New America Foundation

10/29/2024 | News release | Distributed by Public on 10/29/2024 07:07

What’s the Value of Privacy

What's the Value of Privacy?

Brief

Francesco Ungaro/Pexels

Oct. 29, 2024

On a day-to-day basis, people make decisions about what information to share and what information to keep to themselves-guided by an inner privacy compass. Privacy is a concept that is both evocative and broad, often possessing different meanings for different people. The term eludes a common, static definition, though it is now inextricably linked to technology and a growing sense that individuals do not have control over their personal information. If privacy still, at its core, encompasses "the right to be left alone," then that right is increasingly difficult to exercise in the modern era.

The inability to meaningfully choose privacy is not an accident-in fact, it's often by design. Society runs on data. Whether it is data about people's personal attributes, preferences, or actions, all that data can be linked together, becoming greater than the sum of its parts. If data is now the world's most valuable resource, then the companies that are making record profits off that data are highly incentivized to keep accessing it and obfuscating the externalities of data sharing. In brief, data use and privacy are "economically significant."

"If privacy still, at its core, encompasses 'the right to be left alone,' then that right is increasingly difficult to exercise in the modern era."

And yet, despite the pervasive nature of data collection, much of the public lacks a nuanced understanding of the true costs and benefits of sharing their data-for themselves and for society as a whole. People who have made billions by collecting and re-selling individual user data will continue to claim that it has little value. And yet, there are legitimate reasons why data should be shared-without a clearunderstanding of an issue, it is impossible to address it.

Instead of relying solely on a subjective and individualistic approach to assessing privacy, it is time for countries around the world to explore systemic frameworks for privacy valuation that reflect the potential costs and benefits of sharing data, and the United States can take the lead on this endeavor. Since the 1970s, U.S. federal agencies have been required to evaluate the impacts of significant regulations using a cost-benefit framework.Since then, the federal government has made a concerted effort to value impacts that are hard to quantify, leading to breakthroughs such as the Social Cost of Carbon and the Value of Statistical Life. While these may seem like obscure, technical features of federal evaluation, both of these measurements have had a critical impact on policy decisions in areas as diverse as workplace safety, transportation, environmental quality, and health.

"It is time for countries around the world to explore systemic frameworks for privacy valuation that reflect the potential costs and benefits of sharing data."

Extending this cost-benefit framework to include privacy valuation would clarify the societal impacts of data sharing on a case-by-case basis while still prioritizing data sharing when it is in the broader public interest. This valuation would take the form of a number that accounts for the external impacts of privacy, which can subsequently influence investment decisions, consumer behavior, and business practices. Such a framework would ensure privacy is less routinely undervalued. The purpose is not to replace much-neededcomprehensive federal privacy legislation, but rather to supplement it.

Privacy Is Difficult to Value

Weighing what is gained and lost from sharing data is currently an ambiguous and cumbersome ordeal for most users. Several hypothetical scenarios, reflecting real-world tradeoffs that individuals encounter, illustrate the difficulties of evaluating the costs and benefits of data use-especially given how opaque and confusing data-sharing choices often are.

Suppose a customer uses their email to procure a 10-percent-off coupon for a sandwich, and the company providing that coupon then distributes their email address to other vendors so that the customer ends up with five new marketing emails a day in their inbox. Was having their email shared and the resulting digital clutter worth it?

A person just moved to a new city and needs to set up a new account with the local electricity utility company. The fastest way for the company to approve the account is if the individual gives the company their Social Security number, instead of filling out a more extensive form and then waiting 10 business days for approval. A year later, that individual learns that utility companies are increasingly targets of cyberattacks and realizes that there is a chance any utility company will suffer a data breach. Was the faster approval still worth that risk?

What if a remote worker applies for a job online, and after they submit their application, they are asked to fill out a survey that asks them about their job aspirations so that the company can ensure it is reaching the right applicants. The applicant fills out the survey and, while they do not land that job, a few months later they receive a targeted request to apply to a different job from the same company. Eventually, the company offers them that job. Was submitting personal data worth the subsequent job offer?

