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BLUE PAPER –CHARTINGANEW
FRAMEWORK FORDATAPROTECTIONIN
INDIA
This Blue Paper is a result
of a Roundtable discussion
held on 4September 2017,
on the Discussion
Document Beyond
Consent: A New
Paradigm for Data
Protection
Prepared by:
Manasa Venkataraman
and Ajay Patri
October 2017
ABOUTTHE DISCUSSION DOCUMENT
This segment addresses the following aspects of the Discussion
Document:
— The foundational principles to govern any new data
protection framework
— The salient features of the new data protection framework
being proposed
— The key implementation features of the proposed framework
3|
Guiding Principles
for Data Protection
Accountability
An entity handling the data of an individual (a data controller) will
be liable for any harm caused as a result of its actions.Consent, in
such scenarios, cannot be a defense against liability.
Autonomy
The new model must be designed in a manner that ensures that an
individual has the power to determine how much data he is willing
to share.
Security
A data controller should be vested with the responsibility to ensure
appropriate security standards are maintained with respect to the
data.
Traditionalmodelsofdataprotectionrelyonan
individual’sconsenttothetermsandconditions
ofdataprocessing.Withthedevelopmentof
technologyandanincreasedglutininformation,
thismodelisnolongerfeasible. TheDiscussion
Documentexploresthepossibilityofan
alternativetothismodel,onebasedonthe
principlesoutlinedinthissegment.
4|
Salient Features of
the Proposed Model
Data rights
Every individual will have certain inalienable rights over their
personal data.
Harm
The violation of the data rights will result in harm to the individual.
Liability
The causation of harm will make the entity handling the data liable.
Buildingontheguidingprinciplesoutlinedearlier,
theproposedmodelincorporatesthefollowing
features.
5|
Implementation
Features
Learned Intermediary
A learned intermediary acts as an auditor, helping individuals and
data controllers recognise biases in the system and suggest
corrective measures.
Data Commissioner
A regulatory and adjudicatory authority that is also vested with the
power to set standards for data protection.
Theimplementationoftheproposedmodelwill
beachievedthroughacombinationoftwo
entities:LearnedIntermediaryandData
Commissioner.
ROUNDTABLE DISCUSSION POINTS
List of participants to the Roundtable:
— Akash Mahajan, Co-founder, Appsecco
— Andrew Kramer , Omidyar Network
— Beni Chugh , Research Associate, IFMR Finance Foundation
— C.V. Madhukar, Investment Partner, Omidyar Network and
Project Lead – Digital Identity
— Faiza Rahman, Consultant, National Institute of Public
Finance and Policy
— KiranJonnalagadda, Co-founder, HasGeek and Internet
Freedom Foundation
— Malavika Raghavan, Project Head for the Future of Finance
Initiative at IFMR Finance Foundation
— Nayantara Narayan, Head of Policy and Research at the
office of Mr. Baijayant ‘Jay’ Panda, Member of Parliament
(MP) in the Lok Sabha
— Pranesh Prakash, Policy Director at theCentre for Internet
and Society
— Sandesh Anand , Managing Consultant at Synopsys
— Subhashish Bhadra, Associate, Digital Identity,Omidyar
Network
— Sukarn Singh Maini, Research Associate,Software Freedom
Law Centre
The Roundtable was chaired by Rahul
Matthan, Fellow,Technology and Policy
Research at theTakshashila Institution
and Partner,Trilegal.
7|
On Consent Discussion Point #1: Agency of an individual
Consent allows an individual to maintain a certain level of control
over his personal data. It empowers the individual to exercise his
autonomy by refusing to deal with a particular data controller if he
distrusts the terms on offer.
The corollary of this could also hold true, i.e., an individual might
trust a data controller with his data despite the likelihood of a harm
being caused. An individual should have the ability to judge such a
scenario for himself.
Discussion Point #2:The threat of paternalism
A model that overrides an individual’s consent might be construed
as being too paternalistic. It would be symptomatic of a situation
where the State claims to know what is best for the individual.
One must also consider the implications of this on the wider
relationship between an individual and a State, particularly in a
democratic nation.
8|
On Consent Discussion Point #3: A consent+ model
Given the shortcomings of consent and the importance of
preserving an individual’s autonomy, it could be worthwhile to
explore a consent+ model.
Under this model, the accountability principle will become
applicable in certain specified circumstances where it can be
reasonably inferred that the individual has not consented to harm,
or even the probability of harm. In all other situations not covered
by this bare minimum threshold, the individual’s consent will
govern the relationship between the individual and the data
controller.
