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AI harm is often behind the scenes and builds over time – a legal scholar explains how the law can adapt to respond

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theconversation.com – Sylvia Lu, Faculty Fellow and Visiting Assistant Professor of Law, University of Michigan – 2024-11-22 07:25:00

One AI harm is pervasive facial recognition, which erodes privacy.
DSCimage/iStock via Getty Images

Sylvia Lu, University of Michigan

As you scroll through your social media feed or let your favorite music app curate the perfect playlist, it may feel like artificial intelligence is improving your life – learning your preferences and serving your needs. But lurking behind this convenient facade is a growing concern: algorithmic harms.

These harms aren’t obvious or immediate. They’re insidious, building over time as AI systems quietly make decisions about your life without you even knowing it. The hidden power of these systems is becoming a significant threat to privacy, equality, autonomy and safety.

AI systems are embedded in nearly every facet of modern life. They suggest what shows and movies you should watch, help employers decide whom they want to hire, and even influence judges to decide who qualifies for a sentence. But what happens when these systems, often seen as neutral, begin making decisions that put certain groups at a disadvantage or, worse, cause real-world harm?

The often-overlooked consequences of AI applications call for regulatory frameworks that can keep pace with this rapidly evolving technology. I study the intersection of law and technology, and I’ve outlined a legal framework to do just that.

Slow burns

One of the most striking aspects of algorithmic harms is that their cumulative impact often flies under the radar. These systems typically don’t directly assault your privacy or autonomy in ways you can easily perceive. They gather vast amounts of data about people — often without their knowledge — and use this data to shape decisions affecting people’s lives.

Sometimes, this results in minor inconveniences, like an advertisement that follows you across websites. But as AI operates without addressing these repetitive harms, they can scale up, leading to significant cumulative damage across diverse groups of people.

Consider the example of social media algorithms. They are ostensibly designed to promote beneficial social interactions. However, behind their seemingly beneficial facade, they silently track users’ clicks and compile profiles of their political beliefs, professional affiliations and personal lives. The data collected is used in systems that make consequential decisions — whether you are identified as a jaywalking pedestrian, considered for a job or flagged as a risk to commit suicide.

Worse, their addictive design traps teenagers in cycles of overuse, leading to escalating mental health crises, including anxiety, depression and self-harm. By the time you grasp the full scope, it’s too late — your privacy has been breached, your opportunities shaped by biased algorithms, and the safety of the most vulnerable undermined, all without your knowledge.

This is what I call “intangible, cumulative harm”: AI systems operate in the background, but their impacts can be devastating and invisible.

YouTube video
Researcher Kumba Sennaar describes how AI systems perpetuate and exacerbate biases.

Why regulation lags behind

Despite these mounting dangers, legal frameworks worldwide have struggled to keep up. In the United States, a regulatory approach emphasizing innovation has made it difficult to impose strict standards on how these systems are used across multiple contexts.

Courts and regulatory bodies are accustomed to dealing with concrete harms, like physical injury or economic loss, but algorithmic harms are often more subtle, cumulative and hard to detect. The regulations often fail to address the broader effects that AI systems can have over time.

Social media algorithms, for example, can gradually erode users’ mental health, but because these harms build slowly, they are difficult to address within the confines of current legal standards.

Four types of algorithmic harm

Drawing on existing AI and data governance scholarship, I have categorized algorithmic harms into four legal areas: privacy, autonomy, equality and safety. Each of these domains is vulnerable to the subtle yet often unchecked power of AI systems.

The first type of harm is eroding privacy. AI systems collect, process and transfer vast amounts of data, eroding people’s privacy in ways that may not be immediately obvious but have long-term implications. For example, facial recognition systems can track people in public and private spaces, effectively turning mass surveillance into the norm.

The second type of harm is undermining autonomy. AI systems often subtly undermine your ability to make autonomous decisions by manipulating the information you see. Social media platforms use algorithms to show users content that maximizes a third party’s interests, subtly shaping opinions, decisions and behaviors across millions of users.

The third type of harm is diminishing equality. AI systems, while designed to be neutral, often inherit the biases present in their data and algorithms. This reinforces societal inequalities over time. In one infamous case, a facial recognition system used by retail stores to detect shoplifters disproportionately misidentified women and people of color.

The fourth type of harm is impairing safety. AI systems make decisions that affect people’s safety and well-being. When these systems fail, the consequences can be catastrophic. But even when they function as designed, they can still cause harm, such as social media algorithms’ cumulative effects on teenagers’ mental health.

Because these cumulative harms often arise from AI applications protected by trade secret laws, victims have no way to detect or trace the harm. This creates a gap in accountability. When a biased hiring decision or a wrongful arrest is made due to an algorithm, how does the victim know? Without transparency, it’s nearly impossible to hold companies accountable.

YouTube video
This UNESCO video features researchers from around the world explaining the issues around the ethics and regulation of AI.

Closing the accountability gap

Categorizing the types of algorithmic harms delineates the legal boundaries of AI regulation and presents possible legal reforms to bridge this accountability gap. Changes I believe would help include mandatory algorithmic impact assessments that require companies to document and address the immediate and cumulative harms of an AI application to privacy, autonomy, equality and safety – before and after it’s deployed. For instance, firms using facial recognition systems would need to evaluate these systems’ impacts throughout their life cycle.

Another helpful change would be stronger individual rights around the use of AI systems, allowing people to opt out of harmful practices and making certain AI applications opt in. For example, requiring an opt-in regime for data processing by firms’ use of facial recognition systems and allowing users to opt out at any time.

Lastly, I suggest requiring companies to disclose the use of AI technology and its anticipated harms. To illustrate, this may include notifying customers about the use of facial recognition systems and the anticipated harms across the domains outlined in the typology.

As AI systems become more widely used in critical societal functions – from health care to education and employment – the need to regulate harms they can cause becomes more pressing. Without intervention, these invisible harms are likely to continue to accumulate, affecting nearly everyone and disproportionately hitting the most vulnerable.

With generative AI multiplying and exacerbating AI harms, I believe it’s important for policymakers, courts, technology developers and civil society to recognize the legal harms of AI. This requires not just better laws, but a more thoughtful approach to cutting-edge AI technology – one that prioritizes civil rights and justice in the face of rapid technological advancement.

The future of AI holds incredible promise, but without the right legal frameworks, it could also entrench inequality and erode the very civil rights it is, in many cases, designed to enhance.The Conversation

Sylvia Lu, Faculty Fellow and Visiting Assistant Professor of Law, University of Michigan

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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

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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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