Algorithmic policing of queer sexuality reproduces moral hierarchies by categorizing acceptable and deviant identities based on societal norms and expectations. This process reinforces power structures that marginalize individuals who do not conform to these standards and perpetuates discrimination against them. Through algorithms, the law enforcement system can identify potential deviants and target them for surveillance and monitoring, creating an environment where nonconformity is punished.
One way algorithmic policing manifests itself is through predictive policing techniques. Predictive policing uses data analytics to forecast crime patterns and deploy resources accordingly. It has been used in many cities across the United States, including Chicago, Los Angeles, New York City, and Philadelphia. The technology analyzes historical crime data, social media posts, demographic information, weather reports, and other factors to determine which areas are more likely to experience criminal activity.
This approach often ignores contextual factors such as poverty, racism, and discrimination. As a result, it disproportionately affects communities of color and increases their risk of being profiled.
The use of algorithms also extends beyond law enforcement agencies into other institutions such as schools, workplaces, and healthcare facilities.
Facial recognition software can be used to monitor students' gender expression and clothing choices at school. Employers may use artificial intelligence (AI) to screen job applicants based on their sexual orientation or gender identity. Healthcare providers might rely on AI to detect HIV/AIDS-related stigmas among patients seeking medical care. While these technologies aim to improve safety and efficiency, they reinforce existing power dynamics that privilege heteronormative ideals over queer identities.
Algorithmic policing further exacerbates existing power imbalances by limiting access to resources for marginalized individuals. By monitoring online behavior, law enforcement can identify individuals who seek out support from LGBTQ+ organizations or explore nontraditional relationships. This surveillance creates an environment where people cannot freely express themselves without fear of punishment or judgment.
Algorithmic policing can lead to the mislabeling of innocent activities as deviant behaviors, leading to unnecessary arrests and incarceration.
Algorithmic policing reinforces traditional gender roles by associating certain behaviors with masculinity or femininity. The algorithm may classify transgender individuals under their assigned gender rather than their chosen one, leading to discrimination against them in the criminal justice system. The same is true for individuals with fluid identities, such as those who do not conform to binary labels. These individuals are often seen as 'deviant' because they challenge societal norms about what it means to be a man or woman.
Algorithmic policing perpetuates moral hierarchies that differentiate acceptable from deviant identities. It disproportionately affects communities of color and increases their risk of being profiled. Moreover, it limits access to resources and promotes stereotypes that restrict self-expression and expression. To address these issues, society must reevaluate its attitudes towards queer sexuality and recognize all identities as valid. We must also demand more transparency and accountability from institutions that use algorithms to monitor our behavior. Only then can we create a safer and more equitable world for everyone.
How does algorithmic policing of queer sexuality reproduce moral hierarchies that differentiate acceptable from deviant identities?
Algorithmic policing of queer sexuality reproduces moral hierarchies by promoting heteronormative standards and reinforcing gender binaries through its categorization of individuals based on their sexual orientation and gender identity. It often uses binary classifications that do not account for non-binary genders and sexual orientations, which can lead to misidentification and exclusion.