wildercb/PrivacyTextBooks1.2 · Datasets at Hugging Face

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protecting their customers’ privacy when, in fact, they have done quite
little.22
Based on his interviews with technologists, Waldman observes that
many technologists believe privacy merely involves providing users with
notice about the company’s privacy practices. Others think privacy is
synonymous with encryption, which in this context is driven more by a
desire to secure company data than to safeguard against consumer privacy
risks. As Waldman also notes, “Few engineers remembered meeting with
lawyers or privacy professionals one-on-one to discuss integrating privacy
considerations into their work. Many found it difficult to design with user
needs in mind; therefore, engineer-only design teams not only minimized
the importance of privacy, but also missed how their designs impacted
consumers.”23 This kind of organizational schism has led to a mentality
around privacy and data security that ends up limiting the effectiveness of
both domains.
One of the problems with separating data security and privacy is that
people working in these areas cannot learn from each other. This means
they often repeat the same mistakes or miss out on different ways of
thinking about problems. People can get a little myopic, thinking that their
little patch of responsibilities is the cosmos. This kind of narrow thinking
also leads to a breakdown in cooperation where privacy interventions could
help improve data security and vice versa.
Waldman’s interviews with technologists reveal that the companies they
work for often do very little to prioritize privacy by design. As Waldman
observes, “Privacy professionals or other personnel trained in privacy rarely
met with engineers and programmers, even during weeks of intense design
work.” Even at companies that had “privacy teams that were supposed to
‘insinuate’ themselves into design, high turnover, a laissez-faire attitude,
and corporate silos kept privacy mostly orthogonal to design.”24
Further, Waldman’s work reveals that privacy is often deprioritized
while other values take precedence. The mandate often comes from the top,
where executives want engineers to prioritize “speed, agility, [and]
functionality.’ ”25 Waldman noted that “[i]nterviewees used words and
phrases like ‘hands off,’ ‘absent,’ ‘uninvolved,’ and ‘not really a factor,’ to
describe their employers’ approach to privacy. Privacy is akin to security’s
distant cousin, whom everyone forgets to invite to the party. Even when
privacy is at the party, it is relegated to the small children’s table off to the
side.
Beyond a lack of privacy protection, the schism between privacy and
data security has resulted in organizations viewing data security mainly as
an IT issue. Certainly, many components of good data security involve IT,
such as encryption, firewalls, access controls, and more. But many more
security issues involve a human dimension. Many security decisions
involve human behavior, such as how to deal with cognitive limitations,
carelessness, cheating, denial, ignorance, gullibility, and misconduct—
security’s seven deadly sins. Security decisions also involve policy, such as
managing the tradeoff between security on the one side, and ease,
convenience, and ready accessibility on the other.
We have heard people call the security side “hard” or “left-brained” and
the privacy side “soft” or “right-brained.” IT technologists are often not
well-trained in addressing complex issues involving people and values; they
are more often trained mostly in “hard” technological problems and
solutions. They know how computer systems and code operate, but often
they aren’t sufficiently trained about how to respond to human behavior or
how to think through challenging policy choices. Privacy professionals, in
contrast, receive a heavier dose of training about so-called soft issues such
as human behavior, values, law, and policy. We aren’t fond of the terms
“hard” and “soft” or “left-brained” or “right-brained,” but we agree that
there is certainly a distinction between the kinds of training IT and privacy
professionals receive. The key difference is that privacy draws more from
the humanities and data security is more steeped in engineering. For
effective data security, however, both types of thinking are essential.
Privacy is (or at least should be) about much more than just effectuating
peoples’ personal preferences about who should have their data. Privacy is
about trust, power, dignity, and the collective autonomy to set the
preconditions of human flourishing.26 In a broader sense, privacy is about
all the rules that govern our personal information.27 Data security policy
similarly cannot escape a web of value-laden decisions, because it, too,
requires tradeoffs guided by ethics and normative considerations.
A Schism in the Law
The schism between security and privacy also exists in the law, especially
in U.S. law. Broadly speaking, the law began with a more unified view of
privacy and security, but after the ChoicePoint breach, data security law
spun off into a more separate domain.
In the early laws of the 1970s through 2000, data security evolved
alongside and within privacy laws and frameworks. Data security is one of
the original Fair Information Practice Principles (FIPPs), which were the
principles proposed to address concerns with the rise of computer databases
of personal information.28 The FIPPs arose in a 1973 report by the U.S.
Department of Health, Education, and Welfare (HEW) called Records,
Computers and the Rights of Citizens.29 The HEW report was prompted by
concerns about the computerization of records, and the committee that
drafted the report was charged with recommending legal and policy
responses. The primary recommendation of the report was to enact a code
of fair information practices to regulate all repositories of personal data.
Data security was one of the main recommendations in the report: “Any
organization creating, maintaining, using, or disseminating records of
identifiable personal data must assure the reliability of the data for their
intended use and must take reasonable precautions to prevent misuse of the
data.”30
The FIPPs have become the backbone of privacy laws around the world.
In 1980, the OECD Privacy Guidelines included the “Security Safeguards
Principle,” which stated that “Personal data should be protected by
reasonable security safeguards against such risks as loss or unauthorized
access, destruction, use, modification or disclosure of data.”31 The OECD
Privacy Guidelines have formed the blueprint for the EU’s privacy laws,
starting with various member nation’s laws, then the EU Data Protection
Directive, and today’s General Data Protection Regulation (GDPR). Laws
in the United States and around the world include many of the FIPPs. There
are now more than 200 countries with data privacy laws, and most of them

protecting their customers’ privacy when, in fact, they have done quite

little.22

Based on his interviews with technologists, Waldman observes that

many technologists believe privacy merely involves providing users with

notice about the company’s privacy practices. Others think privacy is

synonymous with encryption, which in this context is driven more by a

desire to secure company data than to safeguard against consumer privacy

risks. As Waldman also notes, “Few engineers remembered meeting with

lawyers or privacy professionals one-on-one to discuss integrating privacy

considerations into their work. Many found it difficult to design with user

needs in mind; therefore, engineer-only design teams not only minimized

the importance of privacy, but also missed how their designs impacted

consumers.”23 This kind of organizational schism has led to a mentality

around privacy and data security that ends up limiting the effectiveness of

both domains.

