marketing and advertisement targeting. A recent paper from the Rand Corporation claims "privacy is not the opposite of sharing – rather, it is control over sharing." Internet privacy concerns arise from the surrender of personal information to engage in a variety of acts, from transactions to commenting in online forums. Protection against invasions of online privacy will require individuals to make an effort informing and protecting themselves via existing software solutions, to pay premiums for such protections or require individuals to place greater pressure on governing institutions to enforce privacy laws and regulations regarding consumer and personal information. Impact of internet surveillance tools on marginalized communities Internet privacy issues also affect existing class distinctions in the United States, often disproportionately impacting historically marginalized groups typically classified by race and class. Individuals with access to private digital connections that have protective services are able to more easily prevent data privacy risks of personal information and surveillance issues. Members of historically marginalized communities face greater risks of surveillance through the process of data profiling, which increases the likelihood of being stereotyped, targeted, and exploited, thus exacerbating pre-existing inequities that foster uneven playing fields. There are severe, and often unintentional, implications for big data which results in data profiling. For example, automated systems of employment verification run by the federal government such as E-verify tend to misidentify people with names that do not adhere to standardized Caucasian-sounding names as ineligible to work in the United States, thus widening unemployment gaps and preventing social mobility. This case exemplifies how some programs have bias embedded within their codes. Tools using algorithms and artificial intelligence have also been used to target marginalized communities with policing measures, such as using facial recognition softwares and predictive policing technologies that use data to predict where a crime will most likely occur, and who will engage in the criminal activity. Studies have shown that these tools exacerbate the existing issue of over-policing in areas that are predominantly home to marginalized groups. These tools and other means of data collection can also prohibit historically marginalized and low-income groups from financial services regulated by the state, such as securing loans for house mortgages. Black applicants are rejected by mortgage and mortgage refinancing services at a much higher rate than white people, exacerbating existing racial divisions. Members of minority groups have lower incomes and lower credit scores than white people, and often live