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DOJ funding pipeline subsidizes questionable big data surveillance technologies

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DOJ funding pipeline subsidizes questionable big data surveillance technologies

Predictive policing aimed to identify crime hot spots and ‘chronic’ offenders but missed the mark.
Patrick T. Fallon for The Washington Post via Getty Images

Andrew Guthrie Ferguson, American University

Predictive policing has been shown to be an ineffective and biased policing tool. Yet, the Department of Justice has been funding the crime surveillance and analysis technology for years and continues to do so despite criticism from researchers, privacy advocates and members of Congress.

Sen. Ron Wyden, D-Ore., and U.S. Rep. Yvette Clarke, D-N.Y., joined by five Democratic senators, called on Attorney General Merrick Garland to halt funding for predictive policing technologies in a letter issued Jan. 29, 2024. Predictive policing involves analyzing crime data in an attempt to identify where and when crimes are likely to occur and who is likely to commit them.

The request came months after the Department of Justice failed to answer basic questions about how predictive policing funds were being used and who was being harmed by arguably racially discriminatory algorithms that have never been proven to work as intended. The Department of Justice did not have answers to who was using the technology, how it was being evaluated and which communities were affected.

While focused on predictive policing, the senators’ demand raises what I, a law professor who studies big data surveillance, see as a bigger issue: What is the Department of Justice’s role in funding new surveillance technologies? The answer is surprising and reveals an entire ecosystem of how technology companies, police departments and academics benefit from the flow of federal dollars.

The money pipeline

The National Institute of Justice, the DOJ’s research, development and evaluation arm, regularly provides seed money for grants and pilot projects to test out ideas like predictive policing. It was a National Institute of Justice grant that funded the first predictive policing conference in 2009 that launched the idea that past crime data could be run through an algorithm to predict future criminal risk. The institute has given US$10 million dollars to predictive policing projects since 2009.

Because there was grant money available to test out new theories, academics and startup companies could afford to invest in new ideas. Predictive policing was just an academic theory until there was cash to start testing it in various police departments. Suddenly, companies launched with the financial security that federal grants could pay their early bills.

National Institute of Justice-funded research often turns into for-profit companies. Police departments also benefit from getting money to buy the new technology without having to dip into their local budgets. This dynamic is one of the hidden drivers of police technology.

YouTube video
How predictive policing works – and the harm it can cause.

Once a new technology gets big enough, another DOJ entity, the Bureau of Justice Assistance, funds projects with direct financial grants. The bureau funded police departments to test one of the biggest place-based predictive policing technologies – PredPol – in its early years. The bureau has also funded the purchase of other predictive technologies.

The Bureau of Justice Assistance funded one of the most infamous person-based predictive policing pilots in Los Angeles, operation LASER, which targeted “chronic offenders.” Both experiments – PredPol and LASER – failed to work as intended. The Los Angeles Office of the Inspector General identified the negative impact of the programs on the community – and the fact that the predictive theories did not work to reduce crime in any significant way.

As these DOJ entities’ practices indicate, federal money not only seeds but feeds the growth of new policing technologies. Since 2005, the Bureau of Justice Assistance has given over $7.6 billion of federal money to state, local and tribal law enforcement agencies for a host of projects. Some of that money has gone directly to new surveillance technologies. A quick skim through the public grants shows approximately $3 million directed to facial recognition, $8 million for ShotSpotter and $13 million to build and grow real-time crime centers. ShotSpotter (now rebranded as SoundThinking) is the leading brand of gunshot detection technology. Real-time crime centers combine security camera feeds and other data to provide surveillance for a city.

The questions not asked

None of this is necessarily nefarious. The Department of Justice is in the business of prosecution, so it is not surprising for it to fund prosecution tools. The National Institute of Justice exists as a research body inside the Office of Justice Programs, so its role in helping to promote data-driven policing strategies is not inherently problematic. The Bureau of Justice Assistance exists to assist local law enforcement through financial grants. The DOJ is feeding police surveillance power because it benefits law enforcement interests.