One of the problems with separating data security and privacy is that

people working in these areas cannot learn from each other. This means

they often repeat the same mistakes or miss out on different ways of

thinking about problems. People can get a little myopic, thinking that their

little patch of responsibilities is the cosmos. This kind of narrow thinking

also leads to a breakdown in cooperation where privacy interventions could

help improve data security and vice versa.

Waldman’s interviews with technologists reveal that the companies they

work for often do very little to prioritize privacy by design. As Waldman

observes, “Privacy professionals or other personnel trained in privacy rarely

met with engineers and programmers, even during weeks of intense design

work.” Even at companies that had “privacy teams that were supposed to

‘insinuate’ themselves into design, high turnover, a laissez-faire attitude,

and corporate silos kept privacy mostly orthogonal to design.”24

Further, Waldman’s work reveals that privacy is often deprioritized

while other values take precedence. The mandate often comes from the top,

where executives want engineers to prioritize “speed, agility, [and]

functionality.’ ”25 Waldman noted that “[i]nterviewees used words and

phrases like ‘hands off,’ ‘absent,’ ‘uninvolved,’ and ‘not really a factor,’ to

describe their employers’ approach to privacy. Privacy is akin to security’s

distant cousin, whom everyone forgets to invite to the party. Even when

privacy is at the party, it is relegated to the small children’s table off to the

side.

Beyond a lack of privacy protection, the schism between privacy and

data security has resulted in organizations viewing data security mainly as

an IT issue. Certainly, many components of good data security involve IT,

such as encryption, firewalls, access controls, and more. But many more

security issues involve a human dimension. Many security decisions

involve human behavior, such as how to deal with cognitive limitations,

carelessness, cheating, denial, ignorance, gullibility, and misconduct—

security’s seven deadly sins. Security decisions also involve policy, such as

managing the tradeoff between security on the one side, and ease,

convenience, and ready accessibility on the other.

We have heard people call the security side “hard” or “left-brained” and

the privacy side “soft” or “right-brained.” IT technologists are often not

well-trained in addressing complex issues involving people and values; they

are more often trained mostly in “hard” technological problems and

solutions. They know how computer systems and code operate, but often

they aren’t sufficiently trained about how to respond to human behavior or

how to think through challenging policy choices. Privacy professionals, in

contrast, receive a heavier dose of training about so-called soft issues such

as human behavior, values, law, and policy. We aren’t fond of the terms

“hard” and “soft” or “left-brained” or “right-brained,” but we agree that

there is certainly a distinction between the kinds of training IT and privacy

professionals receive. The key difference is that privacy draws more from

the humanities and data security is more steeped in engineering. For

effective data security, however, both types of thinking are essential.

Privacy is (or at least should be) about much more than just effectuating

peoples’ personal preferences about who should have their data. Privacy is

about trust, power, dignity, and the collective autonomy to set the

preconditions of human flourishing.26 In a broader sense, privacy is about

all the rules that govern our personal information.27 Data security policy

similarly cannot escape a web of value-laden decisions, because it, too,

requires tradeoffs guided by ethics and normative considerations.

A Schism in the Law

The schism between security and privacy also exists in the law, especially

in U.S. law. Broadly speaking, the law began with a more unified view of

privacy and security, but after the ChoicePoint breach, data security law

spun off into a more separate domain.

In the early laws of the 1970s through 2000, data security evolved

alongside and within privacy laws and frameworks. Data security is one of

the original Fair Information Practice Principles (FIPPs), which were the

principles proposed to address concerns with the rise of computer databases

of personal information.28 The FIPPs arose in a 1973 report by the U.S.

Department of Health, Education, and Welfare (HEW) called Records,

Computers and the Rights of Citizens.29 The HEW report was prompted by

concerns about the computerization of records, and the committee that

drafted the report was charged with recommending legal and policy

responses. The primary recommendation of the report was to enact a code

of fair information practices to regulate all repositories of personal data.

Data security was one of the main recommendations in the report: “Any

organization creating, maintaining, using, or disseminating records of

identifiable personal data must assure the reliability of the data for their

intended use and must take reasonable precautions to prevent misuse of the

data.”30

The FIPPs have become the backbone of privacy laws around the world.

In 1980, the OECD Privacy Guidelines included the “Security Safeguards

Principle,” which stated that “Personal data should be protected by

reasonable security safeguards against such risks as loss or unauthorized

access, destruction, use, modification or disclosure of data.”31 The OECD

Privacy Guidelines have formed the blueprint for the EU’s privacy laws,

starting with various member nation’s laws, then the EU Data Protection

Directive, and today’s General Data Protection Regulation (GDPR). Laws

in the United States and around the world include many of the FIPPs. There

are now more than 200 countries with data privacy laws, and most of them