Discussion Point #4: Feasibility of simplified consent
If the shortcoming of consent is that it is riddled with excessive
legalese and jargon, one should also consider the possibility of
having simplified consent mechanisms.
This would be akin to providing the individual with a privacy notice.
9|
On Consent Discussion Point #5: Scenarios where prior consent is not possible
The accountability model can also be applied in situations where
prior consent of an individual cannot be obtained.
This could be seen in cases where data in the aggregate is
converted to personally identifiable information.Typically, this
conversion happens without the individual’s consent being
obtained.
Discussion Point #6: Data protection standards need not be
universal
Given the vast differences in the use of data in various sectors, as
well as the different levels of risks involved therein, it might be
prudent to incorporate sector-specific standards of data protection.
Under this, it is likely that consent might be overridden in some
sectors where the likelihood of harm is high. Similarly, in other
sectors, the consent of the individual will retain its primacy.
10|
On Rights and
Harms
Discussion Point #1: Institutional requirements
If the data protection framework relies on rights as the basis for
protecting the interests of individuals, it must be accompanied by
strong institutions capable of enforcing such rights. In the Indian
context, it remains to be seen if the institutional capacity exists for
handling such a framework.
Discussion Point #2:Gradation of rights
Apart from sectoral gradations in data protection, it could be useful
to define various types of rights themselves. For instance, some
rights could be classified as sensitive personal information or data.
The thresholds for determining the harm caused due to the
violation of such enumerated rights can accordingly be different.
11|
On Liability Discussion Point #1:The point in time when liability kicks in
It could be difficult to identify when a data controller becomes liable
for its actions. For instance, in cases where an individual has been
identified without his consent from disparate sources of data, would
the mere identification, with the potential for future harm, result in
liability? Or would there be a requirement for actual harm to be
effected in order to ascertain liability?
Discussion Point #2: Determining who is liable for a harm caused
In most cases, the information belonging to an individual would
have been within the control of various entities at some point of
time before harm occurs.Given this, determining which of the
entities involved is liable for the harm can be often difficult to
pinpoint.
12|
On Liability Discussion Point #3: Liability for State actors
In order to be truly effective, a data protection framework must
account for data rights violations by State actors as well.The
definition of a data controller must necessarily includeState actors
handling the data of individuals.
One possible solution is to penalise the concerned department
responsible for the violation by imposing a penalty that is a
percentage of its budget.This would be in addition to any fines and
compensation that other data controllers will be liable for under
the law.
13|
On Implementation Discussion Point #1: Scope of audits
The information security model in India already incorporates
elements of an audit, primarily through the nodal agency CERT-In.
The efficacy of this model, however, is questionable.The audit
requirements often do little in the way of improving security while
increasing the complexity and cost of the systems being deployed.
The inefficiencies of this model must be studied so that they can be
avoided in the new framework.
Discussion Point #2:Cost of audits
Any requirement to conduct audits will come at a cost to data
controllers.While this cost may not dent the finances of large
corporations, it might inhibit the development of the start-up
ecosystem in India.
Given this, it might be advisable to have graded levels of audit that
are pegged to the size and finances of the data controller in
question.
14|
On Implementation Discussion Point #3: Publication of queries
The model proposed in the Discussion Document provides for the
publishing of queries that data controllers ask with respect to the
individuals. Such queries can then be audited by Learned
Intermediaries to identify patently bad actors. If implemented, it is
unclear how this will be interpreted by enforcement authorities.
There is a possibility that the content of the queries might conflict
with the proprietary rights that data controllers have over their
algorithms.
Having said that, it is easier to envisage a scenario where this can
be made applicable to State actors.
Discussion Point #4:Composition of enforcement body
The enforcement organisation being contemplated should have the
technical expertise to handle issues related to data protection. It
would be advisable to avoid a body that is purely executive or
judicial in nature.
15|
On Implementation Discussion Point #5: Ensuring compliance from data collectors
It would be worthwhile exploring the means by which data
controllers can be encouraged to be more compliant with data
standards.One option is the creation of a post of a Data Privacy
Officer who can be made personally liable for violations that occur
under his watch. Companies that appoint such officers have shown
to be more cognizant of their responsibilities.
REFERENCE
Discussion Document:
BeyondConsent: A New Paradigm for Data Protection by Rahul Matthan, Fellow,Technology & Policy
Programme,TheTakshashila Institution and Partner,Trilegal. Edited by: ManasaVenkataraman and Ajay Patri,
TheTakshashila Institution.

