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Heritage algorithms combine the rigors of science with the infinite possibilities of art and design

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The model of democracy in the 1920s is sometimes called “the melting pot” – the dissolution of different cultures into an American soup. An update for the 2020s might be “open source,” where cultural mixing, sharing and collaborating can build bridges between people rather than create divides.

Our research on heritage algorithms aims to build such a bridge. We develop digital tools to teach students about the complex mathematical sequences and patterns present in different cultures’ artistic, architectural and design practices.

By combining computational thinking and cultural creative practices, our work provides an entry point for students who are disproportionately left out of STEM careers, whether by race, class or gender. Even those who feel at home with equations and abstraction can benefit from narrowing the gap between the arts and sciences.

What are heritage algorithms?

Traditional STEM curricula often present science as a ladder you climb. For example, you might be told that math starts with counting, then goes to algebra, then calculus and so on.

But our research has found that the global history of science is more like a bush: Each culture has its own branching set of discoveries. Some of these discoveries offer a perspective that’s different from the theorem-proof approach for math or hypothesis-experiment approach for biology. Understanding the rules and techniques that create cultural patterns from the maker’s point of view can help bridge the gap between knowledge branches. We refer to these hybrids of computation and culture as heritage algorithms, and there are examples everywhere.

Flying over an African village, you can see the recursive geometry of African fractals in their architecture: circles of circles, rectangles within rectangles, and other “self-similar” structures. These fractal patterns also appear in their textiles, carvings, paintings, ironwork and more.

Other kinds of algorithms underlie the repeating sequences of bent wood arcs that make up Native American wigwams, canoes and cradles. Even henna tattoos demonstrate the interactions among computation, nature and culture.

These heritage algorithms challenge the myth of “primitive cultures” – the idea that early Africans had no math past counting on fingers or that Native American agriculture lacked sophistication.

The computational thinking that is embedded in Indigenous artifacts and other creative practices, such as weaving, beadwork and quilting, is not merely decorative. It also reflects different ways of thinking about the world. Our interviews with artisans revealed how they visualize spiritual concepts in formal techniques and numerical sequences.

Bringing heritage algorithms to the classroom

Heritage algorithms give students a way to blend the abstract rigors of math, the grounded legacies of culture and the infinite possibilities of art. To bring these algorithms to the classroom, we have created interactive computer programs and simulations that we call culturally situated design tools, or CSDTs.

Each CSDT was created in collaboration with Indigenous elders, street artists, traditional crafters and others. With the creators’ permission, we transfer their knowledge of pattern creation into digital tools that students enjoy using and teachers enjoy implementing in their lesson plans.

It’s important to craft each CSDT to reflect the way those artisans think about the cultural practice. For instance, the slope of the line y=x, mathematically calculated as “rise over run,” is 1 – for every unit you move up the line, you move a unit to the right. This line forms a 45-degree angle with the x-axis. But when Navajo weavers use this “up one, over one” pattern, the slope is closer to a 30-degree angle. This is because they weave yarn horizontally through vertical cords that are thicker than the yarn. So we made sure to preserve this feature in the weaving simulation we built.

A crucial aspect of CSDTs is that students may use them to follow their interests. This freedom and independence lets students encounter new cultures, delve deeper into their own identity or mix designs from different cultures to create something completely new.

We have seen Black students choose an Appalachian quilting simulation, Native American students choose cornrow simulations and white students create beadwork simulations. Students’ creative designs often mix many cultures together – cornrows become “powwow braids,” and African fractal simulations turn into plants, lungs and river deltas.

Heritage algorithms and CSDTs provide a powerful starting place for students to improve their computing skills and confidence. These tools even provide a foundation for a variety of careers, from architecture to environmental engineering.

When computation and culture collide

The reach of heritage algorithms has recently extended beyond learning environments to contemporary art spaces. Artists are generating a bold new creative style using “ethnocomputing” – an understanding of computer science from a cultural perspective.

You can see fresh interpretations of heritage algorithms in the African fractals embedded in the work of visual artist Tendai Mupita, the cornrow simulations integrated in the work of Rashaad Newsome, the blending of the African diaspora and technology by Nettrice Gaskins and the creative duo Tosin Oshinowo and Chrissy Amuah.

An exhibition on display in New York City, the U.K. and Los Angeles explores the textile techniques of artists inspired by the African American quilting tradition of Gee’s Bend, Alabama.

