Science Friday - Personifying AI, The Reading Brain, Environmental Sampling Via Bees. April 28, 2023, Part 2

Episode Date: April 28, 2023

Why Do Humans Anthropomorphize AI? Artificial intelligence has become more sophisticated in a short period of time. Even though we may understand that when ChatGPT spits out a response, there’s no human behind the screen, we can’t help but anthropomorphize—imagining that the AI has a personality, thoughts, or feelings. How exactly should we understand the bond between humans and artificial intelligence? Guest host Sophie Bushwick talks to Dr. David Gunkel, professor of media studies at Northern Illinois University, to explore the ways in which humans and artificial intelligence form emotional connections.   A Bee’s Eye View Of Cities’ Microbiomes When you want to look at the microbial health of a city, there are a variety of ways to go about it. You might look at medical records, or air quality. In recent years, samples of wastewater have been used to track COVID outbreaks. Studies of urban subway systems have involved painstaking swabs of patches of subway muck. But now, researchers are offering another approach to sample a city’s environment—its beehives. A report recently published in the journal Environmental Microbiome used the bees foraging in a city to provide information about the town’s bacteria and fungi. The researchers found that by looking at the debris in the bottom of a beehive, they could learn about some of the environments in the blocks around the hives. The microbes they collected weren’t just species associated with flowers and plant life, but included organisms associated with ponds and dogs. The team found that the hive samples could reveal changes from one neighborhood to another in a city, and in the microbial differences between different cities—samples taken in Venice, for instance, contained signals associated with rotting wood that were not seen in samples from Tokyo. Elizabeth Henaff, an assistant professor in the NYU Tandon School of Engineering at New York University and a co-author of the report, joins SciFri’s Kathleen Davis to talk about what bees and microbes can tell us about the cities we share.   This Is Your Brain On Words What happens after you pick up a book, or pull up some text on your phone? What occurs between the written words hitting your eyes and your brain understanding what they represent? Scientists are trying to better understand how the brain processes written information—and how a primate brain that evolved to make sense of twisty branches and forking streams adapted to comprehend a written alphabet. Researchers used electrodes implanted in the brains of patients being evaluated for epilepsy treatment to study what parts of the brain were involved when those patients read words and sentences. They found that two different parts of the brain are activated, and interact in different ways when you read a simple list of unrelated words, compared to when you encounter a series of words that builds up a more complex idea. Dr. Nitin Tandon, a professor of neurosurgery at UTHealth Houston and one of the authors of a report on the work published in the Proceedings of the National Academy of Sciences, joins guest host Sophie Bushwick to talk about the study, and what scientists are learning about how the brain allows us to read.   Transcripts for each segment will be available the week after the show airs on sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

This is Science Friday. I'm Sophie Bushwick. And I'm Kathleen Davis. And now it's time to check in on the state of science. This is KERNO. St. Louis Public Radio News. Iowa Public Radio News. Local science stories of national significance. As we've talked about on this show, the West is in the midst of a water crisis. So we're going to take a little field trip to Lake Mead, which is the nation's largest reservoir.

It plays a key role in the Colorado River system. And the effects of drought are obvious. There's a big white ring along the edges of the reservoir. It's known locally as the bathtub ring. It's roughly 160 feet above the current water level. It's a stark reminder of where water used to be. Reporter Luke Runyon has been taking an in-depth look at how Southwest states, tribes, and individuals are dealing with this water shortage. It's a tale of climate change, bureaucracy, and learning to live with less. Luke is host and producer of Thurst Gap, learning to live with Les on the Colorado River, a new podcast from KUNC Public Radio.

He's based in Grand Junction, Colorado. Luke, welcome back to Science Friday. Hey, thanks so much for having me. So let's start by kind of getting to know this Colorado River watershed. So imagine a little drop of water. Where does it start its journey before getting into, you know, let's say Lake Mead? Well, the river begins high up in the Rocky Mountains, where Snow piles up each winter. That snow in the mountains of Colorado, Wyoming, and Utah just sits there

until springtime when the sun gets high enough in the sky and it warms up enough to melt it all. And that's happening right now. We're in runoff season. And all that snow melts. It rushes into the river and it's such a fun time of year. But what we do know is that less water is ending up in the river throughout the year, mostly due to rising temperatures from climate change. Is it possible to know just how much water has dried up from the Colorado River? A lot of the measurements are long-term averages, so it's kind of tough to put a specific volume on how much we're losing. Some studies have put it at 20% to 30% of the river's total volume, with a significant cause of that loss being warming temperatures. What we can say, according to all of the climate science, is that the river is getting smaller.