Not all privacy considerations can be so neatly tied to some externally measurable value. For example, a new parent who lives far away from close friends and family finds that regularly sharing family photos on their accounts helps maintain those connections and reduces their sense of isolation. News emerges that Meta has been using those posts and photos to train their AI models. The company says the photos are anonymized, but the user does not understand what that means. Should the user keep sharing the photos?

In all these scenarios, individuals are making judgments about a trade-off between the costs and the benefits of sharing specific information. The ultimate decision an individual makes depends on a self-assessment based on imperfect information and personal preferences. The so-called "privacy paradox," or the apparent disconnect between individuals claiming they care about privacy while not acting in a congruent manner, stems partially from how situational these preferences are and the fact that people often are unable to exercise meaningful choices about their online privacy. This is particularly true in the United States, which is without a comprehensive federal privacy law.

The current U.S. approach to privacy consistently undervalues it and imposes high costs on privacy-conscious individuals-either by forcing non-participation or requiring payment for additional rights-which only exacerbate equity issues around online access and data privacy. The United States needs a systematic common framework that reduces the burden on individuals to make these judgment calls against a backdrop that is heavily skewed toward protecting the value that companies derive from massive data collection. The current approach underestimates the social and economic costs that flow from data breaches, data misuse, and the resulting loss of trust. It also minimizes the very real social and economic benefits that privacy confers by creating an environment in which individuals-and companies-can innovate and create with enough private space to experiment.

Why Valuing Privacy Matters

Much of the general discussion around privacy poorly captures its actual value. At one end of the spectrum, some companies treat the concept of privacy as a box-checking exercise in legal compliance. They measure the value of maximizing data access against potential fines for lax security protocols or over-collecting information. In principle, companies with poor data security and invasive data collection practices could risk losing customers who care about privacy, but it is difficult to assess how much this actually happens, especially given the lack of meaningful alternatives.

Conversely, privacy is sometimes seen as so critical that it can prevent institutions from prioritizing the many compelling reasons that data might be collected and linked, whether to ensure school districts are serving all students equitably, to demonstrate that young children under five are the most likely group to be evicted, or even to simplify how Americans file taxes.

Society lacks a method and a vocabulary for operating in the middle ground, one in which a fundamental right to privacy is affirmed and a rights-respecting framework for data sharing is acknowledged as necessary to advance evidence-based policy. Discussions of clear tradeoffs between the two need to be anchored in specific cases-ones where civil society advocates and policymakers can argue for clearly-defined proposals that advance privacy and other human rights, knowing that appropriate safeguards keep privacy risks at acceptable levels.

"Society lacks a method and a vocabulary for operating in the middle ground, one in which a fundamental right to privacy is affirmed and a rights-respecting framework for data sharing is acknowledged as necessary."

Enter valuation. At its core, valuation is a way to quantify and weigh the various impacts of an action in a methodical way. When organizations and governments are determining what policy to implement, they are often trying to understand the potential impacts of various scenarios. Doing so with hard numbers can turn a diverse set of facts and considerations into comparable outcomes. Without valuation, decision makers must rely more on conceptual and qualitative arguments that, while important and compelling, do not always lend themselves as well to comparison. Debates solely between value judgments can make objective decision-making more difficult and allow the most powerful and most organized actors to shift policy in their favor.

But the United States can move away from this subjective framework, as evidenced by discourse around climate change. For years, industries were able to get away with producing massive amounts of carbon emissions without accounting for the harm caused to society. Despite decades of scientists and environmentalists voicing concerns, companies still argued that the impact of carbon emissions was negligible or, at the very least, of little importance when compared to the perceived cost of combating the issue. This left policymakers with little guidance on how to properly weigh the merits of reducing carbon emissions against the costs of inaction. The U.S. government now uses a fixed number to determine the value of the environmental benefits from reducing carbon emissions and currently sets the cost to society of emitting one additional ton of carbon dioxide at roughly $190. While not perfect, putting a number on this previously hard-to-value impact has improved the United States' ability to identify cost-effective mitigation strategies, like raising environmental standards, pricing carbon, or investing in clean energy. And it has allowed for a broader understanding of therealcosts of unsustainable growth.