Our research on heritage algorithms is partially driven by a philosophical desire to reframe STEM as a source of radical joy for every ethnicity and identity. Inspired by the radical feminist phrase “sex-positive feminism,” we sometimes call our perspective “race-positive design” – thinking of race not in purely negative terms of oppression but instead as a rich source of creativity, liberation and a free-thinking mindset for curiosity and scientific inquiry.

This philosophical stance also has a practical side: statistically significant improvement in STEM scores for underrepresented students. Many teachers have recognized the potential of heritage algorithms for getting students invested in STEM. One teacher using the graffiti tool told us this was the first time students asked if they could stay in her math class after school. Another said she would never teach negative numbers again without the bead loom CSDT.

Heritage algorithms, both in the classroom and beyond, open up a two-way bridge between humanistic and technical knowledge. They offer a space where everyone – teacher and student, young and old, geek and artist – can learn, share and collaborate.

^^^

Audrey G. Bennett, University Diversity and Social Transformation Professor, Stamps School of Art & Design, University of Michigan and Ron Eglash, Professor of Information, University of Michigan.

This article originally appeared in The Conversation under a Creative Commons Liscense

Feature Image by James Wheeler via Pexels

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The truth behind a successful social media platform

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Nowadays, just about anyone can launch their own social media platform to the public— but its simplicity doesn’t come without its tribulations. More than half the world uses social media on a daily basis, averaging 2 hours daily on platforms like FaceBook and Instagram. Each year, sites are seeing a 3% increase in user signups, indicating that social media is solidifying its presence in society on a global scale. While these aspects may sound promising to the next social media entrepreneur, it reveals the competitive nature behind the ever-growing technology industry. 

Currently, there are 7 platforms that dominate the social media market, with 4 being owned by META corporation. It is estimated that 4.88 billion identities are registered online as of July 2023, making social media the largest international digital connection. Most users are active on 6 or 7 platforms, meaning that a registered account doesn’t guarantee usage. Unlike other forms of media, social media relies on its users to generate content and spur activity, and inactivity guarantees the death of the platform. 

META’s recent social media creation, Threads, shows how easy it is for a platform to die out despite its large user base. In an attempt to rival Twitter, META’s biggest competitor, Zuckerberg and team decided to create a platform eerily similar, except users must register using their Instagram credentials and identity, binding the two platforms to each other. At first, Threads saw great success with 27.8 million downloads during the first week in the USA alone. In less than a week, Threads managed to gain half as many users as Twitter, a platform created back in 2006. While these reports seemed promising for the future of Threads, 70% of accounts were reported as inactive by its third week of existence. 

Photo by Julio Lopez via Pexels
Photo by Julio Lopez via Pexels

While there are various factors contributing to Threads’ decline, perhaps the most notable aspect was Threads dependence on its mother platform, Instagram. Forcing users to link their Instagram credentials to their Threads profile guarantees a lack of curated online identity, which often will lose users’ excitement as it provides nothing new. Content generation, curation, and maintenance is too similar to Instagram, leading to users disengaging. Why maintain another social media profile when Instagram already exists? 

This phenomena is certainly not new to the world of social media, yet it’s a cautionary tale about the trials and tribulations of a new social media platform. Even for well established companies like META, a new platform’s success is not guaranteed. It can be difficult to identify how the market will respond to a new social media platform as both technology and people’s desires seem to be changing at rapid rates. Therefore, one must go beyond the technical components in order to ensure their social media platform’s success, and maintain activity. 

One of the newest popular social media platforms, BeReal, has achieved enormous success due to its ability to target an aspect of the market missing on other platforms. Built upon “authentic use” , BeReal allows users to post one photo a day highlighting their lifestyle “in real time”. It is now the fastest growing social media app for Gen. Z users worldwide, with a 313% surge of signups this past year. The creators targeted those who felt that social media was “inauthentic”, which seems to be quite the lucrative market. In this instance, identifying a gap within the social media market for users has paid off greatly for BeReal. From its creation in 2020 to now, it seems BeReal is here to stay for many avid social media users. 

While social media’s fruitful rewards seem promising to a young entrepreneur, it takes a lot more than one may think to be successful. Take it from companies like META, a projected profit on paper is not always reality for the social media market. It takes great creativity, skill, and perhaps a bit of luck to crack into the ever-expanding world of social media. 

