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By Zaid Zada, Princeton University 

Language enables people to transmit thoughts to each other because each person’s brain responds similarly to the meaning of words. In our newly published research, my colleagues and I developed a framework to model the brain activity of speakers as they engaged in face-to-face conversations.

We recorded the electrical activity of two people’s brains as they engaged in unscripted conversations. Previous research has shown that when two people converse, their brain activity becomes coupled, or aligned, and that the degree of neural coupling is associated with better understanding of the speaker’s message.

A neural code refers to particular patterns of brain activity associated with distinct words in their contexts. We found that the speakers’ brains are aligned on a shared neural code. Importantly, the brain’s neural code resembled the artificial neural code of large language models, or LLMs.

The neural patterns of words

A large language model is a machine learning program that can generate text by predicting what words most likely follow others. Large language models excel at learning the structure of language, generating humanlike text and holding conversations. They can even pass the Turing test, making it difficult for someone to discern whether they are interacting with a machine or a human. Like humans, LLMs learn how to speak by reading or listening to text produced by other humans.

By giving the LLM a transcript of the conversation, we were able to extract its “neural activations,” or how it translates words into numbers, as it “reads” the script. Then, we correlated the speaker’s brain activity with both the LLM’s activations and with the listener’s brain activity. We found that the LLM’s activations could predict the speaker and listener’s shared brain activity.

To be able to understand each other, people have a shared agreement on the grammatical rules and the meaning of words in context. For instance, we know to use the past tense form of a verb to talk about past actions, as in the sentence: “He visited the museum yesterday.” Additionally, we intuitively understand that the same word can have different meanings in different situations. For instance, the word cold in the sentence “you are cold as ice” can refer either to one’s body temperature or personality trait, depending on the context. Due to the complexity and richness of natural language, until the recent success of large language models, we lacked a precise mathematical model to describe it.

Our study found that large language models can predict how linguistic information is encoded in the human brain, providing a new tool to interpret human brain activity. The similarity between the human brain’s and the large language model’s linguistic code has enabled us, for the first time, to track how information in the speaker’s brain is encoded into words and transferred, word by word, to the listener’s brain during face-to-face conversations. For example, we found that brain activity associated with the meaning of a word emerges in the speaker’s brain before articulating a word, and the same activity rapidly reemerges in the listener’s brain after hearing the word.

Powerful new tool

Our study has provided insights into the neural code for language processing in the human brain and how both humans and machines can use this code to communicate. We found that large language models were better able to predict shared brain activity compared with different features of language, such as syntax, or the order in which words connect to form phrases and sentences. This is partly due to the LLM’s ability to incorporate the contextual meaning of words, as well as integrate multiple levels of the linguistic hierarchy into one model: from words to sentences to conceptual meaning. This suggests important similarities between the brain and artificial neural networks.

An important aspect of our research is using everyday recordings of natural conversations to ensure that our findings capture the brain’s processing in real life. This is called ecological validity. In contrast to experiments in which participants are told what to say, we relinquish control of the study and let the participants converse as naturally as possible. This loss of control makes it difficult to analyze the data because each conversation is unique and involves two interacting individuals who are spontaneously speaking. Our ability to model neural activity as people engage in everyday conversations attests to the power of large language models.

Other dimensions

Now that we’ve developed a framework to assess the shared neural code between brains during everyday conversations, we’re interested in what factors drive or inhibit this coupling. For example, does linguistic coupling increase if a listener better understands the speaker’s intent? Or perhaps complex language, like jargon, may reduce neural coupling.

Another factor that can influence linguistic coupling may be the relationship between the speakers. For example, you may be able to convey a lot of information with a few words to a good friend but not to a stranger. Or you may be better neurally coupled to political allies rather than rivals. This is because differences in the way we use words across groups may make it easier to align and be coupled with people within rather than outside our social groups.

About the Author:

Zaid Zada, Ph.D. Candidate in Psychology, Princeton University

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

By Omar H. Fares, Toronto Metropolitan University and Seung Hwan (Mark) Lee, Toronto Metropolitan University 

A new TikTok trend called “underconsumption core” is gaining traction online. This trend champions minimalism and frugality, and encourages people to maximize the utility of their purchases and buy only what they truly need, challenging the culture of consumerism.

Instead of showcasing large hauls of clothing, makeup or over-flowing fridge shelves, users are posting videos showing thrift store purchases, modest wardrobes and practical, well-used everyday items.

The rise of this trend can be linked to several challenges facing young people today, including increasing economic pressures, environmental concerns and social pressures, all of which are particularly affecting Gen Z and younger Millennials. If you’re also feeling financially squeezed, this trend might resonate with you.

