Surveillance Creep and its Sinister Impacts
What happens when surveillance measures first installed for beneficial purposes are later used for more sinister purposes?
What is surveillance creep?
“Surveillance creep” is the idea that surveillance measures first installed for beneficial purposes are later used for more sinister purposes. While surveillance has always been about collecting data, it has now stretched into collecting much more personal information. While a type of surveillance may seem reasonable initially, its intentions past its initial purpose are mainly unknown and perverse. For example, with the rise of technologies to help people work from home comes the ability for employers to surveil their employees without their knowledge or at odd hours.
Social media is one example of this type of surveillance. While having access to your friends and family online may seem like a simple and effective type of digital monitoring, this can lead to data collection and targeted advertising which is far less simple. A person’s use of social media also acts as a type of peer surveillance, where the watched watch each other, thus giving even more power to the watcher. While many social media users are aware of small data collection on their sites, they continue to use the platform and give it their information willingly due to the addictive qualities of online social networking. Even data collection from advertising agencies seems light when compared to the potential threats of fraud and identity theft that can come from social media sites. The idea of social media and data collection has become so normalized that the threats of more sinister crimes are occurring more often.
According to experts, “Companies like Clearview AI, Japanese tech giant NEC, iOmnicient, Hert Security LLC, and Idemia are happy to sell facial recognition systems to the police.” It may seem simple and effective, leading to finding criminals and missing persons, and even allowing people to unlock their phones with a glance. However, this technology is not always accurate; there are many accounts of racial bias and misidentification when using facial recognition. Because the cameras being used for facial recognition do not recognize darker skin well, these demographics tend to be negatively affected when it comes to facial recognition searches.
How to help
Be cautious and aware of the technology around you–the location tracking on your phone, apps that use facial recognition such as AI art programs, background app refresh, targeted ads, and more.
If the government and large corporations wish to use surveillance as a way to creep into daily life for regular citizens, people should have the right to contest that and need to if they wish to maintain autonomy within the current political power dynamic stretching throughout the world.