^^^

Katie Williams, Rome Design Agency

Feature Image by Geri Tech via Pexels

Image by Mikhail Nilov

3 ways AI is transforming music

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Each fall, I begin my course on the intersection of music and artificial intelligence by asking my students if they’re concerned about AI’s role in composing or producing music.

So far, the question has always elicited a resounding “yes.”

Their fears can be summed up in a sentence: AI will create a world where music is plentiful, but musicians get cast aside.

In the upcoming semester, I’m anticipating a discussion about Paul McCartney, who in June 2023 announced that he and a team of audio engineers had used machine learning to uncover a “lost” vocal track of John Lennon by separating the instruments from a demo recording.

But resurrecting the voices of long-dead artists is just the tip of the iceberg in terms of what’s possible – and what’s already being done.

In an interview, McCartney admitted that AI represents a “scary” but “exciting” future for music. To me, his mix of consternation and exhilaration is spot on.

Here are three ways AI is changing the way music gets made – each of which could threaten human musicians in various ways:

1. Song composition

Many programs can already generate music with a simple prompt from the user, such as “Electronic Dance with a Warehouse Groove.”

Fully generative apps train AI models on extensive databases of existing music. This enables them to learn musical structures, harmonies, melodies, rhythms, dynamics, timbres and form, and generate new content that stylistically matches the material in the database.

There are many examples of these kinds of apps. But the most successful ones, like Boomy, allow nonmusicians to generate music and then post the AI-generated results on Spotify to earn money. Spotify recently removed many of these Boomy-generated tracks, claiming that this would protect human artists’ rights and royalties.

The two companies quickly came to an agreement that allowed Boomy to re-upload the tracks. But the algorithms powering these apps still have a troubling ability to infringe upon existing copyright, which might go unnoticed to most users. After all, basing new music on a data set of existing music is bound to cause noticeable similarities between the music in the data set and the generated content.

Furthermore, streaming services like Spotify and Amazon Music are naturally incentivized to develop their own AI music-generation technology. Spotify, for instance, pays 70% of the revenue of each stream to the artist who created it. If the company could generate that music with its own algorithms, it could cut human artists out of the equation altogether.

Over time, this could mean more money for giant streaming services, less money for musicians – and a less human approach to making music.

2. Mixing and mastering

Machine-learning-enabled apps that help musicians balance all of the instruments and clean up the audio in a song – what’s known as mixing and mastering – are valuable tools for those who lack the experience, skill or resources to pull off professional-sounding tracks.

Over the past decade, AI’s integration into music production has revolutionized how music is mixed and mastered. AI-driven apps like Landr, Cryo Mix and iZotope’s Neutron can automatically analyze tracks, balance audio levels and remove noise.

These technologies streamline the production process, allowing musicians and producers to focus on the creative aspects of their work and leave some of the technical drudgery to AI.

While these apps undoubtedly take some work away from professional mixers and producers, they also allow professionals to quickly complete less lucrative jobs, such as mixing or mastering for a local band, and focus on high-paying commissions that require more finesse. These apps also allow musicians to produce more professional-sounding work without involving an audio engineer they can’t afford.

3. Instrumental and vocal reproduction

Using “tone transfer” algorithms via apps like Mawf, musicians can transform the sound of one instrument into another.

Thai musician and engineer Yaboi Hanoi’s song “Enter Demons & Gods,” which won the third international AI Song Contest in 2022, was unique in that it was influenced not only by Thai mythology, but also by the sounds of native Thai musical instruments, which have a non-Western system of intonation. One of the most technically exciting aspects of Yaboi Hanoi’s entry was the reproduction of a traditional Thai woodwind instrument – the pi nai – which was resynthesized to perform the track.

A variant of this technology lies at the core of the Vocaloid voice synthesis software, which allows users to produce convincingly human vocal tracks with swappable voices.

Unsavory applications of this technique are popping up outside of the musical realm. For example, AI voice swapping has been used to scam people out of money.

But musicians and producers can already use it to realistically reproduce the sound of any instrument or voice imaginable. The downside, of course, is that this technology can rob instrumentalists of the opportunity to perform on a recorded track.

While I applaud Yaboi Hanoi’s victory, I have to wonder if it will encourage musicians to use AI to fake a cultural connection where none exists.

