AI needs a human touch to function at its highest level

There is an old saying that speaks to the current state of AI: “To someone holding a hammer, everything looks like a nail.” As companies, governments, and organizations scramble to be in the vanguard of this new generation of artificial intelligence, they are trying their best to persuade everyone that all of our human shortcomings will be absolved by this technological evolution. But what exactly will it solve? Machine learning is an incredibly powerful tool, but, like any other tool, it requires a clear understanding of the problems to be solved in the first place — especially when those problems involve real humans.

Human versus machine intelligence

There is an oft-cited bit from Douglas Adams’ The Hitchhiker’s Guide to the Galaxy series in which an omniscient computer is asked for the ultimate answer to life and the universe. After 7.5 million years, it provides its answer: the number 42. The computer explains to the discombobulated beings who built it that the answer appears meaningless only because they never understood the question they wanted answered.

What is important is identifying the questions machine learning is well-tailored to answer, the questions it struggles with, and perhaps most importantly, how the paradigmatic shift in AI frameworks is impacting the relationship between humans, their data, and the world it describes. Using neural nets has allowed machines to become uncannily accurate at distinguishing idiosyncrasies in massive datasets — but at the cost of truly understanding what they know.

In his Pulitzer Prize-winning book, Gödel, Escher, Bach: an Eternal Golden Braid, Douglas Hofstadter explores the themes of intelligence. He contemplates the idea that intelligence is built upon tangled layers of “strange loops,” a Möbius strip of hierarchical, abstracted levels that paradoxically wind up where they started out. He believes that intelligence is an emergent property built on self-referential layers of logic and abstractions.

This is the wonder that neural nets have achieved — a multi-layered mesh of nodes and weights that pass information from one tier to the next in a digital reflection of the human brain. However, there is one important rule of thumb in artificial intelligence: The more difficult it is for a human to interpret and process something, the easier it is for a machine, and vice versa.

Calculating digits of π, encrypting messages using unimaginably huge prime numbers, and remembering a bottomless Tartarean abyss of information can occur within the blink of an eye using a computer, which manages to outperform millennia of human calculations. And yet humans can recognize their friend’s face in an embarrassing baby photo, identify painters based on brush strokes, and make sense of overly verbose and ruminating blog entries. These are domains that machine learning has made vast improvements in, but it is no wonder that as the human brain-inspired architecture of neural nets brings machines up to parity, and in some cases beyond, in areas of human cognition, machines are beginning to suffer some of the same problems humans do.

Nature or nurture?

By design, we are unable to know what neural nets have learned, and instead we often keep feeding the system more data until we like what we see. Worse yet, the knowledge it has “learned” is not discrete principles and theories, but rather contained in a vast network that is incomprehensible to humans. While Hofstadter might have contemplated artificial intelligence as a reflection of human intelligence, modern AI architects have no tendency to share the same preoccupation. Consequently, modern neural nets, while highly accurate, do not elucidate any understanding of the world for us. In fact, there are several well-publicized instances where AI went afoul, manifesting in a socially unacceptable reality. Within a day of Microsoft’s AI chatbot Tay being active, it learned from Twitter users how to craft misogynistic, racist, and transphobic tweets. Did Tay learn a conceptual sociohistorical theory of gender or race? I would argue not.

Why AI can’t be left unattended

Paradoxically, even if we assume that the purpose of an AI isn’t to understand human concepts at all, these concepts often materialize anyway. As another example of misguided AI, an algorithm was used to predict the likelihood of someone committing future crimes. Statistically based software models learned racial biases, assigning higher risks to black defendants with virtually no criminal records, if any, than to white defendants with extensive histories of violent crime. Facial recognition software is also known to have its biases, to the point that a Nikon camera was unable to determine if a Taiwanese-American woman had her eyes open or not. Machine learning is only as good as the data it is built upon, and when that data is subject to human biases, AI systems inherit these biases. Machines are effective at learning from data, but unlike humans, have little to no proficiency when it comes to taking into account all the things they don’t know, the things missing from the data. This is why even Facebook, which is able to devote massive AI resources to its efforts to eliminate terroristic posts, concedes that the cleanup process ultimately depends on human moderators. We should be rightfully anxious about firing up an AI, whose knowledge is unknowable to us, and leaving it to simmer unattended.

The AI community cannot be haphazard about throwing open the AI gates. Machine learning works best when the stakeholders’ problems and goals are clearly identified, allowing us to chart an appropriate course of action. Treating everything as a nail is likely to waste resources, erode users’ trust, and ultimately lead to ethical dilemmas in AI development.

Mike Pham is a technical product manager at Narrative Science, a company that makes advanced natural language generation (Advanced NLG) for the enterprise.


The Louis Vuitton Cruise 2017 runway show in Niteroi, Brazil. Photo: Fernanda Calfat/Getty Images

What do Tom Ford, Raf Simons, Pierre Balmain, Pierre Cardin and Gianni Versace all have in common? Before kickstarting a flourishing career in fashion, each of these individuals enrolled to study architecture or industrial design.

Fernando Garcia, one-half of the creative director duo behind Monse and Oscar de la Renta, is among that list of designers. He graduated with an architecture degree from Notre Dame — though he vividly remembers secretly reading Harper’s Bazaar or Vogue during lectures in college. (Sorry, Professor Economakis.) “There’s a great sense of satisfaction for me when I’m able to see my designs come to life in a matter of a week or two,” Garcia tells Fashionista when asked about making the switch to a career in fashion. He says his degree is still applicable even when he’s designing clothes, especially when it comes to a general sense of proportion: “I find a building’s façade, for example, to be similar to when I’m trying to find a balance in designing any garment.”

