[Editors note: This article is a companion article to Mickey McManus' previous article entitled "How to Build an IoT Apocalypse." Both articles are written from the point of view of some time in the future. They take a look back on the choices we may make today and how those decisions could play out over time.]
As we look back at the last century and explore the early beginnings of the age of Networked Matter, it may be worth taking a moment to consider where it all began. How did we "pass through the eye of the needle" of unbounded malignant complexity and get to the other side?
Today we take it for granted that we live among a sea of information devices that have faded into the woodwork, extended our reach and helped us collaborate on a galaxy-spanning society that has uplifted tens of billions of life forms. Our birth planet is rich with the flora and fauna of both natural and artificial life and is a veritable garden of delight for all who visit. Some of the most astounding new advances in science and art come from collaborative minds comprised of humans, meta-humans, and machines.
Just as brick and mortar architects and engineers came to the forefront when cities began to rise, the community of design scientists has been lauded for their efforts in architecting a rich and resilient era of networked matter.
The seeds of the era are many fold but most historians and pioneers agree that one seminal work by Nobel Laureate Herb Simon called, The Sciences of the Artificial, framed a key concept early on. Simon offered up a parable that design scientists took to heart:
There were once two watchmakers, named Hora and Tempus, who manufactured very fine watches. Both of them were highly regarded, and the phones in their workshops rang frequently — new customers were constantly calling them. However, Hora prospered, while Tempus became poorer and poorer and finally lost his shop. What was the reason?The watches the men made consisted of about 1,000 parts each. Tempus had so constructed his that if he had one partly assembled and had to put it down — to answer the phone, say — it immediately fell to pieces and had to be reassembled from the elements. The better the customers liked his watches, the more they phoned him, and the more difficult it became for him to find enough uninterrupted time to finish a watch. The watches that Hora made were no less complex than those of Tempus. But he had designed them so that he could put together subassemblies of about ten elements each. Ten of these subassemblies, again, could be put together into a larger subassembly; and a system of ten of the latter subassemblies constituted the whole watch. Hence, when Hora had to put down a partly assembled watch in order to answer the phone, he lost only a small part of his work, and he assembled his watches in only a fraction of the man-hours it took Tempus.
Simon's watchmakers exemplified the difference between designing using architecture with a capital "A" and designing a house of cards. This was a powerful principle of beautiful complexity called hierarchy. It sits alongside other core principles of design science like modularity, redundancy and generativity. Simon went on to note that complex systems were "nearly hierarchical" in nature. Ultimately this meant that not everything fit in a perfect box, un-modeled features that bled across boundaries could lead to hard-to-predict emergent properties. Even to this day, unintended consequences remain a challenge for design and society. These principles are well regarded and accepted by 22nd-century school children today as they craft their worlds, but that wasn't always the case.
While we have long become accustomed to our things and places capturing reality and providing us with dreams for what could be, there was a primitive time before things could actually aspire or catch dreams of their own. A time when design tools were oddly confined to creating the birth (launch) and death (recycling) of things and places, rather than the rich inner lives they lived throughout their existence. Where Computer Aided Design (CAD) was really little more than a set of documentation tools that resided on a desktop or in some sort of rudimentary client server system known as the cloud. It's hard to imagine today that our communities of things were frozen in their infant forms, blind, dumb, mute and with no imaginations to share, no social connections with each other or us. Authoring was somehow relegated to a single creative team designing from the top down.
In rich ecologies we find that the nature of an organism (the genetic makeup given by its creator at the time of its birth) shapes how it engages with the system, but we also find that organisms are shaped by how they are nurtured over their lifetime. The concept of nature and nurture — where in essence we have to design for a little loss of control so that a thing or place can evolve in the wild based on what sort of ecosystem it finds itself within — seemed unknown at the time. It was a sterile existence.
In early 2016 a handful of organizations recognized they had a responsibility and a role to play in the future of making and learning at a system level. They undertook an epic journey of reinvention and shaped a response to the existential threat of the early 21st century, namely unbounded malignant complexity.
A research lab named MAYA, off the eastern coast of Pittsburgh sounded the early warning response system with their seminal book entitled, Trillions and others took up the call. One such company of note was in what is now known as the Sunken Burning Collectivate but at the time was known as California — that company was called Autodesk.