And that's happening on a few fronts. The warming temperatures are causing more precipitation to fall as rain instead of snow, which is harder to capture and manage. And the higher temperatures are also speeding up how fast water evaporates. So let's get into, there's kind of this bureaucratic nightmare that's at the heart of all of this. And that's the Colorado River Compact, which is now a century old. Happy birthday. What is the story of this agreement? Well, the agreement itself was signed in 1922, but to understand,

understand why it came together, you have to go back a bit further to around the turn of the 20th century. Around that time, white settlers were moving into the southwest in greater numbers. They started agricultural communities in southern Arizona and California. And these farm towns relied really heavily on the Colorado River. But the settlers thought of the river as this unreliable menace. It caused flooding in the spring. And then it nearly dried. up in the fall and winter. In my podcast's first episode, I talk about this with Eric Coon. He wrote the book, Science Be Damned, about the compact negotiations. And it created a political movement to control the river, if you want to call it, control this wild raging river. And at the same time,

Southern California was developing, and we were electrifying the nation. So there was a need for power generation. People in California, started to think that a big dam on the river would solve their problems. It would control the river, generate electricity, and store water for later. And that's really what pushed the seven states that rely on the river. That's Colorado, Utah, Wyoming, New Mexico, Nevada, California, and Arizona to the negotiating table was this desire to build Hoover Dam. And they all got together to figure out a way to divide the river's water amongst themselves. So who was at the table during this decision-making process and who was not?

Well, at the table, you had representatives from the seven southwestern states and the federal government, but not at the table was pretty much everyone else. There was no one from any Native American tribes, and that exclusion of tribal voices lasted for decades after. And even now, tribes don't have an equal seat at the negotiating table. No one was representing Mexico, which also relies on the river. No one was advocating for the environment. And Eric Coon, says everyone in the room was basically a politician, an engineer, or a lawyer. Stream flows, recreation, fishing, no one had that in mind. That attitude was unanimous. Without those different voices, was this kind of doomed to fail? Well, we were definitely doomed

to be short on water. That's one thing that almost everyone agrees on here. The compact put a number on paper of how much water the Colorado River would provide. And that's just not how rivers function, especially rivers in the West. There was no way that the Colorado River was going to meet everyone's needs. It was over-allocated right from the very beginning, which means we would be having this problem even without climate change. But climate change is speeding it up and we're having to confront this problem sooner than we'd like to. All right. Outside of the seven states that are part of this agreement, Southwest tribes do hold some rights to a percentage of the Colorado River's water. But how has that really played out in reality?

It's a big, broad landscape when it comes to tribal water rights. There are 30 federally recognized tribes in the watershed, and they're all different. Some tribes have water rights that have been fully settled, and in some cases actually leasing their water off of tribal land. But in lots of other cases, tribes do not have their water rights settled, meaning that they have a certain amount of water that's been promised to them, but they haven't had the resources to actually use that water. So it's a bit of a mix. One thing that we do know is that tribes collectively hold rights to about 20% of the river's total amount of water. They're just not using it all right now. And there's lots of questions about what it's going to take to make sure

that tribes are included in all future talks over the river and that they're meaningfully not just a box to be checked in the process. So this brings us to modern times. How is this negotiation for water going? It's a pretty tense moment on the river. Last summer, things were looking really dire for the Colorado River. Like the loss of hydropower at one of its biggest dams seemed possible, if not likely. So in response to that, the federal government, which manages the river's big dams,

they threw down this gauntlet for the states. They asked for huge cuts to how much water was being used to, stabilize the system. The states came up with these proposals on how to do that. And basically, they differ in how water cuts should be dished out. Basically, who should feel the burden of water scarcity? Should it hit California or Arizona or Nevada or Mexico, the hardest? Recently, the federal government put forward its own proposals. And those are up for public comment right now. And really, what the federal government is doing is kind of weighing how involved it wants to get in Colorado river management. But everyone got a bit more time to negotiate this year because we had a very

wet winter and all that snow eases some of the pressure on the decision makers. There's one city that I want to talk about that is not known for restraint, but it has become somewhat of a model for tightening water use, and that's Las Vegas. Can you tell me what's going on here? Yeah, Las Vegas is a really interesting example of how big cities are grappling with a limited water supply. I focus on it in episode four of the podcast, and that one comes out on May 8th. Nevada has the lowest allocation of Colorado River water. So they've had to make do with a lot less water than Arizona or California. And to live within that smaller supply, the city and its main water utility have instituted some of the most aggressive conservation measures in the

