Source URL: https://algorithmwatch.org/en/algorithmic-policing-explained/
Source: AlgorithmWatch
Title: Algorithmic Policing: When Predicting Means Presuming Guilty
Feedly Summary: Algorithmic policing refers to practices with which it is allegedly possible to “predict” future crimes and detect future perpetrators by using algorithms and historic crime data. We explain why such practices are often discriminatory, do not hold up to what they promise, and lack a legal justification.
AI Summary and Description: Yes
**Summary:** The text discusses the implications of predictive policing, particularly its reliance on AI systems and algorithms that suggest potential criminal activity based on data analysis. It highlights the risks of bias and discrimination inherent in such systems, especially against minority groups, and examines the legal frameworks governing their use in Europe. The analysis reveals significant concerns about data accuracy, privacy violations, and the potential for systemic racial profiling.
**Detailed Description:** The text provides a comprehensive overview of predictive policing, focusing on the following key points:
– **Definition and Functionality:**
– Predictive policing employs AI systems to identify potential crime hotspots and individuals likely to commit crimes based on historical data and deep learning algorithms.
– It utilizes big data to develop profiles, often leading to racial and ethnic discrimination.
– **Real-world Applications and Consequences:**
– The Berlin kbO system exemplifies how predictive policing is implemented in neighborhoods, disproportionately affecting minority communities.
– Increased police presence in “predicted” hotspots creates a feedback loop that heightens crime statistics, further justifying targeting of these areas.
– **Algorithmic Discrimination:**
– The systems can lead to false positives, as seen in alarming accuracy rates from various studies (e.g., only 0.3% accuracy in the PNR checks).
– These systems perpetuate discrimination, as seen in the historical context of racial profiling and biases toward marginalized groups.
– **Legal and Ethical Concerns:**
– Major legal ramifications exist, especially in Europe, where the Law Enforcement Directive and the AI Act impose restrictions on the use of AI for predictive policing.
– The German Federal Constitutional Court found certain uses of the Palantir system unconstitutional, raising questions about data privacy and the right to informational self-determination.
– **Broader Implications for Justice:**
– The systemic issues in AI deployment reflect broader societal inequities, raising ethical concerns about the use of technology in law enforcement.
– Examples show that unchecked predictive algorithms can result in severe personal and societal repercussions, reinforcing the need for stringent regulations and oversight.
This text is critical for security and compliance professionals, particularly those in law enforcement and legal frameworks regarding AI, as it underscores the ethical and operational risks associated with algorithmic policing and the necessity for accountability in the deployment of such technologies.