In 2021, Capitol Music Group made headlines by signing an “AI rapper” that had been given the avatar of a Black male cyborg, but which was really the work of Factory New non-Black software engineers. The backlash was swift, with the record label roundly excoriated for blatant cultural appropriation.

But AI musical cultural appropriation is easier to stumble into than you might think. With the extraordinary size of songs and samples that comprise the data sets used by apps like Boomy – see the open source “Million Song Dataset” for a sense of the scale – there’s a good chance that a user may unwittingly upload a newly generated track that pulls from a culture that isn’t their own, or cribs from an artist in a way that too closely mimics the original. Worse still, it won’t always be clear who is to blame for the offense, and current U.S. copyright laws are contradictory and woefully inadequate to the task of regulating these issues.

These are all topics that have come up in my own class, which has allowed me to at least inform my students of the dangers of unchecked AI and how to best avoid these pitfalls.

At the same time, at the end of each fall semester, I’ll again ask my students if they’re concerned about an AI takeover of music. At that point, and with a whole semester’s experience investigating these technologies, most of them say they’re excited to see how the technology will evolve and where the field will go.

Some dark possibilities do lie ahead for humanity and AI. Still, at least in the realm of musical AI, there is cause for some optimism – assuming the pitfalls are avoided.

^^^

Jason Palamara, Assistant Professor of Music Technology, Indiana University

This article originally appeared in The Conversation under a Creative Commons License

Feature Image by Mikhail Nilov via Pexels 

Photo by Erik Mclean

Why homes often feel warmer than the thermostat suggests – and what to do about it

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Picture two homes on the same street: one constructed in the 1950s and the other in the 1990s. There are no trees or other shade. The air conditioning units are identical, recently replaced, and operating perfectly. Identical thermostats are set at 82 degrees Fahrenheit (27.8 Celsius).

When it’s 110 F (43.3 C) outside, the 1950s house will likely feel at least 10 F (5.6 C) warmer inside, even with the same air temperature.

Why?

The answer has to do with radiant heat. Radiant heat is what keeps you toasty warm at a campfire on a cold winter night. The fire doesn’t warm the air much; rather, like the Sun, most of the fire’s heat moves through invisible waves directly from the campfire to your body.

In the radiant heat of the Arizona sun, the surface temperature of the uninsulated post-and-beam ceilings in my house, one of 41,000 built in Tucson during the post-World War II era, can reach over 100 F (37.8 C). The single-glazed steel windows register 122 F (50 C), and the uninsulated concrete block walls aren’t much cooler.

Inside my house on triple-digit days, it can feel like I’m standing near a campfire, even with the air conditioner roaring to maintain 75 F (23.9 C). And when the system breaks – as it did during the long-running 2023 heat wave, when Phoenix hit 110 F (43.3 C) every day for weeks – temperatures rise dangerously fast. Without the AC, the hot surfaces plus the swirl of air from the ceiling fan makes the house feel like an air fryer.

Air temperature: An incomplete indicator of comfort

While people are used to thinking about how clothing, air movement, temperature and humidity affect comfort, two lesser-known measures help explain how they experience comfort indoors:

  1. Mean radiant temperature. This is the average temperature of all the surfaces that surround us: ceiling, windows, walls, floor. For radiant heat to move between an object and the human body, it needs an uninterrupted line of sight, so ceilings and unobstructed windows have an outsized influence on the radiant temperature experienced in a specific place in a house.
  2. Operative temperature. This can be approximated by averaging the mean radiant temperature and the average air temperature in a room. Other calculations of operative temperature take into account effects of air movement, humidity and additional variables. Roughly half of how you experience comfort is determined by the radiant environment.

Unfortunately, as the building scientist Robert Bean (no relation) says, “an entire industry of manufacturers, suppliers, builders and tradespeople incorrectly equate thermal comfort with air temperatures.” The result is that most people are completely oblivious to what actually makes a space feel comfortable — or uncomfortably hot.

On a hot, sunny day, good insulation and double-pane windows slow heat transfer enough for air conditioning to keep the mean radiant temperature inside the building within a few degrees of the air temperature.

However, in an under-insulated building, such as my house, or in some older public housing projects in Phoenix, the high mean radiant temperature can push the operative temperature over 90 F (32.2 C) – even with the thermostat set to 75 F (23.9 C). When the surface temperature exceeds the temperature of our skin, heat will begin to radiate from the hot surface into the body, making heat stroke more likely.