southwest. Within the last couple of years, they've made some ornamental grass illegal and are actually forcing its removal. I was there last fall and I met with Curtis Hyde. He's a landscaper in Las Vegas and is doing a lot of these lawn removals. And he says people are slowly coming around to the idea of trading out their grass for desert landscaping. I think when people think of Zeriscape, they think of the old, you know, white, ugly rock with lava rock and a wagon wheel and a cow skull and like three cactus. It is a mindset change where there's people who prior to this mandate, there'd be HOAs who would literally say, we've gotten rid of some grass and we're keeping every blade that we have left. And they'll get pretty emotional about it.

Is this tactic by the city of Las Vegas working, would you say? It's working for Las Vegas. They're quick to say that these conservation efforts have enabled the city to grow in population while using less water in the process. So since 2002, they've added about 750,000 new residents. Meanwhile, they're using about 26% less Colorado River water than they were back then. And much of that has been this focus on scaling back outdoor water use. Could this be a strategy for other cities, this Las Vegas model? It could. You know, there's a lot of cities in the West that don't have any programs for dealing with outdoor water conservation. Vegas has been very aggressive, but other cities haven't necessarily felt that

same sense of urgency. And some city leaders, I think, find it really uncomfortable to be dictating what kinds of landscaping people can have and can't have. Of course, people depend on the Colorado River. That is the point of this whole conversation. But I mean, what about other creatures? How is this ecosystem around the river changing with less water? Yeah, the ecological impacts here are huge. We had three dry years in a row where river flows were way down. I know here in Colorado, where I live, rivers up high in the mountains were getting so warm that fish were getting too stressed and dying in large numbers. The lack of water also contributes to the prevalence of wildfires. I mean, who else did you talk to for this huge reporting project? I really tried to center the series

around this idea that the big overarching solution to the Southwest's water woes is using less. That's what I hear when I talk to scientists and water managers. We are going to have to live within what the river provides to us. And that's incredibly difficult because we've created a ton of demand for water in the Southwest. But that is really the way forward here. And so I spend much of the series visiting with people who are already doing that, already adapting to the scarcity to see what we might all glean from their experience. Luke Runyon is host and producer of Thirst Gap, learning to live with less on the Colorado

River, which is a new podcast from KUNC Public Radio. He's based in Grand Junction, Colorado. Thanks so much, Luke, for joining me. Hey, thanks for having me. And you can check out Thirst Gap wherever you get your podcasts or at KUNC.org slash Thirst Gap. We have to take a break. And when we come back, why humans tend to project human traits onto artificial intelligence. We'll get into the complicated bonds between humans and bots. Stay with us. This is Science Friday. I'm Kathleen Davis. And I'm Sophie Bushwick. Artificial intelligence has become increasingly more sophisticated

in a very short amount of time. Even though we may understand that when Chad GPT spits out a response, there's no human writing us back. Yet, we, we can't. can't help but anthropomorphize, maybe imagining that the AI has thoughts or feelings, even a personality. So how exactly should we understand this bond between human and artificial intelligence? Joining me now to help answer this question and more is my guest, Dr. David Gunkel, Professor of Media Studies at Northern Illinois, based in DeKalb, Illinois. Dr. Gunkel, welcome to Science Friday. Hello, thanks for having me. To start off, why do we as humans have this tendency to anthropomorphize technology, including AI?

So anthropomorphism is a human behavior that is manifested in a number of different places and in different ways. We anthropomorphize our animals like our pets. We anthropomorphize our technologies. And there's been decades of research under the umbrella term, the media equation that looks at this phenomenon. And we actually anthropomorphize each other. Anthropomorphism is the way that we understand another social entity as social. We don't know what goes on in the head of another person or an animal for that matter, but we project into them intentional states, emotions, thoughts, etc.

