transfer of data under Principle 7.
Important Terms?
Source must provide R with tools to access; Source must make the data accessible in a
structured and machine-readable format; Source must enable the data to be accessed
remotely by R unless there are security concerns; same "fit for purpose" and control
obligations as for transfer
Recipient may only process for purposes consistent with or agreed to in contract; May port
on same conditions; May read, process or port including by auto means as many times as R
wishes during contract term
Principle 9: Contracts for exploitation of a data source
What is it? A contract for exploitation of a data source is one under which the supplier
undertakes to provide to the recipient access to data by providing access to a particular
device or facility by which data is collected or otherwise generated (the 'data source')
enabling
the recipient to read the data, process or port data from the data source.
Important Terms:
S must provide access in real time. S does not provide a warranty as it pertains to quantity
or quality
R may port all data
(Not covered in class) Principle 10: Con
\ALI-ELI principles for a data economy, Part III, Chapter C (Data Rights in the Public
Interest). - ANS-ALI-ELI: "(1) The law should afford data rights for the public interest, and for
similar reasons independent of the share that the party to whom the rights are afforded had
in the
generation of the data, only if the encroachment on the controller's or any third party's
legitimate interests is necessary, suitable and proportionate to the public interest pursued."
\Amy Kapcynski, The Law of Informational Capitalism, 129 YALE LAW JOURNAL 1460,
1480-1515 (Parts II and III). - ANS-Legal realism, formulated in response to laissez-faire,
powerfully repudiated its description of the relationship between law and markets. There was
a lie at the heart of laissez-faire: markets do not exist outside of law, so as to make state
regulation an unjust incursion into a natural order
o Big idea of Karl Polanyi
- Companies may be hungry for data as a means of price discrimination e.g., Amazon shows
each of us the price that we're individually willing to pay
- Law has a fear of interfering with its "fetish" of innovation
o Moore v. Regents case about cell line for leukemia and fear of destroying economic
incentive for important research
- Primary sources of power for Google, Facebook, financial algorithmic sector, etc. are...
o Trade-Secret Rights
§ IP scholars have fought hard against recognizing property rights in personal data or
databases of personal information
§ Copyright law does not cover facts and databases can rarely be protected by copyright
o Contract Law
§ Blessing of "click-wrap" agreements
