Photographs by Maciek Miloch, Set Design by Zuza Slominska, Food Styling by Nadine Page, Prop Styling by Pawel Wyszynski
Long after we’ve conquered the cosmos, we’ll still be eating potatoes, but that doesn’t mean that the way we breed, grow, harvest, distribute, prepare, and enjoy those potatoes won’t evolve. In fact, it already has. Despite a lack of Jetsonsian aesthetics, we have blasted off into a brand-new food age over the past decade or so. It hasn’t been an easy journey. Food is complicated, and we have a complicated relationship with it. Advances in everything from gene sequencing to satellite photography to the Notify button on restaurant reservation apps have provided us with tools to understand our food and ourselves better than ever before, while the rise of artificial intelligence and machine learning have provided us with a means to chart that data into actionable paths forward. Here is where the future of food has been hiding.
Precision Agriculture
Along with the institutional knowledge of generations of farmers intimately familiar with the quirks of their land, we’ve long been able to gather bits of quantitative data about soil composition, drainage, precipitation, and temperature conditions of farms. Those disparate pieces, while helpful in informing a farmer’s game plan each season for a single field, have historically lacked a crucial through line to stitch together a bigger picture of how our crops are performing in real time. We now have that thread in the form of satellite imagery. With the help of an abundant low-orbit flock of satellites from private companies and various nation states, now you can obtain a quality snapshot of a farm or an entire region about once a day.
This opens doors for how we farm. Instead of overdosing fields with fertilizer—which is cheap—to hedge against missing out on a boom crop, farmers might be able to target and tailor their fertilizer dosage to areas that need it most, in turn reducing the environmental impact of overfertilization. When we develop a new crop that has nutrition or flavor advantages but requires more resources to grow, we can lay out those differences in plain, quantitative terms, enabling us to make informed choices in cases where human health and climate concerns may not be aligned. We have the ability to learn more than ever about one plot on one farm or thousands of farms scattered around the globe. We can ask and answer questions that were never possible before.
Biotechnology
Food, like all living things, is a wiggly mishmash of molecules that are constantly changing. Old-school crossbreeding is a blunt-force technique that smashes two genomes together, and it has historically taken several years, often more than a decade, to sort through the results and weed out all the undesirable genetic debris that hitched a ride with the target genes. For centuries we had to cross two plants, produce hundreds of offspring, and wait for months or years to see which specimens had the traits we were looking for. With the advent of molecular-genotyping techniques in the ’80s and ’90s, we gained the ability to take a sneak peak at select sections of a baby plant’s genome, rather than waiting for its full life cycle to play out. Those techniques were revolutionary, but still slow. Today we have the ability to analyze millions of plant samples in the time it used to take to plod through dozens, which means plant breeders are unlocking more delicious, nutritious, and prolific crops in record time, shaving years off the time it takes to get a new plant variety ready for market.
Even with our supercharged genetic surveillance power, however, there is a ceiling on what can be accomplished without genetic engineering. Technologies like the use of CRISPR, a DNA modification trick we learned from bacteria, allow us to replace the head-on genetic car crash of traditional crossbreeding with the precision of a Formula 1 pit crew, targeting the exact genes in the exact locations we want them with incredible fidelity. The technology is well established, but the regulatory and cultural discussion surrounding genetic modification is the most polarizing topic in food. With changes in our nutritional needs, flavor preferences, and climate change accelerating at an increasingly alarming rate, it’s comforting to know that we don’t have to wait for the future to take the next massive technological leap. We’ve already done it; we just need to decide how to use what we’ve found.
Hyperpersonalization/Consumer Health
People, with all of our dizzying diversity of genetics, habits, and ages, represent some of the most complex systems that science has ever tried to model and understand. Throw food into that chaos blender and you’ve got a level of complexity that is literally beyond human comprehension. Megan Fisklements, PhD, a food scientist who specializes in big datasets and the interaction between food and our health, says that the last five years constitute the first era in history where we’ve had the computing power to ask the Big Questions about the intersection between food and our bodies. “Computational work used to be intended to do things like algebra faster than a person can do. But we could eventually figure it out, if given enough time. Now we’re doing computations that we were never going to be able to do with our own brains.” Datagathering tools like continuous glucose monitors, step trackers, and heart-rate monitors are widespread, and high-throughput methods for analysis like fecal-sample sequencing are allowing us to gather quantities of data about how food is affecting our bodies that are beyond our ability to comprehend. AI and machine learning systems, however, can help us do the work that every grad student in every lab in the world would never catch up to.
We no longer need to smooth every nutritional data point out into population-scale trends; we can now embrace and learn from all of our individual variations. We have zoomed in on the biochemistry that underpins questions such as which foods have a molecular connection to which diseases or which foods are best suited to a specific person’s genetics and lifestyle. For the first time in our history we’ve been able to ask and answer the question, “What does this food do to me?”
Transport/Retail
The slow, meandering processes of breeding and growing produce are marathons that gives way to a breakneck sprint the moment it is picked. “The product is dying as soon as you remove it from the tree,” says Irwin Donis-González, PhD, and codirector of the University of California-Davis Postharvest Research and Extension Center. He and his colleagues in the postharvest world work to maintain the quality of produce on its journey to market, with the goal of delivering consumers the most delicious, high-quality products possible.
That job has gotten easier with improvements in measurement. In addition to more reliable and widespread data on benchmarks like ambient temperature and humidity, advanced metrics such as internal produce temperature and near-infrared data paint a clearer picture of the condition of commodities like avocados on their journey from field to market. Aided by this worm’s-eye view, we can make informed decisions on when to refrigerate to preserve quality or when to let temperatures rise to encourage ripening so that a given crop’s arrival to market is perfectly synchronized with peak quality and flavor. The more attention we pay, the more we learn: Improving shock absorbers on transport trucks that carry berries can prevent them from softening, losing color, and becoming less fragrant.
Dining Evolution
Your dining experience used to begin once you walked into a restaurant. Now it can start weeks before your reservation. You can watch the rhythm of daily changes to a restaurant’s menu through its Instagram Stories, and some restaurants even post movie-trailer-style hype videos for new dishes. Innovations like digital reservation notes, food preference profiles, and the Notify button feel ubiquitous, but before platforms like Resy, OpenTable, and Tock started noting your proclivities and letting you know when reservations became available, the conduit for conversation between diners and restaurants was ultranarrow.
Our broadening digital connection to restaurants has unlocked new possibilities for how they manage their operations. Alex Faulkner, GM of Nancy’s Hustle in Houston, spent hours tinkering with the restaurant’s Resy profile to tackle one of the issues that plagues most restaurants: how to accommodate as many guests as possible during peak hours without burying kitchen and front-of-house crews. She found that within a time window where a section of the restaurant could accommodate 12 guests, there were massive advantages to booking a two-top, a four-top, and a six-top rather than six tables of two. Parties of two tend to get straight to the point of ordering, whereas larger parties are more likely to spend several minutes greeting each other and deciding whether to get a round of appetizers for the table. When programmed into the framework of their reservation system, the information provides automated yet organic pacing to avoid a tsunami of urgent orders without compromising the number of guests that can be seated at the same time.
Our futuristic food present has less chrome and robotic beeping than some expected, which might be why this version of the future of food, where subtle, behind-the-scenes innovations orbit around and enhance, not supplant, the real stars of the food system—the food on our plates and the people we share it with— feels comfortingly familiar. We haven’t mastered our bodies, our food, or our farms, we’ve just finally learned to have meaningful conversations with them, and a lot of the major decisions that guide the next phase of our food future will depend on how we collectively feel about what they have to say.