#predictive policing

I'm on tour with my new novel The Bezzle! Catch me TONIGHT (Feb 27) in Portland at Powell's. Then, onto Phoenix (Changing Hands, Feb 29), Tucson (Mar 9-12), and more!

You can barely turn around these days without encountering a think-piece warning of the impending risk of AI disinformation in the coming elections. But a recent episode of This Machine Kills podcast reminds us that these are hypothetical risks, and there is no shortage of real AI harms:

https://soundcloud.com/thismachinekillspod/311-selling-pickaxes-for-the-ai-gold-rush

The algorithmic decision-making systems that increasingly run the back-ends to our lives are really, truly very bad at doing their jobs, and worse, these systems constitute a form of "empiricism-washing": if the computer says it's true, it must be true. There's no such thing as racist math, you SJW snowflake!

https://slate.com/news-and-politics/2019/02/aoc-algorithms-racist-bias.html

Nearly 1,000 British postmasters were wrongly convicted of fraud by Horizon, the faulty AI fraud-hunting system that Fujitsu provided to the Royal Mail. They had their lives ruined by this faulty AI, many went to prison, and at least four of the AI's victims killed themselves:

https://en.wikipedia.org/wiki/British_Post_Office_scandal

Tenants across America have seen their rents skyrocket thanks to Realpage's landlord price-fixing algorithm, which deployed the time-honored defense: "It's not a crime if we commit it with an app":

https://www.propublica.org/article/doj-backs-tenants-price-fixing-case-big-landlords-real-estate-tech

Housing, you'll recall, is pretty foundational in the human hierarchy of needs. Losing your home – or being forced to choose between paying rent or buying groceries or gas for your car or clothes for your kid – is a non-hypothetical, widespread, urgent problem that can be traced straight to AI.

Then there's predictive policing: cities across America and the world have bought systems that purport to tell the cops where to look for crime. Of course, these systems are trained on policing data from forces that are seeking to correct racial bias in their practices by using an algorithm to create "fairness." You feed this algorithm a data-set of where the police had detected crime in previous years, and it predicts where you'll find crime in the years to come.

But you only find crime where you look for it. If the cops only ever stop-and-frisk Black and brown kids, or pull over Black and brown drivers, then every knife, baggie or gun they find in someone's trunk or pockets will be found in a Black or brown person's trunk or pocket. A predictive policing algorithm will naively ingest this data and confidently assert that future crimes can be foiled by looking for more Black and brown people and searching them and pulling them over.

Obviously, this is bad for Black and brown people in low-income neighborhoods, whose baseline risk of an encounter with a cop turning violent or even lethal. But it's also bad for affluent people in affluent neighborhoods – because they are underpoliced as a result of these algorithmic biases. For example, domestic abuse that occurs in full detached single-family homes is systematically underrepresented in crime data, because the majority of domestic abuse calls originate with neighbors who can hear the abuse take place through a shared wall.

But the majority of algorithmic harms are inflicted on poor, racialized and/or working class people. Even if you escape a predictive policing algorithm, a facial recognition algorithm may wrongly accuse you of a crime, and even if you were far away from the site of the crime, the cops will still arrest you, because computers don't lie:

https://www.cbsnews.com/sacramento/news/texas-macys-sunglass-hut-facial-recognition-software-wrongful-arrest-sacramento-alibi/

Trying to get a low-waged service job? Be prepared for endless, nonsensical AI "personality tests" that make Scientology look like NASA:

https://futurism.com/mandatory-ai-hiring-tests

Service workers' schedules are at the mercy of shift-allocation algorithms that assign them hours that ensure that they fall just short of qualifying for health and other benefits. These algorithms push workers into "clopening" – where you close the store after midnight and then open it again the next morning before 5AM. And if you try to unionize, another algorithm – that spies on you and your fellow workers' social media activity – targets you for reprisals and your store for closure.

WHY DATA ANALYTICS IS IMPORTANT FOR ANY BUSINESS.

The Covid-19 situation has disrupted the business environment for the worst and many businesses are at their wit’s end about their future. An advanced data solutions provider like Vuelitics can help executives and managers get the much-needed clarity about their current business and prepare for the future. Most businesses are online nowadays and the pandemic situation has forced others to do the same. Thus, data analytics has become very relevant, and in this article, we will discuss some of the methods and the importance of data analytics.

  WHAT DATA ARE WE TALKING ABOUT?

Data solution providers like Vuelitics are primarily concerned with data analytics in marketing and analyse the business website for valuable insights. For example, the bounce rate can gauge the interest your website generates among your audience as a higher bounce rate is not desirable. Similarly, we provide deep insights into other relevant data like demographics and conversion rates. Vuelitics is proficient in handling huge amounts of such data quickly with accuracy by employing state of the art tools such as Qlikview, Qliksense, and PowerBI. Thus, data analytics can offer you data related to client behavior, allowing you to customize your product.