While the exact threshold where overheating becomes dangerous is debated, most people would agree that 90 F (32.2 C) is far too warm for comfort.

Hot surfaces are why smaller buildings, such as mobile homes, tiny homes, shipping containers and garages turned into apartments, often feel uncomfortable regardless of the thermostat setting. Smaller structures expose occupants to three, four or even six surfaces with the exterior exposed to the sun and hot outside air. More warm surfaces, more discomfort.

Cooler surfaces, more comfort

If you live in an under-insulated building and don’t mind using more electricity, you can set the thermostat lower. But if the mean radiant temperature is high, a 2 F (1.1 C) drop in air temperature will feel like only 1 F (0.6 C) — and those hot surfaces will still make you feel uncomfortable.

Adding insulation to your roof and replacing single-pane windows with double-pane units with low-emissivity (low-E) glass can help reduce the mean radiant temperature and your energy bills. They’re expensive improvements, but new federal tax credits and forthcoming rebates, to be administered by individual states, can help.

Trees, awnings and exterior shades can also reduce mean radiant temperatures by blocking direct sunlight. However, glass is a lousy insulator, so in very hot climates, single-pane windows completely protected from the sun can still become uncomfortably warm.

Adding a curtain inside — and keeping it closed — can help decrease mean radiant temperature because the curtain will be closer to the air temperature than the glass.

What about renters in old buildings?

Renters in older, under-insulated buildings are often less able to afford large energy bills, and landlords may be unable or unwilling to make expensive improvements. Making matters worse, older air conditioning systems use two to three times as much energy as newer units to deliver the same amount of cooling.

Since creating a comfortable operative temperature requires setting the thermostat lower, an HVAC system in an under-insulated building must work longer and harder, using more energy and further raising the cost. And the costs of discomfort are not only financial: Hot buildings also have adverse impacts on health and productivity.

Millions of Americans now live in places where cooling is the only thing preventing a mass casualty event. In Phoenix, city code requires rental units cooled by air conditioning to maintain a temperature of no more than 82 F (27.8 C), measured 3 feet above the floor in the center of the room. Unfortunately, the code does not specify whether 82 F is the operative temperature or the air temperature.

That one word makes a world of difference.

In an older, under-insulated building similar to my house — or, in what might be the worst-case scenario, a sun-fried southwest unit of the top floor of an uninsulated concrete high-rise — a seemingly safe air temperature of 82 F could easily mask dangerous operative temperatures of 96 F (35.6 C) or higher.

The key to better design

As a professor of architecture and building science, I believe today’s byzantine building codes and rental rules could be greatly improved for comfort by regulating mean radiant temperature rather than air temperature. Vast sections of code could be jettisoned by requiring that interior surfaces, which are easy to measure with an inexpensive infrared thermometer, be kept within a comfort range above 60 F (15.6 C) and below 85 F (29.4 C).

For more comfortable buildings, architects and engineers can apply simple, established principles, such as natural ventilation, shading and the right insulation and windows for the climate. Keeping heat out in the first place means we don’t have to spend so much on energy for cooling. Research shows that these measures can also make us safer by keeping buildings cooler for longer in summer power outages.

The happy result: homes and other buildings that are not only comfortable, but also safer and more affordable to operate.

^^^

Jonathan Bean, Associate Professor of Architecture, Sustainable Built Environments and Marketing, University of Arizona

This article originally appeared in The Conversation under a Creative Commons License

Feature Image by Erik Mclean via Pexels

Photo by ThisIsEngineering

Computer science can help farmers explore alternative crops and sustainable farming methods

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Humans have physically reconfigured half of the world’s land to grow just eight staple crops: maize (corn), soy, wheat, rice, cassava, sorghum, sweet potato and potato. They account for the vast majority of calories that people around the world consume. As global population rises, there’s pressure to expand production even further.

Many experts argue that further expanding modern industrialized agriculture – which relies heavily on synthetic fertilizer, chemical pesticides and high-yield seeds – isn’t the right way to feed a growing world population. In their view, this approach isn’t sustainable ecologically or economically, and farmers and scientists alike feel trapped within this system.

How can societies develop a food system that meets their needs and is also more healthy and diverse? It has proved hard to scale up alternative methods, such as organic farming, as broadly as industrial agriculture.