Improved valuation has also played a critical role in health and safety. Government policies and corporate decisions can affect the risks people face to their health and well-being. In the past, these health and safety benefits were often considered qualitatively or driven by legal requirements. When addressing issues like tightening workplace safety regulations or improving airbags in cars, policymakers lacked a systematic way to assess whether the changes were worthwhile. This changed in the 1980s, when the government adopted a new approach to valuing hazardous chemicals based on an individual's "willingness to pay" to avoid harm. This was a change from the previous approach of using the potential risk of lost lifetime earnings, which greatly undervalued lower-income individuals. Today, U.S. agencies use a fixed value to quantify the benefits of risk reduction. For example, the Department of Transportation values each statistical life saved by road safety measures at $13.2 million. These risk reduction benefits now play a significant role in justifying actions on a range of issues, from food standards to pollution control and health care.

How to Value Privacy

When thinking about the economic value of privacy, some products, like virtual private networks (VPNs), appear to directly reflect people's willingness to spend money to protect their data. In many cases, the value people place on privacy is not well captured by existing goods and services that are bought or sold. In this case, there are a range of economic methods that are commonly used for placing a value on important non-market goods and services, including stated or revealed preference methods.

Stated preference methods use surveys and set up hypothetical situations in order to elicit from people the value they place on something. This might be their stated willingness to pay for an increase in privacy or the amount they would need to be compensated for a reduction in privacy.

Revealed preference methods use data stemming from decisions people make to buy different goods and services, such as the amount of information applicants are willing to disclose to secure a lower mortgage rate. The aim is to identify decisions that involve some kind of implicit privacy tradeoff in order to indirectly infer the value people place on increased privacy.

Importantly, putting a value on privacy will almost certainly require developing multiple valuations depending on key criteria and contexts, such as the type of data being shared, with whom it is being shared, and the kinds of privacy impacts this sharing would entail. In this way, valuing privacy differs from environmental valuations, where a single value is used for the social cost of carbon.

"Putting a value on privacy will almost certainly require developing multiple valuations depending on key criteria and contexts."

A recent study exemplifies what one form of privacy valuation can look like. Researchers used a survey-based approach to understand the value people place on privacy for various types of information. They found that health and financial information was valued highly, with people willing to spend approximately $30 per month to protect data from their medical history or bank transactions. By comparison, browsing history or social media activity was less highly valued, with people willing to spend approximately $15 per month to protect these kinds of data.

The value that people place on privacy can be disaggregated into different components. Disclosure of financial information comes with the risk of privacy costs due to fraud. Meanwhile, the disclosure of browsing and purchase history may create privacy costs due to social stigma. Even the low-level disclosure of contact information can lead to hassle and time costs due to spam. The key takeaway from this disaggregation is that, beyond measuring the impact of these outcomes, the likelihood for each outcome to occur also should be taken into account. Since none of these outcomes will occur 100 percent of the time, the probability of a particular consequence occurring should be considered. Beyond any uncertain risks from disclosures and data breaches, all forms of data sharing involve some degree of privacy costs due to people's intrinsic preferences for autonomy over their personal information. Disaggregating these costs to arrive at an overall privacy sum allows for a more nuanced understanding of what is at stake in data sharing and people's preferences.

Credible estimates of people's value of privacy are critical inputs for measuring the aggregate social benefits of policies that alter the privacy landscape. For example, the benefits of increasing data sharing across government agencies can then be weighed against the aggregate privacy costs to the set of individuals whose data is being shared. Another example: The costs of regulations that mandate stricter cybersecurity standards on companies can be weighed against the aggregate benefits of greater privacy for the people those companies serve.

Moving toward a more systematic approach to incorporating the value of privacy will require assembling evidence that can account for these different factors in an objective and quantifiable way. In many cases, this will involve carrying out new research on a range of use cases using the valuation methods discussed above. Relatedly, the Federal Trade Commission requested input on developing a more standardized, societal approach to weighing privacy impacts that would draw on this kind of cost-benefit framework.