  DATA ANALYTICS STRATEGIES

Vuelitics primarily conducts two kinds of analysis which are qualitative and quantitative analysis. As the words imply qualitative methods involve figuring out the reasons for the business performance and quantitative methods involve gathering numbers validating the reasons. However, Vuelitics also deals with various other kinds of strategies like text analysis, statistical analysis, and diagnostic analysis. Graphical analytics using tools like Qlikview offer a visual perspective to businesses, helping them to easily understand complex statistics. Vuelitics specializes in predictive analysis by employing machine learning to predict patterns and trends and prescriptive analysis by suggesting numerous plans for the future.

BENEFITS OF DATA ANALYTICS

Data analytics can be the perfect tool for this pandemic as businesses can carefully analyse their customer behaviour and optimize their customer satisfaction. Also, millennials today expect carefully curated content and product that can be customized according to the data. High-quality data solutions can also help organizations prevent security threats and cyber-attacks. It also helps businesses to compete better as they can continuously improve their product by studying user data and feedback. Analytics tools such as Power BI, Qliksense, and Qlikview help businesses to streamline their production pipeline thereby ensuring optimum customer experience.

  WHY SHOULD YOU CHOOSE VUELITICS?

Vuelitics mission is to integrate all the data points available in the client’s business using its high-performance data analytics tools and offer a comprehensive vision for business development. We specialize in guiding the business in the most profitable directions fostering optimum growth for the business. We have a systematic approach for every business that starts with a deep analysis of the business to identify the objectives and wants of the business. Equipped with the best tools in BI like Qlikview, Qliksense, and Power BI, we then chart a path to achieve those objectives and monitor the results for continuous development.

In their last episode of the season, Felix and Mihir explore the prospects for media outlets like Vice and Buzzfeed and discuss predictive policing. 

Jacques Peretti, The Guardian, 31 July 2017

In Minority Report, the 2002 movie adaptation of the Philip K Dick novel, Tom Cruise plays a police officer in the LAPD “pre-crime” unit. Using the premonitions of sentient mutants called “pre-cogs”, the police are able to predict when someone is going to commit a crime before it happens, swooping down from helicopters and arresting them on the street before they can do anything. Their “crime” is that they merely thought about it.

Palantir, the CIA-backed startup, is Minority Report come true. It is all-powerful, yet no one knows it even exists. Palantir does not have an office, it has a “SCIF” on a back street in Palo Alto, California. SCIF stands for “sensitive compartmentalised information facility”. Palantir says its building “must be built to be resistant to attempts to access the information within. The network must be ‘airgapped’ from the public internet to prevent information leakage.”

Palantir’s defence systems include advanced biometrics and walls impenetrable to radio waves, phone signal or internet. Its data storage is blockchained: it cannot be accessed by merely sophisticated hacking, it requires digital pass codes held by dozens of independent parties, whose identities are themselves protected by blockchain.

What is Palantir protecting? A palantir is a “seeing stone” in JRR Tolkien’s The Lord of the Rings; a dark orb used by Saruman to be able to see in darkness or blinding light. “Palantir” means “one that sees from afar”, a mythical instrument of omnipotence.

In 2004, Peter Thiel--the billionaire PayPal co-founder, Facebook investor and latter-day Trump ally--created Palantir alongside Nathan Gettings, Joe Lonsdale, Stephen Cohen and Alex Karp. Their intention was to create a company that took Big Data somewhere no one else dared to go. In 2013, Karp, Palantir’s CEO, announced that the company would not be pursuing an IPO, as going public would make “running a company like ours very difficult”. This is why.

Palantir watches everything you do and predicts what you will do next in order to stop it. As of 2013, its client list included the CIA, the FBI, the NSA, the Centre for Disease Control, the Marine Corps, the Air Force, Special Operations Command, West Point and the IRS. Up to 50% of its business is with the public sector. In-Q-Tel, the CIA’s venture arm, was an early investor.

Palantir tracks everyone from potential terrorist suspects to corporate fraudsters (Bernie Madoff was imprisoned with the help of Palantir), child traffickers and what they refer to as “subversives”. But it is all done using prediction.

In Iraq, the Pentagon used Palantir software to track patterns in roadside bomb deployment and worked out garage-door openers were being used as remote detonators by predicting it.

Palantir allowed the marines to upload DNA samples from remote locations and tap into information gathered from years of collecting fingerprints and DNA evidence, the results returned almost immediately.

Without Palantir, suspects would have already moved on to a different location by the time the field agents received the results. Using the most sophisticated data mining, Palantir can predict the future, seconds or years before it happens. Samuel Reading--a former marine who has worked in Afghanistan for NEK Advanced Securities Group, a US military contractor--has said: “It’s the combination of every analytical tool you could ever dream of. You will know every single bad guy in your area.”

Palantir is at the heart of the US government, but with its other arm, Palantir Metropolis, it provides the analytical tools for hedge funds, banks and financial services firms to outsmart each other.