The problem, as indicated by Sen. Wyden’s letter, is that in subsidizing experimental surveillance technologies, the Department of Justice did not do basic risk assessment or racial justice evaluations before investing money in a new technological solution. As someone who has studied predictive policing for over a decade, I can say that the questions asked by the senators were not asked in the pilot projects.

Basic questions of who would be affected, whether there could be a racially discriminatory impact, how it would change policing and whether it worked were not raised in any serious way. Worse, the focus was on deploying something new, not double-checking whether it worked. If you are going to seed and feed a potentially dangerous technology, you also have an obligation to weed it out once it turns out to be harming people.

Only now, after activists have protested, after scholars have critiqued and after the original predictive policing companies have shut down or been bought by bigger companies, is the DOJ starting to ask the hard questions. In January 2024, the DOJ and the Department of Homeland Security asked for public comment to be included in a report on law enforcement agencies’ use of facial recognition technology, other technologies using biometric information and predictive algorithms.

Arising from a mandate under executive order 14074 on advancing effective, accountable policing and criminal justice practices to enhance public trust and public safety, the DOJ Office of Legal Policy is going to evaluate how predictive policing affects civil rights and civil liberties. I believe that this is a good step – although a decade too late.

Lessons not learned?

The bigger problem is that the same process is happening again today with other technologies. As one example, real-time crime centers are being built across America. Thousands of security cameras stream to a single command center that is linked to automated license plate readers, gunshot detection sensors and 911 calls. The centers also use video analytics technology to identify and track people and objects across a city. And they tap into data about past crime.

A wall of monitors shows aerial and street views of a city
Real-time crime centers like this one in Albuquerque, N.M., enable police surveillance of entire cities.
AP Photo/Susan Montoya Bryan

Millions of federal dollars from the American Rescue Plan Act are going to cities with the specific designation to address crime, and some of those dollars have been diverted to build real-time crime centers. They’re also being funded by the Bureau of Justice Assistance.

Real-time crime centers can do predictive analytics akin to predictive policing simply as a byproduct of all the data they collect in the ordinary course of a day. The centers can also scan entire cities with powerful computer vision-enabled cameras and react in real time. The capabilities of these advanced technologies make the civil liberties and racial justice fears around predictive policing pale in comparison.

So while the American public waits for answers about a technology, predictive policing, that had its heyday 10 years ago, the DOJ is seeding and feeding a far more invasive surveillance system with few questions asked. Perhaps things will go differently this time. Maybe the DOJ/DHS report on predictive algorithms will look inward at the department’s own culpability in seeding the surveillance problems of tomorrow.The Conversation

Andrew Guthrie Ferguson, Professor of Law, American University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Colors are objective, according to two philosophers − even though the blue you see doesn’t match what I see

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theconversation.com – Elay Shech, Professor of Philosophy, Auburn University – 2025-04-25 07:55:00

What appear to be blue and green spirals are actually the same color.
Akiyoshi Kitaoka

Elay Shech, Auburn University and Michael Watkins, Auburn University

Is your green my green? Probably not. What appears as pure green to me will likely look a bit yellowish or blueish to you. This is because visual systems vary from person to person. Moreover, an object’s color may appear differently against different backgrounds or under different lighting.

These facts might naturally lead you to think that colors are subjective. That, unlike features such as length and temperature, colors are not objective features. Either nothing has a true color, or colors are relative to observers and their viewing conditions.

But perceptual variation has misled you. We are philosophers who study colors, objectivity and science, and we argue in our book “The Metaphysics of Colors” that colors are as objective as length and temperature.

Perceptual variation

There is a surprising amount of variation in how people perceive the world. If you offer a group of people a spectrum of color chips ranging from chartreuse to purple and asked them to pick the unique green chip – the chip with no yellow or blue in it – their choices would vary considerably. Indeed, there wouldn’t be a single chip that most observers would agree is unique green.

Generally, an object’s background can result in dramatic changes in how you perceive its colors. If you place a gray object against a lighter background, it will appear darker than if you place it against a darker background. This variation in perception is perhaps most striking when viewing an object under different lighting, where a red apple could look green or blue.

