Race and Privacy in Broadcast Police Communications
- URL: http://arxiv.org/abs/2407.01817v1
- Date: Mon, 1 Jul 2024 21:34:51 GMT
- Title: Race and Privacy in Broadcast Police Communications
- Authors: Pranav Narayanan Venkit, Christopher Graziul, Miranda Ardith Goodman, Samantha Nicole Kenny, Shomir Wilson,
- Abstract summary: We examine the Chicago Police Department's (CPD's) use of broadcast police communications (BPC) to coordinate activity of law enforcement officers (LEOs) in the city.
From a recently assembled archive of 80,775 hours of BPC associated with CPD operations, we analyze text transcripts of radio transmissions broadcast 9:00 AM to 5:00 PM on August 10th, 2018 in one majority Black, one majority white, and one majority Hispanic area.
We explore the vocabulary and speech acts used by police in BPC, comparing mentions of personal characteristics to local demographics, the personal information shared over BPC, and the
- Score: 3.034710104407876
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Radios are essential for the operations of modern police departments, and they function as both a collaborative communication technology and a sociotechnical system. However, little prior research has examined their usage or their connections to individual privacy and the role of race in policing, two growing topics of concern in the US. As a case study, we examine the Chicago Police Department's (CPD's) use of broadcast police communications (BPC) to coordinate the activity of law enforcement officers (LEOs) in the city. From a recently assembled archive of 80,775 hours of BPC associated with CPD operations, we analyze text transcripts of radio transmissions broadcast 9:00 AM to 5:00 PM on August 10th, 2018 in one majority Black, one majority white, and one majority Hispanic area of the city (24 hours of audio) to explore three research questions: (1) Do BPC reflect reported racial disparities in policing? (2) How and when is gender, race/ethnicity, and age mentioned in BPC? (3) To what extent do BPC include sensitive information, and who is put at most risk by this practice? (4) To what extent can large language models (LLMs) heighten this risk? We explore the vocabulary and speech acts used by police in BPC, comparing mentions of personal characteristics to local demographics, the personal information shared over BPC, and the privacy concerns that it poses. Analysis indicates (a) policing professionals in the city of Chicago exhibit disproportionate attention to Black members of the public regardless of context, (b) sociodemographic characteristics like gender, race/ethnicity, and age are primarily mentioned in BPC about event information, and (c) disproportionate attention introduces disproportionate privacy risks for Black members of the public.
Related papers
- PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action [54.11479432110771]
PrivacyLens is a novel framework designed to extend privacy-sensitive seeds into expressive vignettes and further into agent trajectories.
We instantiate PrivacyLens with a collection of privacy norms grounded in privacy literature and crowdsourced seeds.
State-of-the-art LMs, like GPT-4 and Llama-3-70B, leak sensitive information in 25.68% and 38.69% of cases, even when prompted with privacy-enhancing instructions.
arXiv Detail & Related papers (2024-08-29T17:58:38Z) - The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models [67.38144169029617]
We map the sociodemographics and stated preferences of 1,500 diverse participants from 75 countries, to their contextual preferences and fine-grained feedback in 8,011 live conversations with 21 Large Language Models (LLMs)
With PRISM, we contribute (i) wider geographic and demographic participation in feedback; (ii) census-representative samples for two countries (UK, US); and (iii) individualised ratings that link to detailed participant profiles, permitting personalisation and attribution of sample artefacts.
We use PRISM in three case studies to demonstrate the need for careful consideration of which humans provide what alignment data.
arXiv Detail & Related papers (2024-04-24T17:51:36Z) - White Men Lead, Black Women Help? Benchmarking Language Agency Social Biases in LLMs [58.27353205269664]
Social biases can manifest in language agency.
We introduce the novel Language Agency Bias Evaluation benchmark.
We unveil language agency social biases in 3 recent Large Language Model (LLM)-generated content.
arXiv Detail & Related papers (2024-04-16T12:27:54Z) - A Causal Framework to Evaluate Racial Bias in Law Enforcement Systems [13.277413612930102]
We present a multi-stage causal framework incorporating criminality.
In settings like airport security, the primary source of observed bias against a race is likely to be bias in law enforcement against innocents of that race.
In police-civilian interaction, the primary source of observed bias against a race could be bias in law enforcement against that race or bias from the general public in reporting against the other race.
arXiv Detail & Related papers (2024-02-22T20:41:43Z) - Datastore Design for Analysis of Police Broadcast Audio at Scale [0.0]
We describe preliminary work towards enabling Speech Emotion Recognition (SER) in an analysis of the Chicago Police Department's (CPD)
We demonstrate the pipelined creation of a datastore to enable a multimodal analysis of composed raw audio files.
arXiv Detail & Related papers (2023-10-25T19:52:19Z) - Detecting disparities in police deployments using dashcam data [16.005351901762904]
We show that disparities in police deployment levels can be quantified by detecting police vehicles in dashcam images of public street scenes.
The neighborhood with the highest deployment levels has almost 20 times higher levels than the neighborhood with the lowest.
We discuss the implications of these disparities for policing equity and for algorithms trained on policing data.
arXiv Detail & Related papers (2023-05-24T14:48:59Z) - CPED: A Large-Scale Chinese Personalized and Emotional Dialogue Dataset
for Conversational AI [48.67259855309959]
Most existing datasets for conversational AI ignore human personalities and emotions.
We propose CPED, a large-scale Chinese personalized and emotional dialogue dataset.
CPED contains more than 12K dialogues of 392 speakers from 40 TV shows.
arXiv Detail & Related papers (2022-05-29T17:45:12Z) - US Fatal Police Shooting Analysis and Prediction [13.569449459014104]
More people in the U.S. think that police use excessive force during law enforcement, especially to a specific group of people.
We proposed a new method to quantify fatal police shooting news reporting deviation of mainstream media.
We analyzed the most comprehensive US fatal police shooting dataset from Washington Post.
arXiv Detail & Related papers (2021-03-24T21:39:32Z) - The effect of differential victim crime reporting on predictive policing
systems [84.86615754515252]
We show how differential victim crime reporting rates can lead to outcome disparities in common crime hot spot prediction models.
Our results suggest that differential crime reporting rates can lead to a displacement of predicted hotspots from high crime but low reporting areas to high or medium crime and high reporting areas.
arXiv Detail & Related papers (2021-01-30T01:57:22Z) - Multi-officer Routing for Patrolling High Risk Areas Jointly Learned
from Check-ins, Crime and Incident Response Data [6.295207672539996]
We formulate the dynamic crime patrol planning problem for multiple police officers using check-ins, crime, incident response data, and POI information.
We propose a joint learning and non-random optimisation method for the representation of possible solutions.
The performance of the proposed solution is verified and compared with several state-of-art methods using real-world datasets.
arXiv Detail & Related papers (2020-07-31T23:33:14Z) - Whose Tweets are Surveilled for the Police: An Audit of Social-Media
Monitoring Tool via Log Files [69.02688684221265]
We obtained log files from the Corvallis (Oregon) Police Department's use of social media monitoring software called DigitalStakeout.
These log files include the results of proprietary searches by DigitalStakeout that were running over a period of 13 months and include 7240 social media posts.
We observe differences in the demographics of the users whose Tweets are flagged by DigitalStakeout compared to the demographics of the Twitter users in the region.
arXiv Detail & Related papers (2020-01-23T19:35:12Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.