And this is part of what it means to be social. In fact, we could say anthropomorphism is kind of the social glue that allows us to be social animals and to engage with others in this exact way. And does a physical presence like a robot, for example, change the kind of thoughts and feelings we project onto AI versus just a disembodied chatbot? So there are two things that really trigger anthropomorphism. One is speech. And that's because human beings, since the ancient Greeks define the human being as the animal with speech, we understand speech as being really intimately connected to who and what we are as a species. So if something talks, we tend to accord to it certain expectations that go along with what we accord to other human beings who also possess speech. The other factor that really is powerful in the triggering of anthropomorphism is movement and social presence. And so we'll find that even very rudimentary social presence

or just rudimentary movement can actually cause us to anthropomorphize objects in ways that we normally wouldn't if they weren't in motion. A good example of this was a, done several years ago by a researcher named Wendy Jew in which she created a Ottoman that just moved around the room. And it didn't have a face. It didn't have the ability to talk or anything. It just moved. And when people came into the room, the Ottoman would either run away from them or cozy up to them. And as a result, they started to say, well, the Ottoman's happy to see me or the Ottoman's mad at me today. And none of that is actually going on inside the Ottoman, but it is part of that social presence and the way that the Ottoman is moving within the space that's

occupied by the human beings. First of all, that sounds adorable. And I've seen something similar. There were these trash cans that had a remote controller so a human could steer them around and they would roll around and people would say, oh, it wants my trash. And talking about robots makes me think about this idea of the uncanny valley. When a robot kind of looks like a human, but it's just a little off. That has a different effect on the type of relationships we form with it, right?

Right. So the uncanny valley hypothesis is this idea that as robots or any other object starts to look more and more human-like, we begin to accept it as human or human-like until a certain point is reached where it gets creepy. And we get a little creeped out by the fact that it's just too close to an actual human being to make us feel comfortable. This is why a lot of the morphology for robots tend to use animals as opposed to human beings as their model. because as animals, the uncanny valley expectation or the creepiness that happens as a result of that doesn't transpire as readily. And so a lot of social robots are designed to emulate animals as opposed to actually try to be the facsimile of a human being. And it's not all bad to anthropomorphize robots to some extent. So how can we draw on our desire to make robots seem more human but use it for good?

Are there some examples of this? Yeah. So anthropomorphism, I think, is one of these things that is often addressed as a kind of binary. Either it's good or bad. And I don't think that gets us very far in understanding our human interaction with the other things in our world. I think we've got to look at this more as a degree of difference and come up with a way of understanding the opportunities and the challenges of anthropomorphism so that we are not just either embracing it wholly or dismissing it. completely. I say this all the time to my students. Anthropomorphism is not a bug we're trying to fix. It's a feature. We're trying to manage and we're trying to manage well for ourselves as individuals,

but also as a community. But there's a really big one that came out several years ago, and that's with soldiers working with explosive ordinance disposal robots in the field of battle. And these robots are not autonomous. They don't have friendly looking faces. They don't talk to us. They're mainly remote controlled. They're kind of tank-like objects with a big arm that reaches out. and grabs a bomb to diffuse it. But because of the way that these robots interact with the unit and the way in which they really protect the unit from these explosive ordinances that are in the field, they are given names. The soldiers that work with them, award them battlefield promotions, and in some cases have even risked their own lives to protect that of the robot. Or when the robot is

destroyed, they collect the pieces very carefully and ask for the manufacturer to please return their Scooby-Doo to them. They don't want a new one. They want that robot. because that's their comrade. Wow. You know, these are soldiers. These are not, you know, people who are lost in some sort of ideology of robots or science fiction. They've got a job to do.

But in order for that job to be done effectively, they need to work with the robot in very close quarters and they need to create connections with the robot that allow them to function as a team. And this is where the anthropomorphism, I think, really works quite well. It allows for the soldiers and the robot to create these very workable. scenarios in which the soldiers rely on the robot, and that reliance doesn't even need to be bidirectional. It can just be, you know, the soldiers value the robot. And as a result, they have an emotional connection to the object. That reminds me of the very intense feelings that

the people who worked on the opportunity Mars rover had when they decommissioned it. Yeah, that was a really good example because I think this is something that surprised a lot of us when NASA decommissioned the rovers, there was this outpouring of emotion on social media. And it shouldn't have surprised us, but it did. And the reason it shouldn't have surprised us is that NASA really invited the anthropomorphism by giving these robots a kind of personality in their social media presence, by allowing the robots to talk for themselves, using the first person singular pronoun, to talk about their activities on Mars.

