physics

Predictive policing in the United States

Predictive policing in the United States is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Predictive policing in the United States rather than just read about it. In short: In the United States, the practice of predictive policing has been implemented by police departments in several states such as California, Washington, South Carolina, Alabama, Arizona, Tennessee, New York, and Illinois. Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity.

Key takeaways

Predictive policing in the United States belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Predictive policing in the United States to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Predictive policing in the United States from memory before moving on to harder problems.

Reference excerpt

In the United States, the practice of predictive policing has been implemented by police departments in several states such as California, Washington, South Carolina, Alabama, Arizona, Tennessee, New York, and Illinois. Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. Predictive policing methods fall into four general categories: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators' identities, and methods for predicting victims of crime. In the United States, the technology has been described in the media as a revolutionary innovation capable of "stopping crime before it starts". However, a RAND Corporation report on implementing predictive policing technology describes its role in more modest terms:

Predictive policing methods are not a crystal ball: they cannot foretell the future. They can only identify people and locations at increased risk of crime ... the most effective predictive policing approaches are elements of larger proactive strategies that build strong relationships between police departments and their communities to solve crime problems. In November 2011, TIME Magazine named predictive policing as one of the 50 best inventions of 2011, using the term "pre-emptive policing".

Methodology Predictive policing uses data on the times, locations and nature of past crimes, to provide insight to police strategists concerning where, and at what times, police patrols should patrol, or maintain a presence, in order to make the best use of resources or to have the greatest chance of deterring or preventing future crimes. This type of policing detects signals and patterns in crime reports to anticipate if crime will spike, when a shooting may occur, where the next car will be broken into, and who the next crime victim will be. Algorithms are produced by taking into account these factors, which consist of large amounts of data that can be analyzed. The use of algorithms creates a more effective approach that speeds up the process of predictive policing since it can quickly factor in different variables to produce an automated outcome. From the predictions the algorithm generates, they should be coupled with a prevention strategy, which typically sends an officer to the predicted time and place of the crime. The use of automated predictive policing supplies a more accurate and efficient process when looking at future crimes because there is data to back up decisions, rather than just the instincts of police officers. By having police use information from predictive policing, they are able to anticipate the concerns of communities, wisely allocate resources to times and places, and prevent victimization. Police may also use data accumulated on shootings and the sounds of gunfire to identify locations of shootings. The city of Chicago uses data blended from population mapping crime statistics, and whether to improve monitoring and identify patterns. PredPol, founded in 2012 by a UCLA professor, is one of the market leaders for predictive policing software companies. Its algorithm is formed through an examination of the near-repeat model, which infers that if a crime occurs in a specific location, the properties and land surrounding it are at risk for succeeding crime. This algorithm takes into account crime type, crime location, and the date and time of the crime in order to calculate predictions of future crime occurrences. Another software program that is utilized for predictive policing is operation LASER, which is used in Los Angeles to attempt to reduce gun violence. However, LASER was discontinued in 2019 due to a list of reasons, but specifically because of the inconsistencies when labeling people. Furthermore, some police departments have also discontinued their usage of the program given the racial-biases and ineffective methods associated with it. While the idea behind the predictive policing model is helpful in some ways, it has always had the potential to technologically reiterate social biases, which would inevitably increase the pre-existing patterns of inequality. The models used are not typically built on any direct assumptions about the data or what might cause crime. This is with the intent of removing human judgement and the opportunity for bias that comes with it from the equation however bias within the model may be unavoidable if the data used to build the models is itself biased as predictive models are only able to replicate patterns found in existing data. Furthermore, while many models avoid using race, gender, location, or other sensitive and potentially biasing variables, it is extremely difficult to eliminate all proxies for such variables due to correlations between them and much of the other data available to law enforcement which is used by the models.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Predictive policing in the United States

Start with the simplest possible case. Write down what Predictive policing in the United States claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Predictive policing in the United States before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Predictive policing in the United States ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Predictive policing in the United States

In research: Predictive policing in the United States appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Predictive policing in the United States in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Predictive policing in the United States is common in secondary-school and first-year university syllabi. It links to neighbouring topics Criminology, Law enforcement in the United States, so understanding it makes those chapters shorter.
In everyday life: Look for Predictive policing in the United States outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Predictive policing in the United States in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Predictive policing in the United States means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Predictive policing in the United States out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Predictive policing in the United States in simple terms?

Why does Predictive policing in the United States matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Predictive policing in the United States?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Predictive policing in the United States.