Palantir does not just provide the Pentagon with a machine for global surveillance and the data-efficient fighting of war, it runs Wall Street, too. Palantir is exactly what it says it is: a giant digital eye like Saruman’s seeing stone in The Lord of the Rings.

On the streets of Chicago and Los Angeles, Palantir is getting closest to Philip K Dick’s vision of the future, now. In the film, a premonition of an Orwellian thought-police state, crime rates drop to zero as the pre-crime unit successfully imprisons thousands of individuals for merely thinking of committing a felony.

However, when Cruise’s character begins to question the morality of what he is doing, his superiors detect a threat to the entire pre-crime programme. In order to get rid of him, Cruise is framed for a murder by altering the data of his thought history. In the final showdown with his boss, it is explained to Cruise that sometimes the numbers need to lie for the greater good of society.

Minority Report is set in 2054, but Palantir is putting pre-crime into operation now. The Los Angeles Police Department has used Palantir to predict who will commit a crime by swooping Minority Report-style on suspects. Palantir calls its work with the LAPD “improving situational awareness, and responding to crime in real time”.

Algorithms take in data on the location, time and date of previously committed crimes and this data is superimposed to create hotspots on a map for police officers to patrol. A 2013 video about “predictive policing” by the National Science Foundation features an officer explaining how they used one of these maps to prevent an assault “before it happened”.

Military-grade surveillance technology has now migrated from Fallujah to the suburban neighbourhoods of LA. Predictive policing is being used on illegal drivers and petty criminals through a redeployment of techniques and algorithms used by the US army dealing with insurgents in Iraq and with civilian casualty patterns.

When the US is described as a “war zone” between police and young black males, it is rarely mentioned that tactics developed by the US military in a real war zone are actually being deployed. Is predictive policing as a counter-insurgency tactic a contributing factor in the epidemic of police shootings of unarmed black men in the past four years?

One could argue that sophisticated pre-crime algorithms are not necessary when being black and male is seen as reason enough for the police to swoop. What predictive policing has done is militarise American cities, creating a heightened culture of suspicion and fear in areas where tensions are highest and policing is already most difficult. Officers being led to certain neighbourhoods solely because of an algorithm is enough to cause tension; enough to ignite a powder keg and push a delicate policing situation over the edge.

Ana Muniz is an activist and researcher who works with the Inglewood-based Youth Justice Coalition. “Any time that a society’s military and domestic police become more similar, the lines blur,” she told LA Weekly. “The military is supposed to defend the territory from external enemies, that’s not the mission of the police--they’re not supposed to look at the population as an external enemy.”

In 2013, TechCrunch obtained a leaked report on the use of Palantir by the LA and Chicago police departments. Sgt Peter Jackson of the LAPD was quoted as saying: “Detectives love the type of information [Palantir] provides. They can now do things that we could not do before.”

Palantir is immensely secretive. It wields as much real-world power as Google, Facebook, Amazon, Microsoft and Apple, but unlike them, Palantir operates so far under the radar, it is special ops.

The New Inquiry is proud to announce the launch of a new law enforcement app, WHITE COLLAR CRIME RISK ZONES, which harnesses the power of predictive policing technology to locate white collar crime. 

The deployment of the IoT in Public Safety market is steering law enforcement away from historical crime mapping and toward accurate, real-time threat prevention. Legacy surveillance setups required human security personnel to monitor dozens of video monitors simultaneously—a practice highly prone to fatigue and missed details. Modern connected ecosystems use edge-computed video analytics to scan live video feeds for specific risk indicators, like left-behind packages, erratic driving behaviors, or crowd pile-ups. When an anomaly is detected, the system flags the exact coordinate for human review, allowing patrol teams to intervene before an incident escalates.

This proactive operational stance changes how police forces allocate their daily field personnel. Instead of deploying patrols randomly across a city, command centers leverage predictive analytics that combine real-time sensor data with historical incident records. For instance, if localized weather sensors detect heavy fog combined with automated transit data showing high pedestrian density, traffic enforcement can be proactively positioned at high-risk intersections. This optimization ensures that limited public resources are deployed precisely where they can prevent accidents and deter criminal behavior most effectively.

The global commercial scale of this technology reflects its widespread adoption across modern security departments. The IoT in Public Safety market was valued at USD 1,181 Million in 2023 and is projected to grow to USD 2,972 million by 2030, with a compound annual growth rate (CAGR) of 14.6% from 2024 to 2030. This financial expansion is driven by the clear return on investment that smart security systems offer. By reducing property damage, lowering crime rates, and streamlining administrative reporting workloads, connected safety platforms easily pay for themselves over their operational lifecycles.

Artificial intelligence is redefining border security in the USA, especially along the US-Mexico border, through automated surveillance and predictive systems. With cutting-edge tools like drones, facial recognition, and real-time sensors, AI border security USA technology aims to improve border enforcement efficiency while balancing civil liberties. This comprehensive guide explores the…