And so this is part of a very concerted effort to, build public trust in this project and get people really invested in these rovers on this very distant world. But it also meant that when these rovers were no longer functioning and they were being decommissioned, people suffered. They went through a kind of grief as they were losing a companion. They were losing something in which they were really invested emotionally, personally, you know, in which they would check in daily to see what the news from Mars was from the rovers. So I think we've got to recognize that, you know, with all these opportunities, there's also challenges and there's also hardship that has to be managed. And that's why I say

this is not about an either or. This is about really effective management. And us as human beings knowing how to create the opportunities, but also how to address the challenges when they come. And of course, projecting these human-like traits onto AI has some serious drawbacks as well. What sticks out to you? Yeah, there's a lot of things to be. worried about. And as you can tell, there has been a lot of press on what we could call the bad examples or the bad outcomes. So one example is the way in which the large language models are able to generate text that is very readable, very legible, but also very confident sounding. And that has led a number of users to trust that what the large language model is providing

is somehow accurate and valid. And obviously it is not. And there are a lot of examples on social media and elsewhere about how wrong and how misguided a lot of the outcomes from the large language models can be. So if we just trust that what is coming out of these things is acceptable, we could be in a situation where we are exposed to some danger and some problems with regards to misplace trust in the algorithm. Another really big recent example is in Europe where a man was said to have been talked into suicide by his interactions with chat GPT.

Now, these are very dramatic. They get a lot of press, but they do point to the fact that this emotional investment that we're making in our technologies also is a vulnerability. And it's a vulnerability that we have to be aware of and that we have to be ready to confront so that we are adequately protecting our. ourselves as we engage with these technologies. Misplaced trust, that issue makes me think of a term coined by the data journalist Meredith Broussard, techno-chovinism. We assume technology can do a task better than humans can. Are we more likely to follow advice generated by AI rather than a human-generated solution? So this is a really old question. In fact, it goes all the way back to Plato and a disruptive

technology that really shook up the Greek civilization. And that technology was called writing. And Socrates was worried that people would trust writing more than the people who know the things they speak about and that this misplaced trust would lead the youth astray and cause society to crumble and fall apart and have this catastrophic outcome for human beings. Now, obviously, we figured out writing and it didn't do exactly what was predicted by Socrates. So I think we've got to use our own history with media and technology as a guide for how we gauge what the real dangers are and how well we are suited to respond to those challenges. And I don't think it means that every technology repeats the same pattern, but I do think it means that every response that we

have to disruptive technology tends to fall in line with these historical patterns. And that gives me some confidence that we'll also figure out large language models. It's just going to take some time and a lot of experimentation. I want to talk a little about chatbots. There's a company called Replica that creates AI chatbots, and it basically offers to provide an emotionally available AI best friend. So does this change the dynamic at all, that promise of a human-like experience? Yeah, I think it changes it in a very significant way. We have to remember that a lot of these applications, a lot of these products are created by very powerful and very influential multinational corporations.

We think of organizations like Google, like OpenAI, like Amazon. So that when you're talking to Siri, you're not talking to Siri. You're talking to Apple. When you're talking to Alexa, you're not talking to Alexa. You're talking to the corporation who is taking your data to create a profile and help anticipate your needs and sell you products. So I think with something like Replica, we have to look at it as part of their marketing to get people engaged with using this piece of technology to position it in this way.

But again, this is not new. All of our consumer products are sold to us with the promise of something bigger than just the product. You think about why we buy automobiles. It's because it is pitched and marketed to us as a way of creating influence or sex appeal or whatever else. You think about how we sell cosmetics or how we sell lifestyle. These are not about the product per se, but about a marketing

framing for the product. And I think we see the same thing going on with these AI products. And so I think we need to be aware of what powerful influence is behind these products, their development and their distribution, and how our interacting with these services and these products may be serving some other needs of the organization that stands behind the individual item that we think we're talking to. This is Science Friday from WNYC Studios. I'm Sophie Bushwick. If you're just joining us, I'm talking with Dr. David Gunkel, media and technology scholar at Northern Illinois University. I recently interviewed the hosts of a podcast who followed several people who had developed long-term relationships with AI chatbots.

One person had used her bot as a sort of dating coach, and that ended up backfiring because she said the bot was so good that it ruined her for dating real men. So are we losing something by having these intimate and meaningful relationships with AI instead of humans? Yeah. So this is a worry that we hear from a number of corners. And I think it's worth thinking about as we engage with these technologies. But I also think we get a lot of hyperbole that is associated with these kinds of very dramatic outcomes. There's just as many examples of people who have used these things as a way of helping them become more social. You can think already back to the debate about video games. Will playing video games make us antisocial and never leave the house and only want to interact online? We can think even further back the invention of the novel. When the novel was invented, it was worried that women would spend too much time reading romances

and not go out and do the family's tasks and get married. make children. So there's a worry that is being repeated, I think. For me and what I try to do in my research and with my students is remember our own history with technology and ask the question, how much of this is repeatable, how much of it is different, what is changing, and it really get a good understanding of the different things that have to be balanced in making these opportunities these available to us, but also protecting ourselves from some dangers and some challenges that may come along with them. It doesn't seem like AI is going to go away anytime soon. So what's your vision for the future of how humans interact with AI? The thing that makes me optimistic,