For these designers and their respective brands, along with a slew of others in the fashion industry, architecture serves as an evergreen source of inspiration. “They are both visually driven expressions of personal taste and the times we live in,” says Jane Keltner de Valle, Style Director at Architectural Digest. She cites Virgil Abloh, the brains behind Off-White, as another designer who heavily references architecture in his work. After earning his engineering degree from the University of Wisconsin, Abloh went on to study architecture for graduate school at the Illinois Institute of Technology. “He’s a prime example of someone who doesn’t confine himself to any one medium,” notes Keltner de Valle.

In addition to running a global luxury line, Abloh has created a capsule furniture collection, collaborated with Ikea and has plans to publish a series of books that showcase his clothes alongside iconic structures by Le Corbusier and Mies Van Der Rohe. In an interview with Architectural Digest, Abloh told Keltner de Valle, “The idea is to teach my demographic — the younger generation who’s immersed in fashion — about architecture through these sites.”

Though Nicolas Ghesquière’s education and career is rooted in fashion design, his passion for architecture is widely recognized when it comes to his runway shows. Ghesquière’s Louis Vuitton cruise collections have made their debut within some of the most spectacular works of architecture, including Oscar Niemeyer’s Niterói Contemporary Art Museum in Brazil, and most recently, the I.M. Pei-designed Miho Museum, just outside of Kyoto in Japan.

“I think when I started at Louis Vuitton, I always had this feeling that it had to be travel. And today, people travel a lot for architecture, not only for monuments — and I always thought that the exploration and voyage side of Louis Vuitton could be an architectural journey,” Ghesquière told Suzy Menkes during an interview for UK on his Louis Vuitton Cruise 2016 runway show, which took place at Bob Hope’s home in Palm Springs.

But does fashion ever influence architects? Last spring, I attended Pratt’s annual student graduation show and while leaving the event’s venue, I ended up walking alongside an older couple chatting about the show — or rather, disagreeing. I had gathered that the man speaking had a background in architecture and was telling the woman who was with him about how the runway looks he had just witnessed displayed techniques and practices that would have never been approved in architecture school. Their brief debate is what prompted me to explore the parallels between these two creative fields in the first place.

Shoes by Zaha Hadid for United Nude. Photo: @zahahadidarchitects/Instagram

I posed my question to Dragana Zoric, an adjunct associate professor of architecture at Pratt. She believes that fashion and architecture, at their core, are focused on assembly. The architectural system and technique of “fastening” connects forms or materials in a variety of ways, where sequence is of utmost importance. Fashion’s construction of clothing through patternmaking and sewing follows a similar type of protocol.

“Just like there is a difference between the body and the garment that encases or covers it — for example, the difference would be minimal if clothing was body-hugging — there is a relationship between the building’s structure and skin,” says Zoric. “Both fields utilize, as a base language, innovation, experimentation and fluency with color and texture. In this way, architecture follows fashion.”

At RISD, Carl Lostritto, the architecture school’s Graduate Program Director and Assistant Professor, doesn’t necessarily see architecture pulling from fashion, but rather says that “there’s a territory where the water is muddy and they overlap.” What both Zoric and Lostritto can agree on is that fashion’s advances in fabric manipulation — like digital laser cutting or the use of a 3-D printer — can translate directly into architectural techniques used to define a building’s structural surfaces. “Behaviors of fabrics can be extracted and implemented to work on architectural membranes. I have taught several studios with these as themes,” says Zoric.

Zaha Hadid’s interpretation of a Louis Vuitton bucket bag. Photo: @zahahadidarchitects/Instagram

In our conversation, Lostritto also brings up the late architect Zaha Hadid, who once told that she’d had an interest in fashion since she was a kid. Hadid is both well-known in the fashion world and regarded as a legend in the field of architecture; she worked with high-end brands, playing a role in creating Chanel’s Mobile Art Pavilion, for example, and also tried her hand at fashion design, collaborating with United Nude, Georg Jensen, Fendi, Melissa and Bulgari, among others. Her creations were more structural, naturally, spanning from jewelry and shoes to handbags. During Marc Jacobs’s tenure at Louis Vuitton, he invited Hadid to design her own version of the French house’s iconic bucket bag, which was on display at a special “Icones” exhibit in Paris in 2006.

On a more aesthetic level, fashion designers have also crossed over to interior design, says Keltner de Valle. Pierre Yovonovitch, who used to work at Pierre Cardin, is a rising talent in Paris, while Remy Renzullo, who used to design for Wes Gordon, pursued his talents in interior decorating at the encouragement of Lauren Santo Domingo. “He is now working on a project for her and just finished the New York City apartment of model Jessica Hart,” Keltner de Valle tells us. (You can catch Renzullo’s work in the September issue of Architectural Digest.) Though Kenzo Takada is no longer associated with his eponymous line, he recently collaborated with high-end French furniture company Roche Bobois. Even online, fashion bloggers are turning into home decor influencers.

“It’s all quite fluid,” says Keltner de Valle. “I think there’s always been crossover and fluidity between the two worlds, but we’re seeing it more than ever before now. There are no walls or barriers for the new generation. It’s really refreshing, and I think it’s resulting in some of the best design we’ve seen in a long time.”