A Contemporary Mythology of Man-Machine Symbiosis

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This article was first published in the Human Futures edition of MISC/ magazine, Volume 25.

The motif of the centaur, the half-human, half-horse, originates from Greek mythology and represents a relationship that has evolved throughout history, from food source, to transportation, and beyond. We have found cave paintings of horses dating back over 17,000 years, but it wasn’t until their domestication (estimated to be about 5,000 years ago) that the human-horse relationship led to major innovations in communication, mobility, and trade.

And, just like the image of a human-horse creature may have originated from infantry viewing enemies on horseback in the distance, the merging of human and machine into a hybrid creature is coming more clearly into view. One aspect of this contemporary centaur model for human-computer interaction is the coupling of emotional intelligence (EI) with big data analytics. Researchers investigating this relationship propose that such a coupling is advantageous because emotional intelligence represents our ability to empathize, allowing for the management of interpersonal communication.

We use these skills to overcome obstacles and inspire others to work toward collective goals so that, even in human-machine partnerships, the human will remain the action-inspiring force. Through a centaur-like nervous system, the machine collects data on usage and reveals patterns, trends, and associations as they relate to behavior and interactions. The human remains the strategic driver, understanding lived human experiences in a connected world by applying design research approaches.

Tools and Technology: An Evolution From Passive to Active

Tools have evolved from rocks and stone to tablets, algorithms, and artificial intelligence. As Bryan Johnson, founder and chief executive officer of neuroprosthesis developer Kernel, explains, “we are moving from using our tools as passive extensions of ourselves, to working with them as active partners. An axe or a hammer is a passive extension of a hand, but a drone forms a distributed intelligence along with its operator, and is closer to a dog or horse than a device.” Between the mythological human-horse centaur and the modern human-machine centaur, it seems we are coming full circle. Technology is becoming more “horse-like” again, working as an active extension of the human rather than a passive tool.

J.C.R. Licklider, an MIT professor and key figure in defining modern computing and the internet, explored the concept of human-machine partnerships in his research on man-computer symbiosis in the 1960s. According to Licklider, “human brains and computing machines will be coupled together very tightly, and… the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.”

In Greek mythology, most centaurs were governed by their bestial halves. Their behavior was wild, lustful, and small amounts of wine drove them even wilder. One of the best-known centaurs was named Chiron, who, unlike most of his brethren, was known for his civility and wisdom, and renowned for his medicinal knowledge and ability to teach music and hunting – presumably influenced by his human side. The question to consider is: Which half will guide us in our quest for human-machine symbiosis in our modern centaur story?

Design Research: An Active Tool for Human Futures

Design research is an approach we use to gain an understanding of relationships and interactions between people, technology, our environment, and the artifacts and actors within it. Even as centaur-like collaboration continues to evolve, a challenge remains: Once our products and services are released into the world, we often lack immediate knowledge of the actual human experience with them. We either collect quantitative data, which allows for quick but basic product optimization, or we collect qualitative data, which takes longer to address and apply.

Although design research is an iterative approach, one of the primary constraints is the frequency and relevancy of the iterations to improve experiences, products, and services. If we take the idea of a human-machine centaur designing new products and services collaboratively, and embed those designs into an IoT context of connected devices and things, we can create an iterative feedback loop. We can equip artifacts with a nervous system and create the opportunity to drastically increase the frequency of design research iterations and improve the relevancy of design research data. Johnson envisions connected products “reviewing themselves through data, saying things like, ‘I was only used once before breaking,’ or, ‘I’ve been used for 354 days straight and had one minor malfunction.’” The design researcher, as the human-half of the modern centaur, is critical in adding an understanding of the subjective human experience with those devices and services beyond obvious performance improvements.

Design research is undergoing an evolution of its own, moving the focus from simple user-centricity to co-designing and participative approaches; it is shifting from being a passive tool to being an active one, and is leading us to new paths of collaborative creativity. With that, design research represents a continuous evolution of different approaches and application areas, including: participatory design through the collaboration between the end user and a professional designer conducting speculative design research; co-creation by both a design researcher and a foresight practitioner; and adversarial design, where a team of professional designers and political scientists are involved. However, to date, these various approaches operate under the assumption that design teams are comprised of only human participants.

Yet, many of the prevailing theories influencing design practice, such as actor-network theory and assemblage theory, have begun to question the assumption of a human-only outlook. Perhaps the model of the centaur nervous system, functioning as an iterative feedback loop to understand and improve the lived experience of the products and services, can lead us to Licklider’s vision of human-machine symbiosis.