In a recent study, we considered this problem from our perspectives as a computer scientist and a crop scientist. We and our colleagues Bryan Runck, Adam Streed, Diane R. Wang and Patrick M. Ewing proposed a way to rethink how agricultural systems are designed and implemented, using a central idea from computer science – abstraction – that summarizes data and concepts and organizes them computationally, so we can analyze and act upon them without having to constantly examine their internal details.

Big output, big impacts

Modern agriculture intensified over just a few decades in the mid-20th century – a blink of an eye in human history. Technological improvements led the way, including the development of synthetic fertilizer and statistical methods that improved plant breeding.

These advances made it possible for farms to produce much larger quantities of food, but at the expense of the environment. Large-scale agriculture has helped drive climate change, polluted lakes and bays with nutrient runoff and accelerated species losses by turning natural landscapes into monoculture crop fields.

Many U.S. farmers and agricultural researchers would like to grow a wider range of crops and use more sustainable farming methods. But it’s hard for them to figure out what new systems could perform well, especially in a changing climate. Lower-impact farming systems often require deep local knowledge, plus an encyclopedic understanding of plants, weather and climate modeling, geology and more.

That’s where our new approach comes in.

Photo by Pixabay
Photo by Pixabay via Pexels 

Farms as state spaces

When computer scientists think about complex problems, they often use a concept called a state space. This approach mathematically represents all of the possible ways in which a system can be configured. Moving through the space entails making choices, and those choices change the state of the system, for better or worse.

As an example, consider a game of chess with a board and two players. Each configuration of the board at a moment in time is a single state of the game. When a player makes a move, it shifts the game to another state.

The whole game can be described by its “state space” – all possible states the game could be in through valid moves the players make. During the game, each player is searching for states that are better for them.

We can think of an agricultural system as a state space in a particular ecosystem. A farm and its layout of plant species at any moment in time represent one state in that state space. The farmer is searching for better states and trying to avoid bad ones.

Both humans and nature shift the farm from one state to another. On any given day, the farmer might do a dozen different things on the land, such as tilling, planting, weeding, harvesting or adding fertilizer. Nature causes minor state transitions, such as plants growing and rain falling, and much more dramatic state transitions during natural disasters such as floods or wildfires.

Finding synergies

Viewing an agricultural system as a state space makes it possible to broaden choices for farmers beyond the limited options today’s farming systems offer.

Individual farmers don’t have the time or ability to do trial and error for years on their land. But a computing system can draw on agricultural knowledge from many different environments and schools of thought to play a metaphorical chess game with nature that helps farmers identify the best options for their land.

Conventional agriculture limits farmers to a few choices of plant species, farming methods and inputs. Our framework makes it possible to consider higher-level strategies, such as growing multiple crops together or finding management techniques that are best suited to a particular piece of land. Users can search the state space to consider what mix of methods, species and locales could achieve those goals.

For example, if a scientist wants to test five crop rotations – raising planned sequences of crops on the same fields – that each last four years, growing seven plant species, that represents 721 potential rotations. Our approach could use information from long-term ecological research to help find the best potential systems to test.

One area where we see great potential is intercropping – growing different plants in a mixture or close together. Many combinations of specific plants have long been known to grow well together, with each plant helping the others in some way.

The most familiar example is the “three sisters” – maize, squash and beans – developed by Indigenous farmers of the Americas. Corn stalks act as trellises for climbing bean vines, while squash leaves shade the ground, keeping it moist and preventing weeds from sprouting. Bacteria on the bean plants’ roots provide nitrogen, an essential nutrient, to all three plants.

Cultures throughout human history have had their own favored intercropping systems with similar synergies, such as tumeric and mango or millet, cowpea and ziziphus, commonly known as red date. And new work on agrivoltaics shows that combining solar panels and farming can work surprisingly well: The panels partially shade crops that grow underneath them, and farmers earn extra income by producing renewable energy on their land.

Modeling alternative farm strategies

We are working to turn our framework into software that people can use to model agriculture as state spaces. The goal is to enable users to consider alternative designs based upon their intuition, minimizing the costly trial and error that’s now required to test out new ideas in farming.

Today’s approaches largely model and pursue optimizations of existing, often unsustainable systems of agriculture. Our framework enables discovery of new systems of agriculture and then optimization within those new systems.

Users also will be able to specify their objectives to an artificial intelligence-based agent that can perform a search of the farm state space, just as it might search the state space of a chessboard to pick winning moves.