I have to say, is when I hear about what artists are doing with these various tools, things like the diffusion models for images or the large language models for text. There's a lot of experimentation going on in the community of artists. And we see people like Mark America experimenting with large language models to write his novels. We see people like Holly Herndon working with an AI voice model trained on her own voice for collaborating and creating new musical compositions. And I think if we look at how this experimentation is going, we can see some real effort to try to test the limits of what this AI is giving us. and also see what the real challenges are. So I look to the artists as leaders in sort of thinking through a lot of the very practical,

but also very interesting possible futures that we're confronting as these technologies become more a part of our everyday lives. Thank you so much for coming on the show. What a fascinating conversation. Thank you for inviting me. It's been really great talking with you about this, and I wish you well. Dr. David Gunkel is a professor of media studies at Northern Illinois University, based in DeKalb, Illinois. Are you a teacher or caregiver who's concerned about AI's impact on your learners?

Maybe you want to learn more about how it all works or find ways to prepare your students for the future. Well, Science Friday has you covered. This May, we're hosting an entire month of great conversations about AI in STEM education with free student activities to learn about artificial intelligence, chatbots, and machine. learning. So check out ScienceFriiday.com slash AI month for information. That's ScienceFriiday.com slash AI month. We have to take a break. When we come back, sampling the environment of a city by looking at what it's bees find. Stay with us. This is Science Friday. I'm Kathleen Davis. When you want to look at the health of a city,

there are a bunch of ways that you can go about it. You can look at medical records or maybe air quality, or in recent years, samples of wastewater have been used to track COVID outbreaks. But now researchers are offering another approach to sample a city's environment. It's beehives, using the bees foraging in a city to provide information about the bacteria and the fungi there. Joining me now is Elizabeth Hennoff. She is an assistant professor in the NYU Tandon School of Engineering at New York University. She's a co-author of a report on the approach that was recently published in the journal Environmental Microbiome. Welcome to Science Friday. Glad to be here. So you study environmental microbiomes. Before we get to the bees,

can you explain to me what does this mean? So we think of the environmental microbiome as a population of microorganisms. So that's both bacteria, but also viruses and also protists that can be found in the environment that we interact with. There's a kind of emerging body of literature. that shows that human health and well-being is tightly related to our relationship with our own microbiome, our gut microbiome, our skin microbiome, for example. And the human microbiome interacts with and is sculpted by the environmental microbiome. So let's get to the buzzy news in your study. What makes bees such a good way to study the microbiome of a city? Well, the challenge with studying the microbiome of a city is that a city is a very large surface area to cover. And the tool that we have

used most commonly to take biological samples for microbiological studies is the swab that we're all overly comfortable with or uncomfortable with. But the size of that tool is not quite adjusted to the size of the thing that we want to study. So a swab allows us to sample maybe a square foot area, of a particular environment. But if we want to get the read of a microbiome of, say, a whole block or a whole neighborhood, that tool isn't quite well adapted to that particular resolution, that particular size. And so we were really looking for some kind of system that existed in a city already that would allow us to collect aggregate information about the microbiome of a larger area,

so say a block or a neighborhood. And so that's how we got to thinking about bees. Because basically bees are doing what we've in the past asked armies of undergrad students to do when we're running these citywide studies, which is to go out into the environment, interact with things, and always come back to the same place. And so it turns out that bees are coming back with a lot more information or material than what they set out to forage and we're able to use some of the material that the bees recover to understand the microbial fingerprint of the environment they're foraging in. So it sounds like they're not just picking up the bacteria on flowers, for example. Are they kind of picking up just whatever is out there? Yeah. So our assumption was that bees were going to come back with plant-related microorganisms because that's what they're most frequently physically interacting with. But it turns out that they were recovering microbes for all sorts of other environments. So say aquatic environments, if there happened to be a body of water nearby, or also mammalian systems, like. like human-related microbes or even dog-related microbes, the bees are really traversing this kind of rich, three-dimensional microbial environment as they're foraging. And so as they're traversing these

microbial clouds, they're bringing back that microbial information and then depositing it at the bottom of the hive when they enter the hive and then we're able to collect that material. So you studied hives in several different cities, including New York, Tokyo, Venice, and Sydney, Australia. What sort of differences did you find? So what we saw looking at those cities across the globe is that different cities have different microbial signatures as seen by honeybees. Perhaps most interesting is that even within a city, different neighborhoods will have different microbial signatures. Did you find anything in this debris that signaled, oh, this makes sense to find this sort of microbe in, say, this Tokyo High? or this makes sense to have found in this Venice hive.