Similar to the deinfluencing trend, underconsumption also appears to be a reaction to overconsumption — especially the way influencers have normalized it by posting haul videos. By promoting underconsumption, online users are rejecting and pushing back against this aspect of “influencer culture.”

Born of necessity

Young people are likely engaging with it as a way to adapt to increasing financial pressures.

For instance, the average federal student loan debt balance in the United States is US$37,574 per borrower, according to the Education Data Initiative. Student debt is a significant financial burden that often forces young adults to prioritize debt repayment over discretionary spending.

Inflation is also continuing to erode Gen Z’s purchasing power. While there are signs of economic relief, such as interest rate cuts in Canada, the cumulative effects of high prices continue to strain young peoples’ budgets.

Underconsumption core represents a growing awareness and adaptation to these economic realities, but it’s not the only reason. Another driver of the underconsumption trend appears to be environmental consciousness.

Environmental concerns

Mass consumerism has created significant environmental problems, including the generation of vast amounts of waste. In Chile’s Atacama Desert, an estimated 11,000 to 59,000 tons of used clothing is sitting in a landfill. This is just one example of how overconsumption is polluting the environment.

A report from ThredUp, an online vintage-resale platform, found that 65 per cent of Gen Z respondents wanted to shop more sustainably. However, one-third felt “addicted to fast fashion,” and 72 per cent said they shopped for fast fashion in 2022. Similarly, researchers from Sheffield Hallam University found 90 per cent of university students bought fast fashion in 2022.

Despite this, many of these same consumers are concerned with sustainability and are actively seeking ways to be more responsible. Our recent study found a consistent shift in consumer attitudes towards sustainability practices, especially in fashion. This is particularly the case with Gen Z, who rely heavily on social media for shopping inspiration.

As younger consumers become more aware of the environmental impact of their purchasing decisions, they are increasingly drawn to sustainable fashion content.

This shift in consumer mentality aligns with the broader cultural phenomenon known as the “Marie Kondo effect,” named after the Japanese organizing consultant. She is an advocate for only keeping things that bring one value and joy. Kondo’s influence has sparked a growing interest in intentional consumption.

However, it is important to note that, in some instances, sustainable consumption behaviours may be driven more by selfish motives than purely altruistic ones. By choosing to consume less or more mindfully, younger individuals can project an image of thoughtfulness, responsibility and uniqueness — qualities that are increasingly valued in the social media landscape.

How to be a healthier consumer

If you are interested in practising healthier consumption habits, it’s important to understand how you can sustain this lifestyle long-term. There are two main strategies you can use to do this.

First, find a way to strike a balance between frugality and quality of life to maintain your overall well-being. Research suggests a mix of experiential spending (such as travel) and material purchases (such as a new smartphone) can lead to greater happiness and satisfaction.

Don’t completely abandon material purchases in favour of experiences. Instead, a thoughtful approach that includes both types of spending, albeit at a reduced overall level, will likely lead to better outcomes. This approach focuses more on mindful consumption, rather than blanket restrictions.

Second, try to focus on improving your financial literacy. Start by creating a budget that ensures basic needs and baseline expenses are met. Seek to understand the types of financial products and solutions that fit your particular needs. This will help you avoid overconsumption and make choices that support long-term financial stability.

Those with higher financial literacy are better equipped to select products that align with their needs and values, rather than falling prey to aggressive marketing or unnecessary features that can lead to overconsumption. For instance, young consumers are likely to spend more on credit cards that offer attractive rewards leading to overconsumption and strained budgets over the long-term.

While the underconsumption trend offers potential benefits, it’s important to approach it in a balanced way. While combining healthy spending habits with financial literacy is key, it shouldn’t be about deprivation. Instead, you should make informed choices that align with your personal values and goals. Done right, underconsumption can lead to financial stability and a more purposeful lifestyle.

About the Author:

Omar H. Fares, Lecturer in the Ted Rogers School of Retail Management, Toronto Metropolitan University and Seung Hwan (Mark) Lee, Professor and Associate Dean of Engagement & Inclusion, Ted Rogers School of Management, Toronto Metropolitan University

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

By Yvette Richardson, Penn State and Paul Markowski, Penn State

Scientists in a truck outfitted with instruments race toward a storm.
National Severe Storms Lab/NOAA

Storm-chasing for science can be exciting and stressful – we know, because we do it. It has also been essential for developing today’s understanding of how tornadoes form and how they behave.

In 1996, the movie “Twister” with Helen Hunt brought storm-chasing scientists into the public imagination and inspired a generation of atmospheric scientists.

With the new “Twisters” movie hitting theaters, we’ve been getting questions about storm-chasing – or storm intercepts, as we call them.

Here are some answers about what scientists who do this kind of fieldwork are really up to when they race off after storms.