Modern societies have access to many more plant species and much more information about how different species and environments interact than they did a century ago. In our view, agricultural systems aren’t doing enough to leverage all that knowledge. Combining it computationally could help make agriculture more productive, healthy and sustainable in a rapidly changing world.

^^^

Barath Raghavan, Associate Professor of Computer Science and Electrical and Computer Engineering, University of Southern California and Michael Kantar, Associate Professor of Tropical Plants & Soil Sciences, University of Hawaii.

This article originally appeared in The Conversation under a Creative Commons License

Feature Image by ThisIsEngineering via Pexels

 

Photo by Damir Mijailovic

Does the direction water rotates down the drain depend on which hemisphere you’re in? Debunking the Coriolis effect in your sink

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In countries near the Earth’s equator, tourists are often dazzled by a demonstration of a mysterious physical phenomenon. A presenter will position three buckets of water – one in the Northern Hemisphere, one in the Southern Hemisphere, and one directly on the equator – and let the water drain out.

Tourists are shown that, as the water drains, the water in the northern bucket rotates in one direction, the water in the southern bucket rotates in the other direction, and the water at the equator doesn’t rotate at all.

The demonstrator might claim that this strange phenomenon is governed by physics, that it’s an example of the Coriolis effect.

The intriguing nature of the Coriolis effect has led to its frequent appearances in urban legends and popular culture, from TV shows to video games.

The Coriolis effect is based on the idea that the spinning of the Earth introduces a physical force, known as the Coriolis force, which affects the way objects appear to move to us Earthbound observers. The Coriolis force causes objects on the Earth’s surface to be deflected in different directions depending on whether they are above or below the equator. The effect is strongest near the poles and weakest at the equator.

The Coriolis effect is legitimately responsible for the behavior of some natural phenomena, like hurricanes, that meterologists and physical oceanographers like the two of us study. But in domestic settings, the spinning of the Earth actually has very little effect on how water behaves. Math can explain how this works – or doesn’t work – in a kitchen sink.

The math behind the phenomenon

Geophysicists use certain mathematical equations, known as the Navier-Stokes equations, to describe the behavior of fluids. Roughly, the Navier-Stokes equations relate the change of fluid velocity – how the fluid moves – to the forces acting on the fluid, subject to a few physical constraints. For example, the equations assume that the overall amount of fluid in the system doesn’t change over time.

But just because physicists and mathematicians can write down these equations, it doesn’t mean we can solve them. In fact, these equations are so difficult to solve that you would win a Millennium Prize and US$1 million if you could do it.

Although there is no known complete solution to Navier-Stokes equations, meteorologists and physical oceanographers can still obtain useful partial solutions. One way to obtain these partial solutions is to compare various terms in the Navier-Stokes equations to determine which ones are most important.

These comparisons are often recorded as ratios and have no associated physical unit, thereby earning them the name “dimensionless numbers.”

What happens in your sink?

In the context of the Coriolis effect, perhaps the most important dimensionless number is the Rossby number, named for the early 20th-century meteorologist Carl-Gustav Rossby. The Rossby number compares the dynamics of the fluid with the Earth’s rotation rate, taking into account how big the system is and how fast it’s moving.

A small Rossby number indicates that the Coriolis force has a strong effect on the system, while a large Rossby number signifies that the Coriolis force has a negligible effect. For example, the Rossby number for an average hurricane is of the order of 1, indicating that the dynamics of the fluid and the Earth’s rotation rate are of similar relevance. It is true that hurricanes tend to rotate clockwise in the Southern Hemisphere and counterclockwise in the Northern Hemisphere.

The same math that applies to large-scale phenomena like hurricanes also applies to the water in your bathroom sink. In this setting, the system is relatively small, and so the Rossby number will be much larger than 1 – more than 10,000 times larger. This observation indicates that the Coriolis force is negligible on water draining in a bathroom sink.

In fact, the Rossby number predicts that the water would need to move at an almost imperceptible speed for the Coriolis force to become significant. So even though the way water swirls down the drain may be consistent, that isn’t due to the Coriolis effect.

So what did the tourists see?

The same logic applies to the equatorial attractions. Given the size of the system, physical oceanographers can comfortably conclude that the Coriolis force is not responsible for what the tourists see in those buckets or bowls.

This conclusion is also supported by examining the same kind of presentation in different countries.