I mean, were there any things that really gave you a sense of place that you found in this debris? I think the example for that would be the study that we did in Venice. So one of the main organisms that we recovered in Venice was a fungus related to wood rot, which makes sense because Venice is a city built on wooden pilings, a submerged wooden pilings. So it makes sense historically and architecturally. So zooming out, I mean, now that we know this, where do we go from here? I mean, do you see a future where humans could regularly look at hives and maybe see that there's a disease floating around a city? Yeah, I mean, so there's obviously some constraints to this method that we're well aware of.

One of the constraints being is that there is a bee season, at least in more northern parts of the world, like New York City. So bees are active only from, you know, the end of spring to the beginning of fall. And so as far as using this as an epidemic surveillance method, that's one of the constraints. We also don't know what our false negative rate is. So we don't know what is out there, but we're not recovering. But we do know that the genomic data or genetic data that we're able to recover is rich enough to be able to identify certain types of pathogens. But maybe even more so than using this as a surveillance mechanism, What's really interesting to me is that this is a study and an approach that allows us to think

of cities as kind of multi-species assemblages. That actually cities, you know, we think of them as designed for humans and by humans, but they are very much inhabited by a whole host of other species. And it's looking at the interactions of those species. So in this case, insects and microbes and humans altogether, they were able to kind of approach them and study them as a biological superstructure. Are there other species that you think might have a future as good samplers? I mean, I'm just thinking of things like bird nests or other creatures that move around a lot and collect things.

So there's examples in the literature of people using leeches as a way to study to get aggregate information from other organisms in an ecosystem. So leeches as, you know, being blood-sucking organisms. And then if you collect a leech and you can assess the genomic signatures of the blood of the different species that leach has extracted from, you can get a read of biodiversity in that area. And that's been used really successfully to monitor for endangered species that are maybe hard to identify or to count in other ways. Obviously, we can't use leeches in New York City. and I'm really glad that that is actually not a methodology that's available to us.

But there are other examples of kind of using one organism as a proxy measure for understanding a whole other ecosystem that it's interacting with. Fascinating stuff. Elizabeth Hennoff, assistant professor in the NYU Tandon School of Engineering at New York University. Thank you so much for joining me. Thank you so much. This is Science Friday. I'm Sophie Bushwick. here's a question. What happens right after you pick up a book or pull up some text on your phone? What goes on between the words hitting your eyes and your brain understanding what they represent? And is that process different when you look at a story versus a series of unrelated words like those in a grocery list? Just how the brain processes written information isn't fully understood. But work published this month in the proceedings of the National Academy of Sciences, might offer some clues. Joining me now to talk about that is one of the authors of that report.

Dr. Nittentandin is a professor of neurosurgery at UT Health, Houston. Welcome to Science Friday. Thank you so much, Sophie, for having me. Reading seems like a pretty straightforward thing. So why don't we know how it works? Reading happens at such a rapid pace that we have not in the past had tools to study it effectively. people have used various brain imaging techniques, but they lack the time resolution or the space resolution to be able to understand it well. Reading is the fastest input system to our brain.

So the average reader reads around 300 words a minute, and a speed reader can read as many as 1,500 words per minute. And as you can imagine, that's an extremely rapid transmission of information, up to about 500 years ago, almost no one on our planet could read. And if you consider that here we are a primate brain capable of understanding the shapes of branches and twigs and forks in a river, how do we then take this enormously complex alphabetical system that exists today and build that upon these brains that haven't done this in millennia? So we found that to be a particularly puzzling and important question to ask.

And that has really been the focus of our research over the last decade or so. And in your recent study, you worked with people with epilepsy. Why were they a key to this research? Yeah. So as we've just discussed, reading is a very rapid process. And to study a process of this speed, the best modality that we actually have, is electrodes placed in the brain. In many individuals with epilepsy, the site where seizures start is not exactly well defined.

And the standard is for us to implant tiny probes to understand and to create a network of where the seizures begin and how they propagate. So the opportunity that we've been given in individuals who have electrodes implanted in their brain to pinpoint where seizures begin provides us to take. with very high spatial temporal characteristics that can enable us to really delve into the reading processes. So using those existing electrodes, you could monitor what parts of the brain were activated during different tasks? Exactly. And so while these individuals are in our epilepsy monitoring unit waiting for seizures to happen, they have several days on hand that they're sitting around and sort of bored.