Of course, that you experience something differently does not prove that what is experienced is not objective. Water that feels cold to one person may not feel cold to another. And although we do not know who is feeling the water “correctly,” or whether that question even makes sense, we can know the temperature of the water and presume that this temperature is independent of your experience.

Similarly, that you can change the appearance of something’s color is not the same as changing its color. You can make an apple look green or blue, but that is not evidence that the apple is not red.

Apple under a gradient of red to blue light
Under different lighting conditions, objects take on different colors.
Gyozo Vaczi/iStock via Getty Images Plus

For comparison, the Moon appears larger when it’s on the horizon than when it appears near its zenith. But the size of the Moon has not changed, only its appearance. Hence, that the appearance of an object’s color or size varies is, by itself, no reason to think that its color and size are not objective features of the object. In other words, the properties of an object are independent of how they appear to you.

That said, given that there is so much variation in how objects appear, how do you determine what color something actually is? Is there a way to determine the color of something despite the many different experiences you might have of it?

Matching colors

Perhaps determining the color of something is to determine whether it is red or blue. But we suggest a different approach. Notice that squares that appear to be the same shade of pink against different backgrounds look different against the same background.

Green, purple and orange squares with smaller squares in shades of pink placed at their centers and at the bottom of the image
The smaller squares may appear to be the same color, but if you compare them with the strip of squares at the bottom, they’re actually different shades.
Shobdohin/Wikimedia Commons, CC BY-SA

It’s easy to assume that to prove colors are objective would require knowing which observers, lighting conditions and backgrounds are the best, or “normal.” But determining the right observers and viewing conditions is not required for determining the very specific color of an object, regardless of its name. And it is not required to determine whether two objects have the same color.

To determine whether two objects have the same color, an observer would need to view the objects side by side against the same background and under various lighting conditions. If you painted part of a room and find that you don’t have enough paint, for instance, finding a match might be very tricky. A color match requires that no observer under any lighting condition will see a difference between the new paint and the old.

YouTube video
Is the dress yellow and white or black and blue?

That two people can determine whether two objects have the same color even if they don’t agree on exactly what that color is – just as a pool of water can have a particular temperature without feeling the same to me and you – seems like compelling evidence to us that colors are objective features of our world.

Colors, science and indispensability

Everyday interactions with colors – such as matching paint samples, determining whether your shirt and pants clash, and even your ability to interpret works of art – are hard to explain if colors are not objective features of objects. But if you turn to science and look at the many ways that researchers think about colors, it becomes harder still.

For example, in the field of color science, scientific laws are used to explain how objects and light affect perception and the colors of other objects. Such laws, for instance, predict what happens when you mix colored pigments, when you view contrasting colors simultaneously or successively, and when you look at colored objects in various lighting conditions.

The philosophers Hilary Putnam and Willard van Orman Quine made famous what is known as the indispensability argument. The basic idea is that if something is indispensable to science, then it must be real and objective – otherwise, science wouldn’t work as well as it does.

For example, you may wonder whether unobservable entities such as electrons and electromagnetic fields really exist. But, so the argument goes, the best scientific explanations assume the existence of such entities and so they must exist. Similarly, because mathematics is indispensable to contemporary science, some philosophers argue that this means mathematical objects are objective and exist independently of a person’s mind.

Blue damselfish, seeming iridescent against a black background
The color of an animal can exert evolutionary pressure.
Paul Starosta/Stone via Getty Images

Likewise, we suggest that color plays an indispensable role in evolutionary biology. For example, researchers have argued that aposematism – the use of colors to signal a warning for predators – also benefits an animal’s ability to gather resources. Here, an animal’s coloration works directly to expand its food-gathering niche insofar as it informs potential predators that the animal is poisonous or venomous.

In fact, animals can exploit the fact that the same color pattern can be perceived differently by different perceivers. For instance, some damselfish have ultraviolet face patterns that help them be recognized by other members of their species and communicate with potential mates while remaining largely hidden to predators unable to perceive ultraviolet colors.