Even at this early date Autodesk realized that the future wouldn't be about making things, but rather about making systems. They understood that making and learning were intimately tied together and that a system view that encompassed creative teams that included humans and machines would foster an accelerated and fruitful co-evolution. They embarked on the reinvention of authoring tools for the physical world on two fronts. Under one initiative they explored a new idea for collaborating with machines called "Goal Directed Design." Concurrently they experimented with what would happen when artificial intelligence and generative design intersected with lifelong learners to drive enhanced and open-ended "Generative Learning." Early efforts demonstrated that machine/human collaborative teams accelerated discovery and optionality while increasing cenhognitive plasticity in both forms of life. It was a surprise to researchers at the time that machine algorithms could shed light on human learning and reinforce metacognition. They saw their first hints at the potential to give humankind what has in effect become a sense that today we all take for granted. What historical records first called "Systems123D" we know as our sense of "ecology."
They started by dreaming about helping creators design not only the things and places of the future but also the flows between those things and places; with tools to build new services that harness the economic power of the "Information Carbon Cycle." They imagined the flow of information could help our things become "experienced" by tying real sensor data back into our simulations. They imagined a way to shift the focus from design for the birth of things to the design of their operations over a lifetime. Ultimately they envisioned the learnings from that lifetime paying forward to drive the design of the birth of the next thing. Instead of seeming like "groundhog day" each time a designer started to build a product or environment, they wondered what would happen if they could build "experienced things" at birth. This idea is akin to the theory that humans have portions of their brain already "pre-loaded" at birth, including the ability to verbally communicate via language. Autodesk started talking about creating tools easy enough for a child to use but that also provided the power of systems thinking to the next generation of creators.
Just as looking at the first hammer or arrowhead or early attempts at creating the first towns and cities can teach us about the past and how our ancestors saw the world, a dissection of the very first parametric system-thinking design tool is illustrative of the patterns that helped build the modern Galaxy today. Few people today realize that an early tool built for children to learn about systems and build simple ecologies of places, things and people grew into the reality shaping meme-ware commonly found in all our networked matter today known as "the dreaming."
Below is an excerpt from early concept design documents for a project called "Primordial" that contributed to what later became Systems 123D.
1) Design for a Lifetime
The tool would need to help design teams plan for the lifetime of a product or place. Current design tools and processes encourage the design team to consider the experience a user will get from the product or environment when it is first used. The "out of the box" experience and the way the product is used daily are critical. Designers have also been encouraged to consider what to do when the product is no longer valuable. How it can be recycled, or up-cycled? — this question has become a common component of the design process. But in an ecological design we have to consider not only designing for the birth and death of an object, but also for its entire life's journey, and how short- or long-lived it is in relationship to other members of its ecosystem. Is the product a ten-thousand year clock, or is it as ephemeral as a mayfly? Where does it fit in the "pace layer" of the ecosystem? Could we build a tool that helps designers consider the very essence of the product — its spirit or personality as it grows and matures? Could we help creators imagine and plan for the most perfect moments in its life, how it handles diversity, what or who it might talk to or interact with when "out in the wild?"
2) Design for Fit
Ecosystems have lifeforms that "fit" within the environment. When looked at as a whole, the environment forms an information and resource "biome." A Primordial tool, like Systems 123D, would have to help creators design for the fitness of their product in the native "biome" that it will live within. As we transition from disconnected and "dead" products and environments to connected communities of things we'll need to help design teams plan for how their offering natively fits into the whole. Is the product a "royal" lifeform that requires the entire richness of a biome to survive? Is it a "pioneer" lifeform that lays the foundation for others to bubble up out of rich soil? Are there dark zones in the biome that a product could fill? Is there a danger of overpopulation? What unique position does the product hold that would allow it to sense, gather and exploit underused resources that others would value? How much does the product consume of the surrounding "exhaust data" from other lifeforms and how much does it hold on to? How much exhaust data does it put out itself?