The water in the Northern Hemisphere rotates counterclockwise in one video but clockwise in another video. If the rotation were due to the Coriolis effect, the result would be the same in both videos.

Although physical oceanographers can’t deny what the tourists see, we know that the magic trick isn’t due to the Coriolis effect at such a small scale.

^^^

Francisco José Machín Jiménez, Profesor Titular de Universidad, Oceanógrafo Físico, Universidad de Las Palmas de Gran Canaria and Borja Aguiar González, Personal Docente e Investigador, Universidad de Las Palmas de Gran Canaria.

This article originally appeared in The Conversation, under a Creative Commons license.

Feature Image by Damir Mijailovic via Pexels.

Photo by Buro Millennial

Why ‘Intercultural Communications’ academia may just save the Internet

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As the world delves further into a globalized society interdependent on one another economically, socially, and culturally, the age-old phenomena of intercultural conflict occurs, often on a global stage. 

Digitally, the world is connected to each other in virtually every corner, which has had both its successes and consequences within global society. Internet forums, social media pages, and other digital platforms allow people from Asia to communicate with those in North America in a matter of seconds, which seldom existed previous to this century. The level of awareness and education about different cultures, as well as the information flow between regions is at an all-time high, but this isn’t as positive as you may think. 

If you’ve ever surfed the worldwide web, you’re bound to come across a plethora of ignorance and cultural insensitivity posted from users regardless of the context. Regardless of the users’ intentions, it reveals a larger issue of intercultural communication clashes between populations— an issue that’ll only get worse with increased globalization. 

Intercultural Communications is a field of academia that grew to prominence around the 1950s that American scholar Edward T. Hall is credited for, advancing the field when he was a part of the Foreign Service Institute of the U.S. Department of States. Higher academic institutions across the world began to devise their own academia related to Intercultural Communications, where it remains a prominent field of study today worldwide. It combines a wide range of disciplines like psychology, semiotics, and philosophy to better understand how different cultures interact with each other based on their distinct cultural differences. 

Interesting theories such as Hofstede’s Cultural Dimensions or Information flow and Contra-flow are among some research that could prove beneficial to improving cultural sensitivity online. These ideas present a new way of interpreting the global world, such as the Monochronic vs. Polychronic dimensions or collectivism vs. individualism; it allows us to rationalize the differences we see between populations in a way that minimizes judgment and prejudice. It’s human nature to perceive things that clash with our dominant understandings as negative, especially when it relates to our identities. But this doesn’t mean those initial judgements should be taken as truthful, and may in fact lead to further conflict between groups. 

Photo by Fauxels
Photo by Fauxels via Pexels.

For example, many Westerners may think it’s absurd to eat food primarily with their hands, whereas most nonwestern societies prefer not to use cutlery. Both groups may quickly assume one another is odd, and their way is better, yet these sentiments only further create intercultural conflict. While this example may seem harmless in itself, such predispositions have drastic consequences on intercultural communication, clearly visible within the digital world. 

In 2020, Twitter hate speech against China and the Chinese community increased 900% in part due to the ignorance about the pandemic. In general, internet traffic towards “hate sites” targeting Asians increased 200% in 2020 as well. Digital hate speech trends often reflect overall stereotypes, prejudices, and ignorance held by populations about one another that is echoed through forums and digital interactions. 

44% of digital hate crimes reported in the UK contained Xenophobic or racist motivations in 2020, with most coming from popular social media platforms like Facebook. A further 27% of hate crimes involved religion, with both Islamophobia and Anti-semiticsm equally prevalent online. UK police believe that most digital hate crimes go unreported, meaning that any statistics gathered regarding the digital world often are unrepresentative of the issue at hand. Yet it’s clear from what little data available that most digital hate crimes are rooted in intercultural conflict, which will only get worse as globalization becomes the new normal.  

Most of us access the digital world everyday, whether it’s for personal, professional, or a combination of both purposes. It’s been a great tool for education, sharing the previous secrets of cultures with each other from the click of a button. But current conversations about cultural sensitivity and intercultural communication have yet to match with the digital society, proposing a threat to the progress of the world wide web. Intercultural communications academia may just be the solution to cleaning up our digital world in favor of a positive socio-cultural internet. 

^^^

Kathryn Williams, Rome Design Agency.

Feature Image by Buro Millenial via Pexels.

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