How Hacking Harms Open Data Access
Since the dawn of data, the debate over who has ownership has vexed societies and their courts. From physical property to digital data, we continuously chase the legal nuances every medium. Each time we build morality and legal precedent around who holds claim to the original and who can copy it. Can you make a copy of a movie you purchased? Yes. Can you sell that copy? No. Can you sell the original copy you bought? Yes. As you can see, it’s complicated.
Let’s use photographs to illustrate: ownership over data is just like a picture. The camera owner takes a photo, that photo can be copied with the owner’s permission, and each holder of the photo is the owner of that copy. The complexity, when overlayed with internet-based data aggregation, is that copies are made at the time of viewing (data has to be “copied” to your phone to view that email). Alas, for the internet, data ownership is intertwined with data access.
The ownership quandary gets even more complicated when we pile on applications whose mission is to intercept information between apps. Take, for example, a gig driver at a company like Uber or Lyft. The way drivers currently get each job is through dispatch referencing a driver’s parameters against a rider’s needs and the company’s desire to ensure every customer is able to quickly hire a vehicle. A driver may be willing to transport someone x amount of miles, and so dispatch will assign that driver a rider within that distance. However, when we introduced privileged information (data not accessible to the general public), those with access to that data gain unfair advantage (think insider trading). There are several popular creators online that leverage algorithms and applications to access this hidden information; focusing on everything from how to decline short-distance and low-value jobs to non-tippers to bad merchants.
This data extraction is often referred to as “trip transparency.” It allows the driver to see distance, tip, merchant, customer, and earnings data that one’s peers cannot through the use of an intercepting code that hacks the communication stream between a gig app and gig dispatch. If that sounds like a misuse of English, trust your instincts. Now a driver with this privileged information knows what jobs will require the least amount of work for the highest amount of pay. There is a reason why platforms are not sharing this information with their workforce – it’s bad for business. One can easily see how such information creates a wide data gap between drivers and harms consumers, causing extended wait times or fares that may not be picked up.
Besides the obvious stratification pitfalls, this process also touches upon the 3rd rail of data aggregation – who owns the data?
A recent Supreme Court ruling, Van Buren, refreshed the Computer Fraud and Abuse Act by defining hacking in a gate-open/gate-closed framework. Gates that are open for a user are ones they have the required access level to enter (i.e. login credentials). Gates that are closed are ones that they do not have access to. Circumventing the gate is hacking.
In many ways, this hacking is like a virus, “infecting” gig platform networks by leaking out information that negatively impacts the overall workforce and consumers. Platforms currently only have blunt tools to combat this — draconian lockdowns of their systems to eradicate the virus.
My company, Argyle, which only transmits gate-open data (like paystubs) has seen its user base impacted by these nefarious actors as well. Further, the dignity of work is in question when workers are trying to optimize their earnings down to the minute like a computer.
While Argyle is able to complete our functions for clients and consumers, I’m frustrated that these apps have made the lives of 600,000+ gig workers harder – workers who use Argyle to facilitate insurance, gas, loans, and pay bills. An unruly minority has disrupted normal commerce and a hard line needs to be drawn.
When we access the system appropriately, only using open gates, businesses can utilize the data in ways that significantly improve their services and result in truly meaningful financial access for consumers. Open gates generate better public data (for the use of everyone), reduce fraud through verification, and create simplicity for consumers. For Argyle, in particular, this means real-time streaming data can help gig workers get a car loan, an apartment, a job, or their pay early (earned wage access).
Hacking these systems may seem like a win over Goliath for a minority of folks that have the ability to access otherwise undisclosed information, but the greater good is only achieved when people copy a photo they truly have the ability to access.