Data Equity

From SI410
Jump to: navigation, search

“Ethics & Data Equity” explores ethical questions and topics in the concept of data equity. Data equity is quantifying the values of big data that can be unlocked by analysis and interpretation for social and economic impacts[1]. A relatively new idea, only possible due to our modern Information Age, data equity has caused tremendous advancements to be made in information technology and a monumental increase in global data production.

The power of data equity depends in part on the technology available and how it is harnessed by individuals. Disparities in access to information technology and capabilities to harness data lead to concerning inequalities in data equity. These inequalities serve to create an uneven foundation, and disparities in data equity will serve to harm countless groups and disadvantage them in a future that is becoming increasingly data centric. This issue leads to an interesting discussion to arise, on the ethics behind data equity and the implications data equity has for the future.


Data is a powerful word in the modern 21st century, and has seeped into every facet of our daily lives. It is the information we perceive every day that serve as the basis of our reasoning and decision making, both as individuals and as a collective society.

In a technology oriented definition, data is the facts and statistics that we collect and feed into technology for computation and analysis[2]. With the rise of the Information Age and technological renaissance, the sheer amount of data produced in the world has skyrocketed at an exponential rate. In 2013, the world contained approximately 4.4 zettabytes of data[3]. By 2020, this figure is projected to be 44 zettabytes, a tenfold increase[4].

Add to this increasing supply of data new breakthroughs and processes by which to utilize data, and a recipe for social innovation emerges. From solving traffic jams[5] to creating medical breakthroughs[6] to making Amazon’s insane same day delivery possible[7], quantifying the values of big data (aka data equity) creates enormous value for data and the implications data brings to society. These impacts are completely rehauling everyday life and are on the verge of making society an information utopia of the future.

However, these advancements and breakthroughs bring with them rising ethical questions and concerns.


Equity is a term that refers to the aspect of being fair and impartial to others[8]. In a financial and economic sense, equity changes definitions to the values of goods or services[9]. Due to these definitions, equity can serve to act as a moral anchor in situations involving judgement, by introducing values of ethics and “doing the right thing”. Equity in data specifically can help to determine the values (economic and non-economic) of analyzing and understanding complex data, along with how to utilize data in a manner that is fair for all[10].

This is why the idea of data equity is an important one, and why ethical concerns in data equity need to be addressed sooner rather than later.


In a nutshell, ethics means “doing the right thing”; acting in a way that is moral and good[11]. Ethics are important in society as they serve as guidance and motivators for us, as individuals and a collective, to act and live in a manner that is just and promotes proper values for the future.

The responsibility of ethics transfers well from the physical world to the digital one, and the realm of data. Ethics in data covers a wide array of concepts in the ever expanding data world. For example[12]:

  • How does one generate and acquire data, especially from other users?
  • Which manners are appropriate in analyzing user data, and which are not?
  • What rights do users have to the data they produce, especially on platforms that are owned by others?
  • How accessible is data in general?
  • Do I as a user have a say in when a company can and cannot collect data on me when I use their services?
  • What data can be shared, and what data is strictly private?
  • How do algorithms play a role in data development, and what are the tenants to responsibly using data?
  • What is the morality behind performing [xyz action] with the data I obtain?

To further understand these questions and the importance of ethics around data equity, take a look at the example below.

Ethics & Data Equity - An Example with Public Health

Public health is a field that is driven by the cause of improving the population and well being of entire populations. Data is crucial for this field, as data informs the actions in health policy, strategy, and health interventions that can be enacted by public health professionals.

With the introduction of technology trends such as healthcare apps, wearables, the digitalization of medical records, and advanced medical intervention tools, the data available to public health professionals has drastically expanded and increased in quality[13]. With this, so have the ethical questions and implications around how public health data and individual health data is utilized.

There are several layers of red tape around public health and medical data that public health professionals utilize, on federal and state levels. Introducing technology to increase the scope of data that can be created (through advanced and near constant tracking capabilities of individuals through wearables, for example[14]) raises several questions onto how much data from users can be gathered and utilized ethically, along with what data can be shared to other parties, along with how to navigate the complex privacy laws already set in place for this type of data.

Additionally, the issue of data equity emerges as it becomes questionable into who exactly has access to this data, what are their intentions in using the data, do users themselves have proper access to the data they create, and do users have a say in who else obtains this private data.

Finally, socioeconomic status and accessibility to data/data technology become a greater issue here. Much of the advancements in data creation and analysis (the equity or value of the data) come from technological advancements. However, the technology implementations are quite expensive. One popular wearable, the Apple Watch, costs $349[15], a hefty price for poverty stricken and lower income portions of the world. Stemming from this vein, advanced technological capabilities, lab resources, and tools for public health professionals are quite expensive as well. In a field that is so competitive with regards to funding and essentially underfunded, it is almost impossible to provide public health professionals around the world equal opportunities and tools to properly utilize data for impact[16]. Due to these issues, the value that is sought to be created from data and its equity ranges widely across the world based on available tools and resources. This inequality fails the basic premise of equity; of being fair for all. With this, discrepancies in resources and tools for data analysis and interpretation give rise to the questioning of the basic ethicality behind data equity in public health.

Ethically, this concept is tricky to navigate, as there are several social, legal, financial, and technological pressures to consider. If these issues are not solved in an ethical manner and if data equity is not properly scaled, vast discrepancies will emerge on a global scale of how data is used and the positive impacts it creates around the world (in a public health sense). Essentially, areas of lower income and less resource availability will suffer due to less accessible data, data analysis resources, and lackluster implementation tools, while areas of higher income do not.

This is the risk of inequality in data equity, and the shortcoming of ethics that emerges if data equity is not truly upheld.

See Also