Big Data: Reconciling Privacy, Antitrust, and Data-Generating Patents

computers in workplace bioethics

Data-Generating Patents require a broad ethical approach that incorporates business ethics. Ethics should that adhere to the spirit behind antitrust law and competition to protect consumers. Intellectual property rights are expanding. Data-generating patents can preclude competitors from obtaining, collecting, or generating the same type of data. It also deprives people of control over their data and privacy. Trade secret law protects the data generated by the technology. The patents provide a windfall of market share in the data market which is not the market of the technology or biomedical device patented. (e.g., if a patented search engine of social media outlet collects data from millions of people, trade secret law protects the actual data longer than a patent would; Myriad Genetics patented the BRCA testing data resulting from its technology giving them exclusive access to the breast cancer genetic data.)

Big Data & Trade Secret Protection

In Association for Molecular Pathology v. Myriad Genetics, Inc., the Supreme Court held that natural sequences of DNA (gDNA) were unpatentable but that cDNA is synthetic and therefore patentable. Brenda Simon and Ted Sichelman note that even after losing the patents on most of the products and the impending expiration of others, Myriad continues to use trade secret law to protect its database of patient information. Trade secret law does not have an end date so the ability to create a monopoly, barrier of entry to competing businesses, or to use big data as an advantage in marketing and producing other products is great. The market control can inhibit innovation and access to data for the public good or public health, hurting consumers and the public.

Privacy in the Data Windfall

Privacy poses an additional problem. Data-generating patents and many products that generate data put data exclusively in the hands of the products’ creator. The general public may not be aware of the data’s collection and use. The data is also often separate and distinct from the product. That is, someone may use an Apple watch without realizing what biometric and other personal data including time and place data Apple will then own or control. The audio information collected could track a conversation, its time and place. That audio includes people near the watch, not only the wearer of the watch. Apple’s patents refer to “additional sensor data”, data clusters, and personal characterization data. The data could provide helpful information to the user, but also could provide information to other actors (e.g., traffic data to the government) or to classify users by habits like staying up late. Tracking routine activities gives companies a marketing advantage in products completely unlike the products that led to the data collection.

Photo by Markus Spiske on Unsplash

Data Fairness

Monopoly behavior, privacy breaches, and the marketing advantages are just the surface of the ethical issues. In Barcode Me, I explore the concept of paying individuals for the data collected. Additional issues include bias and how goods and services are marketed based on stereotyping, preference assumptions based on behaviors, and how the marketing itself can feed many divides. For example, companies will aim ads for inexpensive, packaged foods at people eating inexpensive, packaged foods. They will aim ads for healthy organic foods and corresponding lifestyle products at people eating organic foods. Companies expand the snapshot using stereotypes and the ads further behavioral divides. When an expensive product generates data, large data sets may leave low-income consumers out altogether. Data skewed toward the wealthy leads to broad conclusions that may affect public health, public policy, corporate behavior, and health care. Furthering the divide in a consumer way can lead to further political and economic polarization and affect health disparities.

Tech Ethics & Antitrust

The deeper ethical issues of how we want tech companies or discoveries regulated speak to who should benefit from technology and how. Overregulation would deprive the population of the benefits of big data, yet a failure to protect consumers leaves them vulnerable to monopoly behaviors, high prices, stereotyping, and a lack of control over their own data. A multiangled approach could look to using current antitrust laws and to modernizing antitrust laws to solve some of the issues and require products to create better ways for consumers to limit data collection.

Photo by Marvin Meyer on Unsplash

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