Scientists with the National Severe Storms Lab ‘intercepted’ this tornado to
collect data using mobile radar and other instruments on May 24, 2024.
National Severe Storms Lab

What does a day of storm-chasing really look like?

The morning of a chase day starts with a good breakfast, because there might not be any chance to eat a good meal later in the day. The team looks at the weather conditions, the National Weather Service computer forecast models and outlooks from the National Oceanic and Atmospheric Administration’s Storm Prediction Center to determine the target.

Our goal is to figure out where tornadoes are most likely to occur that day. Temperature, moisture and winds, and how these change with height above the ground, all provide clues.

There is a “hurry up and wait” cadence to a storm chase day. We want to get into position quickly, but then we’re often waiting for storms to develop.

A ‘hook echo’ on radar, typically a curl at the back of a storm cell, is one sign that a tornado could form.
The hook reflects precipitation wrapping around the back side of the updraft.
National Severe Storms Lab

Storms often take time to develop before they’re capable of producing tornadoes. So we watch the storm carefully on radar and with our eyes, if possible, staying well ahead of it until it matures. Often, we’ll watch multiple storms and look for signs that one might be more likely to generate tornadoes.

Once the mission scientist declares a deployment, everyone scrambles to get into position.

We use a lot of different instruments to track and measure tornadoes, and there is an art to determining when to deploy them. Too early, and the tornado might not form where the instruments are. Too late, and we’ve missed it. Each instrument needs to be in a specific location relative to the tornado. Some need to be deployed well ahead of the storm and then stay stationary. Others are car-mounted and are driven back and forth within the storm.

Vehicle-mounted equipment can act as mobile weather stations known as mesonets.
These were used in the VORTEX2 research project. Dozens of scientists, including the authors,
succeeded in recording the entire life cycle of a supercell tornado during VORTEX2 in 2009.
Yvette Richardson

If all goes well, team members will be concentrating on the data coming in. Some will be launching weather balloons at various distances from the tornado, while others will be placing “pods” containing weather instruments directly in the path of the tornado.

A whole network of observing stations will have been set up across the storm, with radars collecting data from multiple angles, photographers capturing the storm from multiple angles, and instrumented vehicles transecting key areas of the storm.

Not all of our work is focused on the tornado itself. We often target areas around the tornado or within other parts of the storm to understand how the rotation forms. Theories suggest that this rotation can be generated by temperature variations within the storm’s precipitation region, potentially many miles from where the tornado forms.

Through all of this, the teams stay in contact using text messages and software that allows us to see everyone’s position relative to the latest radar images. We’re also watching the forecast for the next day so we can plan where to go next and find hotel rooms and, hopefully, a late dinner.

What do all those instruments tell you about the storm?

One of the most important tools of storm-chasing is weather radar. It captures what’s happening with precipitation and winds above the ground.

We use several types of radars, typically attached to trucks so we can move fast. Some transmit with a longer wavelength that helps us see farther into a storm, but at the cost of a broader width to their beam, resulting in a fuzzier picture. They are good for collecting data across the entire storm.

Smaller-wavelength radars cannot penetrate as far into the precipitation, but they do offer the high-resolution view necessary to capture small-scale phenomena like tornadoes. We put these radars closer to the developing tornado.

We also monitor wind, air pressure, temperature and humidity along the ground using various instruments attached to moving vehicles, or by temporarily deploying stationary arrays of these instruments ahead of the approaching storm. Some of these are meant to be hit by the tornado.

Weather balloons provide crucial data, too. Some are designed to ascend through the atmosphere and capture the conditions outside the storm. Others travel through the storm itself, measuring the important temperature variations in the rain-cooled air beneath the storm. Scientists are now using drones in the same way in parts of the storm.

All of this gives scientists insight into the processes happening throughout the storm before and during tornado development and throughout the tornado’s lifetime.

How do you stay safe while chasing tornadoes?

Storms can be very dangerous and unpredictable, so it’s important to always stay on top of the radar and watch the storm.

A storm can cycle, developing a new tornado downstream of the previous one. Tornadoes can change direction, particularly as they are dying or when they have a complex structure with multiple funnels. Storm chasers know to look at the entire storm, not just the tornado, and to be on alert for other storms that might sneak up. An escape plan based on the storm’s expected motion and the road network is essential.

Scientists take calculated risks when they’re storm chasing – enough to collect crucial data, but never putting their teams in too much danger.

It turns out that driving is actually the most dangerous part of storm-chasing, particularly when roads are wet and visibility is poor – as is often the case at the end of the day. During the chase, the driving danger can be compounded by erratic driving of other storm chasers and traffic jams around storms.

What happens to all the data you collect while storm-chasing?

It would be nice to have immediate eureka moments, but the results take time.

