Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Through her research and companies, Dr. Picard has developed wearable sensors, algorithms and systems for sensing, recognizing and responding to information about human emotion. Her products are focused on using fitness trackers to advance clinical quality treatments for a range of conditions.
Meanwhile, in just the past few years, numerous fitness tracking companies have released products with their own stress sensors and systems. You may have heard about Fitbit’s Stress Management Score, or Whoop’s Stress Monitor – these features and apps measure things like your heart rhythm and a certain type of invisible sweat to identify stress. They’re designed to raise awareness about forms of stress such as anxieties and anger, and suggest strategies like meditation to relax in real time when stress occurs.
But how well do these off-the-shelf gadgets work? There’s no one more knowledgeable and experienced than Rosalind Picard to explain the science behind these stress features, what they do exactly, how they might be able to help us, and their current shortcomings.
Dr. Picard is a member of the National Academy of Engineering and a Fellow of the National Academy of Inventors, and a popular speaker who’s given over a hundred invited keynote talks and a TED talk with over 2 million views. She holds a Bachelors in Electrical Engineering from Georgia Tech, and Masters and Doctorate degrees in Electrical Engineering and Computer Science from MIT. She lives in Newton, Massachusetts with her husband, where they’ve raised three sons.
In our conversation, we discuss stress scores on fitness trackers to improve well-being. She describes the difference between commercial products that might help people become more mindful of their health and products that are FDA approved and really capable of advancing the science. We also talk about several fascinating findings and concepts discovered in Dr. Picard’s lab including the multiple arousal theory, a phenomenon you’ll want to hear about. And we explore the complexity of stress, one reason it’s so tough to measure. For example, many forms of stress are actually good for us. Can fitness trackers tell the difference between stress that’s healthy and unhealthy?
Show links:
- Dr. Picard’s book, Affective Computing
- Dr. Picard’s bio
- Dr. Picard on Twitter
- Dr. Picard’s company, Empatica - https://www.empatica.com/ - The FDA-cleared Empatica Health Monitoring Platform provides accurate, continuous health insights for researchers and clinicians, collected in the real world
- Empatica Twitter
- Dr. Picard and her team have published hundreds of peer-reviewed articles across AI, Machine Learning, Affective Computing, Digital Health, and Human-computer interaction.
- Dr. Picard’s TED talk
Rosalind Picard
Dr. May Edward Chinn, Kizzmekia Corbett, PhD., and Alice Ball, among others, have been behind some of the most important scientific work of the last century.
If you look back on the last century of scientific achievements, you might notice that most of the scientists we celebrate are overwhelmingly white, while scientists of color take a backseat. Since the Nobel Prize was introduced in 1901, for example, no black scientists have landed this prestigious award.
The work of black women scientists has gone unrecognized in particular. Their work uncredited and often stolen, black women have nevertheless contributed to some of the most important advancements of the last 100 years, from the polio vaccine to GPS.
Here are five black women who have changed science forever.
Dr. May Edward Chinn
Dr. May Edward Chinn practicing medicine in Harlem
George B. Davis, PhD.
Chinn was born to poor parents in New York City just before the start of the 20th century. Although she showed great promise as a pianist, playing with the legendary musician Paul Robeson throughout the 1920s, she decided to study medicine instead. Chinn, like other black doctors of the time, were barred from studying or practicing in New York hospitals. So Chinn formed a private practice and made house calls, sometimes operating in patients’ living rooms, using an ironing board as a makeshift operating table.
Chinn worked among the city’s poor, and in doing this, started to notice her patients had late-stage cancers that often had gone undetected or untreated for years. To learn more about cancer and its prevention, Chinn begged information off white doctors who were willing to share with her, and even accompanied her patients to other clinic appointments in the city, claiming to be the family physician. Chinn took this information and integrated it into her own practice, creating guidelines for early cancer detection that were revolutionary at the time—for instance, checking patient health histories, checking family histories, performing routine pap smears, and screening patients for cancer even before they showed symptoms. For years, Chinn was the only black female doctor working in Harlem, and she continued to work closely with the poor and advocate for early cancer screenings until she retired at age 81.
Alice Ball
Pictorial Press Ltd/Alamy
Alice Ball was a chemist best known for her groundbreaking work on the development of the “Ball Method,” the first successful treatment for those suffering from leprosy during the early 20th century.
In 1916, while she was an undergraduate student at the University of Hawaii, Ball studied the effects of Chaulmoogra oil in treating leprosy. This oil was a well-established therapy in Asian countries, but it had such a foul taste and led to such unpleasant side effects that many patients refused to take it.
So Ball developed a method to isolate and extract the active compounds from Chaulmoogra oil to create an injectable medicine. This marked a significant breakthrough in leprosy treatment and became the standard of care for several decades afterward.
Unfortunately, Ball died before she could publish her results, and credit for this discovery was given to another scientist. One of her colleagues, however, was able to properly credit her in a publication in 1922.
Henrietta Lacks
onathan Newton/The Washington Post/Getty
The person who arguably contributed the most to scientific research in the last century, surprisingly, wasn’t even a scientist. Henrietta Lacks was a tobacco farmer and mother of five children who lived in Maryland during the 1940s. In 1951, Lacks visited Johns Hopkins Hospital where doctors found a cancerous tumor on her cervix. Before treating the tumor, the doctor who examined Lacks clipped two small samples of tissue from Lacks’ cervix without her knowledge or consent—something unthinkable today thanks to informed consent practices, but commonplace back then.
As Lacks underwent treatment for her cancer, her tissue samples made their way to the desk of George Otto Gey, a cancer researcher at Johns Hopkins. He noticed that unlike the other cell cultures that came into his lab, Lacks’ cells grew and multiplied instead of dying out. Lacks’ cells were “immortal,” meaning that because of a genetic defect, they were able to reproduce indefinitely as long as certain conditions were kept stable inside the lab.
Gey started shipping Lacks’ cells to other researchers across the globe, and scientists were thrilled to have an unlimited amount of sturdy human cells with which to experiment. Long after Lacks died of cervical cancer in 1951, her cells continued to multiply and scientists continued to use them to develop cancer treatments, to learn more about HIV/AIDS, to pioneer fertility treatments like in vitro fertilization, and to develop the polio vaccine. To this day, Lacks’ cells have saved an estimated 10 million lives, and her family is beginning to get the compensation and recognition that Henrietta deserved.
Dr. Gladys West
Andre West
Gladys West was a mathematician who helped invent something nearly everyone uses today. West started her career in the 1950s at the Naval Surface Warfare Center Dahlgren Division in Virginia, and took data from satellites to create a mathematical model of the Earth’s shape and gravitational field. This important work would lay the groundwork for the technology that would later become the Global Positioning System, or GPS. West’s work was not widely recognized until she was honored by the US Air Force in 2018.
Dr. Kizzmekia "Kizzy" Corbett
TIME Magazine
At just 35 years old, immunologist Kizzmekia “Kizzy” Corbett has already made history. A viral immunologist by training, Corbett studied coronaviruses at the National Institutes of Health (NIH) and researched possible vaccines for coronaviruses such as SARS (Severe Acute Respiratory Syndrome) and MERS (Middle East Respiratory Syndrome).
At the start of the COVID pandemic, Corbett and her team at the NIH partnered with pharmaceutical giant Moderna to develop an mRNA-based vaccine against the virus. Corbett’s previous work with mRNA and coronaviruses was vital in developing the vaccine, which became one of the first to be authorized for emergency use in the United States. The vaccine, along with others, is responsible for saving an estimated 14 million lives.