In sum, our ability to determine whether objects are colored the same or differently and the indispensable roles they play in science suggest that colors are as real and objective as length and temperature.The Conversation

Elay Shech, Professor of Philosophy, Auburn University and Michael Watkins, Professor of Philosophy, Auburn University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Perfect brownies baked at high altitude are possible thanks to Colorado’s home economics pioneer Inga Allison

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theconversation.com – Tobi Jacobi, Professor of English, Colorado State University – 2025-04-22 07:47:00

Students work in the high-altitude baking laboratory.
Archives and Special Collections, Colorado State University

Tobi Jacobi, Colorado State University and Caitlin Clark, Colorado State University

Many bakers working at high altitudes have carefully followed a standard recipe only to reach into the oven to find a sunken cake, flat cookies or dry muffins.

Experienced mountain bakers know they need a few tricks to achieve the same results as their fellow artisans working at sea level.

These tricks are more than family lore, however. They originated in the early 20th century thanks to research on high-altitude baking done by Inga Allison, then a professor at Colorado State University. It was Allison’s scientific prowess and experimentation that brought us the possibility of perfect high-altitude brownies and other baked goods.

A recipe for brownies at high altitude.
Inga Allison’s high-altitude brownie recipe.
Archives and Special Collections, Colorado State University

We are two current academics at CSU whose work has been touched by Allison’s legacy.

One of us – Caitlin Clark – still relies on Allison’s lessons a century later in her work as a food scientist in Colorado. The other – Tobi Jacobi – is a scholar of women’s rhetoric and community writing, and an enthusiastic home baker in the Rocky Mountains, who learned about Allison while conducting archival research on women’s work and leadership at CSU.

That research developed into “Knowing Her,” an exhibition Jacobi developed with Suzanne Faris, a CSU sculpture professor. The exhibit highlights dozens of women across 100 years of women’s work and leadership at CSU and will be on display through mid-August 2025 in the CSU Fort Collins campus Morgan Library.

A pioneer in home economics

Inga Allison is one of the fascinating and accomplished women who is part of the exhibit.

Allison was born in 1876 in Illinois and attended the University of Chicago, where she completed the prestigious “science course” work that heavily influenced her career trajectory. Her studies and research also set the stage for her belief that women’s education was more than preparation for domestic life.

In 1908, Allison was hired as a faculty member in home economics at Colorado Agricultural College, which is now CSU. She joined a group of faculty who were beginning to study the effects of altitude on baking and crop growth. The department was located inside Guggenheim Hall, a building that was constructed for home economics education but lacked lab equipment or serious research materials.

A sepia-toned photograph of Inga Allison, a white woman in dark clothes with her hair pulled back.
Inga Allison was a professor of home economics at Colorado Agricultural College, where she developed recipes that worked in high altitudes.
Archives and Special Collections, Colorado State University

Allison took both the land grant mission of the university with its focus on teaching, research and extension and her particular charge to prepare women for the future seriously. She urged her students to move beyond simple conceptions of home economics as mere preparation for domestic life. She wanted them to engage with the physical, biological and social sciences to understand the larger context for home economics work.

Such thinking, according to CSU historian James E. Hansen, pushed women college students in the early 20th century to expand the reach of home economics to include “extension and welfare work, dietetics, institutional management, laboratory research work, child development and teaching.”

News articles from the early 1900s track Allison giving lectures like “The Economic Side of Natural Living” to the Colorado Health Club and talks on domestic science to ladies clubs and at schools across Colorado. One of her talks in 1910 focused on the art of dishwashing.

Allison became the home economics department chair in 1910 and eventually dean. In this leadership role, she urged then-CSU President Charles Lory to fund lab materials for the home economics department. It took 19 years for this dream to come to fruition.

In the meantime, Allison collaborated with Lory, who gave her access to lab equipment in the physics department. She pieced together equipment to conduct research on the relationship between cooking foods in water and atmospheric pressure, but systematic control of heat, temperature and pressure was difficult to achieve.