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Takshashila Blue Paper: Charting a New Framework for Data Protection in India

  • 1. BLUE PAPER –CHARTINGANEW FRAMEWORK FORDATAPROTECTIONIN INDIA This Blue Paper is a result of a Roundtable discussion held on 4September 2017, on the Discussion Document Beyond Consent: A New Paradigm for Data Protection Prepared by: Manasa Venkataraman and Ajay Patri October 2017
  • 2. ABOUTTHE DISCUSSION DOCUMENT This segment addresses the following aspects of the Discussion Document: — The foundational principles to govern any new data protection framework — The salient features of the new data protection framework being proposed — The key implementation features of the proposed framework
  • 3. 3| Guiding Principles for Data Protection Accountability An entity handling the data of an individual (a data controller) will be liable for any harm caused as a result of its actions.Consent, in such scenarios, cannot be a defense against liability. Autonomy The new model must be designed in a manner that ensures that an individual has the power to determine how much data he is willing to share. Security A data controller should be vested with the responsibility to ensure appropriate security standards are maintained with respect to the data. Traditionalmodelsofdataprotectionrelyonan individual’sconsenttothetermsandconditions ofdataprocessing.Withthedevelopmentof technologyandanincreasedglutininformation, thismodelisnolongerfeasible. TheDiscussion Documentexploresthepossibilityofan alternativetothismodel,onebasedonthe principlesoutlinedinthissegment.
  • 4. 4| Salient Features of the Proposed Model Data rights Every individual will have certain inalienable rights over their personal data. Harm The violation of the data rights will result in harm to the individual. Liability The causation of harm will make the entity handling the data liable. Buildingontheguidingprinciplesoutlinedearlier, theproposedmodelincorporatesthefollowing features.
  • 5. 5| Implementation Features Learned Intermediary A learned intermediary acts as an auditor, helping individuals and data controllers recognise biases in the system and suggest corrective measures. Data Commissioner A regulatory and adjudicatory authority that is also vested with the power to set standards for data protection. Theimplementationoftheproposedmodelwill beachievedthroughacombinationoftwo entities:LearnedIntermediaryandData Commissioner.
  • 6. ROUNDTABLE DISCUSSION POINTS List of participants to the Roundtable: — Akash Mahajan, Co-founder, Appsecco — Andrew Kramer , Omidyar Network — Beni Chugh , Research Associate, IFMR Finance Foundation — C.V. Madhukar, Investment Partner, Omidyar Network and Project Lead – Digital Identity — Faiza Rahman, Consultant, National Institute of Public Finance and Policy — KiranJonnalagadda, Co-founder, HasGeek and Internet Freedom Foundation — Malavika Raghavan, Project Head for the Future of Finance Initiative at IFMR Finance Foundation — Nayantara Narayan, Head of Policy and Research at the office of Mr. Baijayant ‘Jay’ Panda, Member of Parliament (MP) in the Lok Sabha — Pranesh Prakash, Policy Director at theCentre for Internet and Society — Sandesh Anand , Managing Consultant at Synopsys — Subhashish Bhadra, Associate, Digital Identity,Omidyar Network — Sukarn Singh Maini, Research Associate,Software Freedom Law Centre The Roundtable was chaired by Rahul Matthan, Fellow,Technology and Policy Research at theTakshashila Institution and Partner,Trilegal.
  • 7. 7| On Consent Discussion Point #1: Agency of an individual Consent allows an individual to maintain a certain level of control over his personal data. It empowers the individual to exercise his autonomy by refusing to deal with a particular data controller if he distrusts the terms on offer. The corollary of this could also hold true, i.e., an individual might trust a data controller with his data despite the likelihood of a harm being caused. An individual should have the ability to judge such a scenario for himself. Discussion Point #2:The threat of paternalism A model that overrides an individual’s consent might be construed as being too paternalistic. It would be symptomatic of a situation where the State claims to know what is best for the individual. One must also consider the implications of this on the wider relationship between an individual and a State, particularly in a democratic nation.
  • 8. 8| On Consent Discussion Point #3: A consent+ model Given the shortcomings of consent and the importance of preserving an individual’s autonomy, it could be worthwhile to explore a consent+ model. Under this model, the accountability principle will become applicable in certain specified circumstances where it can be reasonably inferred that the individual has not consented to harm, or even the probability of harm. In all other situations not covered by this bare minimum threshold, the individual’s consent will govern the relationship between the individual and the data controller. Discussion Point #4: Feasibility of simplified consent If the shortcoming of consent is that it is riddled with excessive legalese and jargon, one should also consider the possibility of having simplified consent mechanisms. This would be akin to providing the individual with a privacy notice.