This approach to quantifying costs and benefits is already a well-established method for government policy evaluation. It is time to develop a similar approach for privacy-related issues.

The Path Toward Privacy Valuation

Currently, the lack of consistent methodology hampers privacy assessments in federal decision-making. Standardizing this process would help policymakers effectively evaluate privacy trade-offs, ensuring privacy is adequately considered when evaluating new technologies, programs, or regulations. In order to shift the conversation toward a more nuanced understanding of privacy, researchers and advocates must demonstrate that there is a need for and a viable path towards federal privacy valuation.

Multidisciplinary Research

An important first step is to invest in more multidisciplinary research demonstrating how privacy valuation can foster a more transparent and rights-respecting data ecosystem. There is already valuable existing research in this space. However, as privacy concerns and data use continue to shift rapidly, researchers must address critical gaps in the current literature on privacy valuation.

A comprehensive understanding of privacy's value requires insights from multiple disciplines, including economics, law, psychology, and data science. For example, economists may assess financial trade-offs of data minimization, while psychologists could explore how privacy and surveillance impact well-being and behavior. It is also important that researchers incorporate insights from industry to capture the diverse approaches that commercial sectors take toward data use.

Addressing equity should be a key focus of any research agenda, starting with exploration of how different demographic groups experience privacy losses. Policies should reflect the diverse needs and values of society, especially given that vulnerable populations face greater risks from data sharing and subsequent misuse. Incorporating these perspectives would provide a more complete understanding of privacy's real costs, both tangible and intangible. Additionally, given the focus of this research agenda on privacy and transparency, it will be important for research in this area to be easily accessible and open-access to ensure these insights can be used in public policy development.

To effectively address these critical gaps and advance our understanding of privacy's value, the following questions can serve as a foundation for this research effort.

  • What benefits do individuals and society derive from privacy?
  • How should the economic and social benefits of privacy be systematically measured?
  • How does the value of privacy vary contextually based on factors that include data sensitivity, who the data references, who holds the data, the associated risks of disclosure, and the intended uses of the data?
  • How should adequate weight be given to aspects of privacy that are hard to quantify?
  • How can changes in data value and sensitivity over time be properly accounted for?
  • What are best practices for integrating developments in privacy valuation into existing regulatory cost-benefit frameworks?
  • How should efforts to account for privacy valuation in government decision-making differ from data use by non-government actors?

Making the Case for Federal Privacy Valuation

Pursuing this research agenda and documenting use cases is essential for establishing a solid evidence base for informed government actions. The insights of research into privacy valuation will require concerted efforts from civil society and academia before it can be transformed into federal action.

Efforts to incorporate privacy valuation into federal policymaking should continue to involve key stakeholders in academia, industry, and civil society. An inclusive approach to policymaking will help gather the best available evidence, identify gaps where further work is needed, and generate more practical recommendations.

Federal agencies will need to coordinate efforts in order to develop a standardized methodology for privacy valuation that can be consistently integrated into all aspects of federal policy development. A coordinated interagency approach to tackling cross-cutting issues of this kind has been met with success in the past.

A federal approach that emerges from these efforts would have several important implications. First, it would serve as a benchmark for state governments and could provide an important guide for privacy issues arising in non-governmental areas. In addition, federal privacy valuation guidelines could bolster the case for privacy regulations that previously have been deemed too burdensome or too expensive due to a lack of explicit cost-benefit analysis. At the same time, privacy valuation guidelines could also support more data sharing when the social benefits are sufficiently compelling. Developing a framework for privacy valuation will be critical if legislators, regulators, industry stakeholders, and civil society groups are to adapt to an evolving data landscape.

Valuing Privacy: A Necessity for Society

Contrary to what a number of large technology companies have argued, people do care about privacy, even if they are operating in a context in which protecting that privacy comes at high cost. That cost is designed to feel high because companies have a strong incentive to protect the ease with which they access Americans' data. While data sharing is necessary for the public good, so too is privacy. Developing a standardized approach to valuing privacy would both reveal how taxing the current reality can really be and help society differentiate between net negative and net positive uses of data. Only then will we be able to maximize the latter.

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