After we collect the data, we spend years analyzing it. Combining data from all the instruments to get a complete picture of the storm and how it evolved takes time and patience. But having data on the wind, temperature, relative humidity and pressure from many different angles and instruments allows us to test theories about how tornadoes develop.

Although the analysis process is slow, the discoveries are often as exciting as the tornado itself.

About the Authors:

Yvette Richardson, Professor of Meteorology, Senior Associate Dean for Undergraduate Education, Penn State and Paul Markowski, Distinguished Professor of Meteorology, Penn State

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

By Jordan Frith, Clemson University 

The first modern barcode was scanned 50 years ago this summer – on a 10-pack of chewing gum in a grocery store in Troy, Ohio.

Fifty is ancient for most technologies, but barcodes are still going strong. More than 10 billion barcodes are scanned every day around the world. And newer types of barcode symbols, such as QR codes, have created even more uses for the technology.

I would have been like most people, never giving a second thought to the humble barcode, if my research as a media scholar at Clemson University hadn’t taken a few strange turns. Instead, I spent a year of my life digging through the archives and old newspaper articles to learn about the barcode’s origins – and eventually went on to write a book about the cultural history of the barcode.

While the barcode didn’t herald the end times, as conspiracy theorists once fretted, it did usher in a new age in global commerce.

Barcodes were a grocery-industry invention

While the world has changed a lot since the mid-1970s, the Universal Product Code (UPC) – what most people think of when they hear the word “barcode” – hasn’t. The code first scanned on a package of gum on June 26, 1974, is basically identical to the billions of barcodes scanned in stores all over the world today.

When that first UPC code was scanned, it was the culmination of years of planning by the U.S. grocery industry. In the late 1960s, labor costs were rising rapidly in grocery stores and inventory was becoming increasingly difficult to track. Grocery executives hoped the barcode could help them solve both of those problems, and they ended up being right.

In the early 1970s, the industry created a committee that developed the UPC data standard and chose the IBM barcode symbol over a half-dozen alternative designs. Both the data standard and the IBM barcode symbol are still used today.

Based on meeting notes I found in Stony Brook University’s Goldberg Archive, the people who developed the UPC system felt they were doing important work. However, they had no idea they were creating something that would long outlive most of them.

Even the grocery industry’s optimistic estimates predicted fewer than 10,000 companies would ever use barcodes. As a result, the scanning of the first UPC barcode received little attention at the time.

A few newspapers published short articles about the launch event, but it wasn’t exactly front-page news. Its importance was only apparent years later, as barcodes became one of the most successful digital data infrastructures ever.

Barcodes created a shelf-space revolution

Barcodes didn’t just change the shopping experience at checkout. By making products machine-readable, they enabled vast improvements to inventory tracking. That meant items that sold well could be restocked quickly when the data indicated, requiring less shelf space to be devoted to any individual product.

As barcode expert Stephen A. Brown has written, that reduced need for shelf space allowed for a rapid proliferation of new products. You can blame barcodes for the fact that your grocery store sells 15 types of almost indistinguishable toothpaste.

Similarly, today’s huge grocery stores and superstores likely couldn’t exist without the massive amount of inventory data that barcode systems produce. As MIT professor Sanjay Sharma put it, “If barcodes hadn’t been invented, the entire layout and architecture of commerce would have been different.”

Other industries quickly got on board

The modern barcode was born in the grocery industry, but it wasn’t confined to the grocery aisles for long. By the mid-1980s, the success of the UPC system encouraged other industries to adopt barcodes. For example, within a span of three years, Walmart, the Defense Department and the U.S. automotive industry all began using barcodes to track objects in supply chains.

Private shipping companies also adopted barcodes to capture identification data. FedEx and UPS even created their own barcode symbols.

As the sociologist Nigel Thrift explained, by the end of the 1990s, barcodes had become “a crucial element in the history of the new way of the world.” They helped enable rapid globalization in ways that would be difficult to imagine if barcodes didn’t exist.

Black and white and unnoticed all over

As someone who became so interested in this history that I got a tattoo of my latest book’s International Standard Book Number barcode on my arm, the quiet passing of the barcode’s 50th anniversary feels almost poetic.

I grew up in a world where barcodes were everywhere. They were on all the products I bought, the concert tickets I scanned, the packages I received.

Like most people, I rarely thought about them, despite — or maybe because of — their ubiquity. It wasn’t until I began research for my book that I realized how a barcode on a package of gum set in motion a chain of events that transformed the world.

For decades, barcodes have been a workhorse operating in the background of our lives. Modern humans scan them countless times every day, but we rarely think about them because they’re not flashy and just work — most of the time, anyway.

As barcodes keep chugging along in their old age, they’re a reminder that the seemingly boring technologies are often far more interesting and consequential than most people realize.

About the Author:

Jordan Frith, Pearce Professor of Professional Communication, Clemson University

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