Other
The data revolution: privacy, politics and predictive policing
The EconomistDr Tom Devlin, Trump, Nick Bowers, Carol Reed, Hal Hodson, David Carroll, Mark Zuckerberg, Jamie Garcia, Hamid Khan, Sergeant David Rich, Anthony, Leo Hu
- Data-driven medical tools are expected to increase patient cures and survival rates, with AI-powered services projected to reach a value of $6.6 billion by 2021.
- The deployment of these technologies aims to significantly reduce the time required to establish definitive care for stroke patients, thereby mitigating the risk of brain tissue death and potential long-term deficits such as right-side weakness and speech impairment.
- The volume of connected devices collecting user data is forecast to reach 31 billion globally by 2020, a trend that will intensify the use of automated tools like cookies to track web activity and tailor advertising.
- Predictive policing systems like PredPol face risks of creating feedback loops that reinforce biased data, disproportionately impacting Black and poor communities, while the increased presence of officers may deter property crimes but does not guarantee unbiased outcomes.
- China is constructing a social credit system to monitor the trustworthiness of 1.4 billion citizens, with potential expansions to include comprehensive surveillance of online and physical activities where antisocial behaviors like jaywalking or littering could result in penalties.
- The global acceleration of the data revolution is anticipated to trigger rigorous ethical scrutiny and debates regarding corporate and government accountability, with Western checks and balances potentially offering some protection against exploitation, though their efficacy remains uncertain.
- A significant risk involves the potential for unsupervised data actions by officials and institutions, creating scenarios where entities can act without external oversight.