A Partnership for the Modern Centaur

1997 was a milestone for the modern-day human- machine centaur. That year, for the first time, a machine – IBM’s Deep Blue – beat then chess grandmaster Garry Kasparov. Assuming that human players augmen- ted by AI would be even better than the computer by itself, Kasparov developed what is now called freestyle chess (sometimes called centaur chess). Confirming his assumption, Intagrand – a hybrid team of humans and several different chess programs – is the reigning chess grandmaster today. As AI innovations continue, the concept of centaur partnerships can go beyond the world of chess and inform other forms of modern collaboration. But just what does a centaur model mean for future relationships and interactions between people, technology, our environment, and the artifacts and actors in our connected world?

Today’s Centaur: The Robo-Advisor

Finance has long utilized technology supported by human counterparts. For years, options traders have used algorithms to time when they enter and exit a position. Big banks soon followed with buy/sell sites, and now large institutions like Fidelity Investment are offering customers a robo-advisor solution, Fidelity Go. While competing services use algorithms to make decisions about investments with as little human input as possible, Fidelity Go combines its robo-advisor technology with human experts to make personalized investment suggestions, putting the human back in the strategic driver seat.

The Nervous System: An Iterative Feedback Loop of AI and EI

Maurice Conti, director of strategic innovation at Autodesk and leader of their Applied Research Lab, describes the need for an AI-powered nervous system for the continuous on-the-go evaluation and evolution of products and services: “Our nervous system, the human nervous system, tells us everything that’s going on around us. But the nervous system of the things we make is rudimentary at best. For instance, a car doesn’t tell the city’s public works department that it just hit a pothole at the corner of Broadway and Morrison. A building doesn’t tell its designers whether or not the people inside like being there, and the toy manufacturer doesn’t know if a toy is actually being played with – how and where and whether or not it’s any fun.” Could we create a better nervous system by combining AI-driven sensor systems with design research approaches? Can we tap into our ability to empathize and interact with others and the AI technology to help us match millions of data points to choose the most strategic and effective next step in order to refine and adjust again and again?

What’s Next, Self-Iterating Centaur-Designed Cars?

Just like technological advances in transportation have taken us from cruise control to adaptive cruise control to driverless cars, the development of human-machine partnerships should evolve to give us the ability to understand the experiences and interactions of all actors and artifacts in a connected world.
Hack Rod is an example of what the AI contribution to the nervous system could look like. Mike “Mouse” McCoy founded this digital industrial startup after running the award-winning entertainment studio Bandito Brothers. In 2016, Bandito Brothers collaborated with Conti at the Applied Research Lab at Autodesk, and equipped a traditional race car with dozens of sensors, creating four billion data points as a world-class driver drove it for a week. The car’s nervous system captured everything that was happening to the car, after which the team took this data and plugged it into DreamCatcher, their generative design AI. Generative design allows engineers and designers to input design goals and parameters (like materials and cost constraints) into the software to simulate design outcomes prior to production. Using cloud computing, the software then explores all possible configurations, generating design alternatives.

As Conti explains, “What do you get when you give a design tool a nervous system? This is something that a human could never have designed. Except a human did design this, but it was a human that was augmented by a generative-design AI, a digital nervous system and robots that can actually fabricate something like this.” If the designer knew the true usage of their designs in the world, they could have designed a better experience. According to Conti, generative design is “a computational system that allows engineers and computers to co-create things they couldn’t have accomplished separately.” It’s true co-creation by a modern-day centaur. Or is it?

This case study can offer a single data point in an emerging future on how design researchers and AI will innovate through the centaur model. In order to truly supplement each other’s skills, the centaur team of the future should look like this: a design researcher, which brings human-centricity, empathy, communication-skills, and participatory approaches, and a machine-counterpart, which collects past and current data and presents possible future scenarios. The human now acts as a driving force during the data collection, the design, and even after the launch, co-creating a new human future continuously and seamlessly.

One way to think about centaur interaction and co-creation and what it might look like is to consider Bill Buxton’s approach to sketching. Buxton, a pioneer in the field of human-computer interaction, defines “sketching along a continuum, which starts with rough drawings at the ideation stage and increases in fidelity to the point of prototype, the usability stage.” Creating 2D and 3D modeling iteratively and collaboratively at the fuzzy front end of innovation, coupled with the continuous feedback loop the nervous system provides, will enable us to reduce the risk of product and service failures after a launch.

The Future Centaur

In our contemporary vision of the centaur, we see how this human-machine collaboration can greatly improve the lived experience for humans as we interact with new products, services, and technologies. Let’s think about the nervous system in terms of reacting to and co-creating the human lived experience as it is happening. The differentiating piece for the modern centaur is a better process to facilitate interaction and co-creation, as it develops human-centered products, services, and experiences, refining and evolving far beyond the official “release date.” This is how we ensure the focus on human futures – AI provides the data and analytical power, but EI remains as the driving force. The human half trumps the “bestial half” – just like our mythical predecessor, Chiron.

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