  • 9. 9| On Consent Discussion Point #5: Scenarios where prior consent is not possible The accountability model can also be applied in situations where prior consent of an individual cannot be obtained. This could be seen in cases where data in the aggregate is converted to personally identifiable information.Typically, this conversion happens without the individual’s consent being obtained. Discussion Point #6: Data protection standards need not be universal Given the vast differences in the use of data in various sectors, as well as the different levels of risks involved therein, it might be prudent to incorporate sector-specific standards of data protection. Under this, it is likely that consent might be overridden in some sectors where the likelihood of harm is high. Similarly, in other sectors, the consent of the individual will retain its primacy.
  • 10. 10| On Rights and Harms Discussion Point #1: Institutional requirements If the data protection framework relies on rights as the basis for protecting the interests of individuals, it must be accompanied by strong institutions capable of enforcing such rights. In the Indian context, it remains to be seen if the institutional capacity exists for handling such a framework. Discussion Point #2:Gradation of rights Apart from sectoral gradations in data protection, it could be useful to define various types of rights themselves. For instance, some rights could be classified as sensitive personal information or data. The thresholds for determining the harm caused due to the violation of such enumerated rights can accordingly be different.
  • 11. 11| On Liability Discussion Point #1:The point in time when liability kicks in It could be difficult to identify when a data controller becomes liable for its actions. For instance, in cases where an individual has been identified without his consent from disparate sources of data, would the mere identification, with the potential for future harm, result in liability? Or would there be a requirement for actual harm to be effected in order to ascertain liability? Discussion Point #2: Determining who is liable for a harm caused In most cases, the information belonging to an individual would have been within the control of various entities at some point of time before harm occurs.Given this, determining which of the entities involved is liable for the harm can be often difficult to pinpoint.
  • 12. 12| On Liability Discussion Point #3: Liability for State actors In order to be truly effective, a data protection framework must account for data rights violations by State actors as well.The definition of a data controller must necessarily includeState actors handling the data of individuals. One possible solution is to penalise the concerned department responsible for the violation by imposing a penalty that is a percentage of its budget.This would be in addition to any fines and compensation that other data controllers will be liable for under the law.
  • 13. 13| On Implementation Discussion Point #1: Scope of audits The information security model in India already incorporates elements of an audit, primarily through the nodal agency CERT-In. The efficacy of this model, however, is questionable.The audit requirements often do little in the way of improving security while increasing the complexity and cost of the systems being deployed. The inefficiencies of this model must be studied so that they can be avoided in the new framework. Discussion Point #2:Cost of audits Any requirement to conduct audits will come at a cost to data controllers.While this cost may not dent the finances of large corporations, it might inhibit the development of the start-up ecosystem in India. Given this, it might be advisable to have graded levels of audit that are pegged to the size and finances of the data controller in question.
  • 14. 14| On Implementation Discussion Point #3: Publication of queries The model proposed in the Discussion Document provides for the publishing of queries that data controllers ask with respect to the individuals. Such queries can then be audited by Learned Intermediaries to identify patently bad actors. If implemented, it is unclear how this will be interpreted by enforcement authorities. There is a possibility that the content of the queries might conflict with the proprietary rights that data controllers have over their algorithms. Having said that, it is easier to envisage a scenario where this can be made applicable to State actors. Discussion Point #4:Composition of enforcement body The enforcement organisation being contemplated should have the technical expertise to handle issues related to data protection. It would be advisable to avoid a body that is purely executive or judicial in nature.
  • 15. 15| On Implementation Discussion Point #5: Ensuring compliance from data collectors It would be worthwhile exploring the means by which data controllers can be encouraged to be more compliant with data standards.One option is the creation of a post of a Data Privacy Officer who can be made personally liable for violations that occur under his watch. Companies that appoint such officers have shown to be more cognizant of their responsibilities.
  • 16. REFERENCE Discussion Document: BeyondConsent: A New Paradigm for Data Protection by Rahul Matthan, Fellow,Technology & Policy Programme,TheTakshashila Institution and Partner,Trilegal. Edited by: ManasaVenkataraman and Ajay Patri, TheTakshashila Institution.