She sought other ways to conduct high-altitude experiments and traveled across Colorado where she worked with students to test baking recipes in varied conditions, including at 11,797 feet in a shelter house on Fall River Road near Estes Park.

Early 1900s car traveling in the Rocky Mountains.
Inga Allison tested her high-altitude baking recipes at 11,797 feet at the shelter house on Fall River Road, near Estes Park, Colorado.
Archives and Special Collections, Colorado State University

But Allison realized that recipes baked at 5,000 feet in Fort Collins and Denver simply didn’t work in higher altitudes. Little advancement in baking methods occurred until 1927, when the first altitude baking lab in the nation was constructed at CSU thanks to Allison’s research. The results were tangible — and tasty — as public dissemination of altitude-specific baking practices began.

A 1932 bulletin on baking at altitude offers hundreds of formulas for success at heights ranging from 4,000 feet to over 11,000 feet. Its author, Marjorie Peterson, a home economics staff person at the Colorado Experiment Station, credits Allison for her constructive suggestions and support in the development of the booklet.

Science of high-altitude baking

As a senior food scientist in a mountain state, one of us – Caitlin Clark – advises bakers on how to adjust their recipes to compensate for altitude. Thanks to Allison’s research, bakers at high altitude today can anticipate how the lower air pressure will affect their recipes and compensate by making small adjustments.

The first thing you have to understand before heading into the kitchen is that the higher the altitude, the lower the air pressure. This lower pressure has chemical and physical effects on baking.

Air pressure is a force that pushes back on all of the molecules in a system and prevents them from venturing off into the environment. Heat plays the opposite role – it adds energy and pushes molecules to escape.

When water is boiled, molecules escape by turning into steam. The less air pressure is pushing back, the less energy is required to make this happen. That’s why water boils at lower temperatures at higher altitudes – around 200 degrees Fahrenheit in Denver compared with 212 F at sea level.

So, when baking is done at high altitude, steam is produced at a lower temperature and earlier in the baking time. Carbon dioxide produced by leavening agents also expands more rapidly in the thinner air. This causes high-altitude baked goods to rise too early, before their structure has fully set, leading to collapsed cakes and flat muffins. Finally, the rapid evaporation of water leads to over-concentration of sugars and fats in the recipe, which can cause pastries to have a gummy, undesirable texture.

Allison learned that high-altitude bakers could adjust to their environment by reducing the amount of sugar or increasing liquids to prevent over-concentration, and using less of leavening agents like baking soda or baking powder to prevent dough from rising too quickly.

Allison was one of many groundbreaking women in the early 20th century who actively supported higher education for women and advanced research in science, politics, humanities and education in Colorado.

Others included Grace Espy-Patton, a professor of English and sociology at CSU from 1885 to 1896 who founded an early feminist journal and was the first woman to register to vote in Fort Collins. Miriam Palmer was an aphid specialist and master illustrator whose work crafting hyper-realistic wax apples in the early 1900s allowed farmers to confirm rediscovery of the lost Colorado Orange apple, a fruit that has been successfully propagated in recent years.

In 1945, Allison retired as both an emerita professor and emerita dean at CSU. She immediately stepped into the role of student and took classes in Russian and biochemistry.

In the fall of 1958, CSU opened a new dormitory for women that was named Allison Hall in her honor.

“I had supposed that such a thing happened only to the very rich or the very dead,” Allison told reporters at the dedication ceremony.

Read more of our stories about Colorado.The Conversation

Tobi Jacobi, Professor of English, Colorado State University and Caitlin Clark, Senior Food Scientist at the CSU Spur Food Innovation Center, Colorado State University

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Why don’t humans have hair all over their bodies? A biologist explains our lack of fur

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theconversation.com – Maria Chikina, Assistant Professor of Computational and Systems Biology, University of Pittsburgh – 2025-04-21 07:33:00

Some mammals are super hairy, some are not.
Ed Jones/AFP via Getty Images

Maria Chikina, University of Pittsburgh

Curious Kids is a series for children of all ages. If you have a question you’d like an expert to answer, send it to CuriousKidsUS@theconversation.com.