3) Design for Dynamics
Designing for ecosystems can, at times, be an exercise in designing, not for complete control, but for the loss of some or all control once the product or environment is set free. For instance, designers will need to consider how much the lifeform is open to learnings from how it's raised or nurtured versus how much its genes or core nature determine its capabilities. What if the Systems 123D tool could help explore the outcomes if a product is static over its lifetime or if it's dynamically mutable based on new developments? How can we help designers understand and design new challenges like how transparent and collaborative the product is versus how secure it is? Does it share only with itself and its authors for internal improvements, does it share with other products in the customer's ecosystem, or is it a part of the grand global pool of experimentation? As we build lifeforms we will need to define the constants and variables that enable them to play out their lives. How can we build tools that help creators set the constants that are core to the brand or product spirit, and define the limits of its variability, as well as its preferred or initial set points?
For instance, what defines a Chevy Corvette's essential spirit, and how much can it stray from the original designer's vision? Could there be a version of the Corvette that takes on some of the design ethos of Charles Eames or Norman Bell Geddes or Karim Rashid or some up-and-coming designer, or even the end user? What if it could evolve in the wild at a faster pace than the traditional model year, reacting to external environmental stimulus? What tools will help design teams configure their lifeforms for composability and fungibility within the broader ecosystem?
4) Simulate for Emergence
It will have to help teams design for the shaping of their things in a dynamic system over time. While the goal shouldn't be to turn everyone into a master system engineer, understanding the common pitfalls and opportunities that ecosystems represent will become increasingly valuable. Helping design teams in understanding and using the elements that make up a complex system's flow, having tools to help build and diagnose system level ideas, and cataloging the menagerie of ecosystem "wildlife" will be critical to reduce surprising developments in the wild.
We will need to develop tools that provide a team with the ability to build interaction physics, assemble information flows, capture stocks of value, and model a system's richness. How can we enable creators to "spin up" their ecosystems, or play test them? How will we help teams learn the implications of their design decisions as the number of lifeforms begin to increase and populate the space How can we help authors signal that they'd like other organisms or proto-lifeforms to join their "petri dish" experiments and invite complimentary products to play?
5) Design for an Information Carbon Cycle
All too often design decisions are made based on the "Internet of Thing" or the "Internet of Five Things" rather than within the true richness of a population of hundreds, thousands or millions of things. As creators build lifeforms and define their initial ecosystems, we'll need to provide tools to help test out their ideas for value exchange at scale. "Designing in" data capture without understanding the potential value it will bring to the product or organization could lead to large amounts of waste data and lame or hobbled systems. It will be important to help creators capture, at birth, how their products will become robust, viral if appropriate, and deliver value back to the creators.
Much of the value of a connected product will come from its ability to be not only future-proofed and agile but also respond to unforeseen events. What new tools can we give organizations to help them try out serendipitous or event-driven campaigns that capitalize on new knowledge? How can we encourage business model experimentation "in situ?" As the rise of distributed ledger methods, like those employed by BitCoin, allow for distributed transactions between entities, will our things and places harvest value locally by trading with other things in the same way that lifeforms on Earth engage in a market called the "Carbon Cycle?" In what ways can we help creators map the social graph of the community of things, take advantage of influential and complementary new members, and turn their own products or places into influencers? Ecosystems are complex by definition and often emerge from the most basic ingredients. How will we build the initial feedstock of data and complementary lifeforms to prime the system? How will we help designers diagnose and trace systemic failure modes and tune the way their lifeforms respond so that they don't all turn into the Internet of Bricked Things when something goes wrong?
6) Become Gardeners of Emergence
As we shift from dead products and environments to living communities of things, people, and places we'll need new tools to manage and shape the growth of not only a given product species but also the community it lives within.
The excerpt above hints at some of the thinking going on at the time within the Autodesk organization. They were quietly biding their time and building the elements that would later become a framework for system thinking. We know that a good number of their customers began using this new framework in earnest within the next few years. Autodesk first showed up in the press when systems built with their tools were some of the only ones that survived a close call known today as "The Day the Earth Almost Bricked." Science fiction authors have often noted in their dystopian stories that, had the company not had the prescience to embark on their "Future of Making Systems" framework, civilization as we know it would have collapsed . In some forms of the story, we'd be living in caves hiding from our robot overlords, in others we apparently make good pets. One wonders if we ever would have taken the threat of complexity seriously if we hadn't gone through such a close call. We still celebrate "Brick Day" as a means of reminding our children and ourselves of how near we came to a technological apocalypse. We were lucky that more creative, and systems-focused, thinkers prevailed.
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