And this is the opportunity that we use to give them various materials to read. and study their brain activity as they read. And what did you find? So we were interested specifically in understanding how, what the difference in the brain was that allowed us to memorize or to learn strings of words, put together strings of words that were meaningless words that still tried to communicate some global concept and then actual sentences. And we found that the regions that do,

this are very closely related to each other. One is in the temporal lobe just above your left ear, and one is in the frontal lobe just next to the area of the brain that allows us to speak. And these two zones communicate with each other in different ways when single words are being read and being understood, and in a different, more complex way when sentence or phrase level information is being transmitted. And so, specific, Specifically, when there's a sentence that is building up on meaning, so I could say something like, Jack took his black cat to the vet. So Jack took his black cat is one phrase in that sentence. And at that point, when that phrase ends, there is a spike in activity that amalgamates that chunk of

information together. A lot of that has to do with word frequency, meaning that words that have lower frequency, less common words, are the ones around which the brain binds information together. And then these chunks of information get stitched together to create the meaning of the sentence. Just a reminder that you're listening to Science Friday from WNYC Studios. I'm Sophie Bushwick talking with Dr. Nittin Tandon about the brain and reading. What about silent reading versus reading something aloud? Does the brain respond differently? Yeah, it does. And so this entire experiment was people reading silently. But if people read out

aloud, two things happen. The first is that you read slower because your speech production rate is only so fast. And the second is that your auditory systems are much, much more online as opposed to just your reading systems. This is, of course, how we all learn to read originally. And one of our goals here is to elaborate why some individuals cannot read well. So dyslexia or the inability to read affects about 10% of all people. And they either cannot read at all or the reading is very slow. And what we are trying to do here is to create a map of how normal reading operates so that we can extrapolate what is likely going wrong in people who cannot read well.

Aside from the special patients with these electrodes, what do you need to make this type of experiment work? Yeah, it takes a really special group and dedicated group of researchers, and I'm privileged to have postdoctoral fellows like Oscar Wilna and Elliot Murphy and a collaborator across the Atlantic in France, Stan DeHan, who've all been critical for this work to happen. And of course, none of this could happen without funding. and the NIH Brain Initiative has really launched a whole bunch of fantastic explorations of the neurobiology of language and of other systems in the human brain all across the country. And I'd like to credit them as well. What do you still want to know? What is the next question you want to explore about the way the brain processes reading? There are three or four interesting new directions we're going in. One is trying to see if we can teach adults new words. And one of our experiments is giving them exposure to very uncommon English words.

English has about 350,000 words in it. But most people's vocabulary is only a few tens of thousands of words. So we're trying to see what happens when people learn new words. And what that process looks like over an interval of about five to seven days while they're with us in our epilepsy units, waiting procedures to happen. Another interesting question for us is trying to understand if we can give people symbols that they've never been exposed to before and have them learn a whole new alphabet. And so for this, we are using Gaelic runes from the United Kingdom. And does this tell us anything about how we made that that leap you talked about from? Yes. Right, in order to read in the first place. Yeah. So what we've

learned, and this is an earlier paper that we've published, is that the same regions of your brain, that are very interested in fine patterns. So for example, distinguishing between two human faces or two geometric shapes are very, very closely aligned with and likely overlapping with the areas that enable us to read. There are two patches of brain regions in the base of the brain next to the occipital lobe that are critical for this.

One is called the lateral occipitopor temporal region or the classic visual visual. whole world form area and the other is the mid-phusiform cortex. And the interaction between these two areas is critical for us to take a shape and understand it. And so this is just that, you know, whether you have an A that is written in italics or in Gothic font or is written on the side of a building 10 stories high, it is still the letter A. And so this sort of invariant representation of a symbol lives in these two areas. and both of them appear to be quite critical for us to read letters.

Well, we wish you luck in decoding all of these brain areas and what they do. Dr. Nittentandan is a professor of neurosurgery at UT Health Houston. Thank you for taking the time to talk with me today. Thank you so much, Sophie. It's been a pleasure. And that's about it for this hour. If you missed any part of this program, or you'd like to hear it again, subscribe to our podcasts. Or ask your smart speaker to play Science Friday. day. I'm Sophie Bushwick. And I'm Kathleen Davis. Have a great weekend.