Why don’t humans have hair all over their bodies like other animals? – Murilo, age 5, Brazil


Have you ever wondered why you don’t have thick hair covering your whole body like a dog, cat or gorilla does?

Humans aren’t the only mammals with sparse hair. Elephants, rhinos and naked mole rats also have very little hair. It’s true for some marine mammals, such as whales and dolphins, too.

Scientists think the earliest mammals, which lived at the time of the dinosaurs, were quite hairy. But over hundreds of millions of years, a small handful of mammals, including humans, evolved to have less hair. What’s the advantage of not growing your own fur coat?

I’m a biologist who studies the genes that control hairiness in mammals. Why humans and a small number of other mammals are relatively hairless is an interesting question. It all comes down to whether certain genes are turned on or off.

Hair benefits

Hair and fur have many important jobs. They keep animals warm, protect their skin from the sun and injuries and help them blend into their surroundings.

They even assist animals in sensing their environment. Ever felt a tickle when something almost touches you? That’s your hair helping you detect things nearby.

Humans do have hair all over their bodies, but it is generally sparser and finer than that of our hairier relatives. A notable exception is the hair on our heads, which likely serves to protect the scalp from the sun. In human adults, the thicker hair that develops under the arms and between the legs likely reduces skin friction and aids in cooling by dispersing sweat.

So hair can be pretty beneficial. There must have been a strong evolutionary reason for people to lose so much of it.

Why humans lost their hair

The story begins about 7 million years ago, when humans and chimpanzees took different evolutionary paths. Although scientists can’t be sure why humans became less hairy, we have some strong theories that involve sweat.

Humans have far more sweat glands than chimps and other mammals do. Sweating keeps you cool. As sweat evaporates from your skin, heat energy is carried away from your body. This cooling system was likely crucial for early human ancestors, who lived in the hot African savanna.

Of course, there are plenty of mammals living in hot climates right now that are covered with fur. Early humans were able to hunt those kinds of animals by tiring them out over long chases in the heat – a strategy known as persistence hunting.

Humans didn’t need to be faster than the animals they hunted. They just needed to keep going until their prey got too hot and tired to flee. Being able to sweat a lot, without a thick coat of hair, made this endurance possible.

Genes that control hairiness

To better understand hairiness in mammals, my research team compared the genetic information of 62 different mammals, from humans to armadillos to dogs and squirrels. By lining up the DNA of all these different species, we were able to zero in on the genes linked to keeping or losing body hair.

Among the many discoveries we made, we learned humans still carry all the genes needed for a full coat of hair – they are just muted or switched off.

In the story of “Beauty and the Beast,” the Beast is covered in thick fur, which might seem like pure fantasy. But in real life some rare conditions can cause people to grow a lot of hair all over their bodies. This condition, called hypertrichosis, is very unusual and has been called “werewolf syndrome” because of how people who have it look.

A detailed painting of a man and a woman standing next to one another in historical looking clothes. The man's face is covered in hair, while the woman's is not.
Petrus Gonsalvus and his wife, Catherine, painted by Joris Hoefnagel, circa 1575.
National Gallery of Art

In the 1500s, a Spanish man named Petrus Gonsalvus was born with hypertrichosis. As a child he was sent in an iron cage like an animal to Henry II of France as a gift. It wasn’t long before the king realized Petrus was like any other person and could be educated. In time, he married a lady, forming the inspiration for the “Beauty and the Beast” story.

While you will probably never meet someone with this rare trait, it shows how genes can lead to unique and surprising changes in hair growth.


Hello, curious kids! Do you have a question you’d like an expert to answer? Ask an adult to send your question to CuriousKidsUS@theconversation.com. Please tell us your name, age and the city where you live.

And since curiosity has no age limit – adults, let us know what you’re wondering, too. We won’t be able to answer every question, but we will do our best.The Conversation

Maria Chikina, Assistant Professor of Computational and Systems Biology, University of Pittsburgh

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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