Category: systems

KTLS: Emerging Cityscapes

Over at KedgeForward I’ve contributed a piece exploring my sense of what cities might look like in the coming years based on current trends and emerging constraints. The question posed by Kedge founder, Frank Spencer, is:

“In what ways will the concept and landscape of the city change over the next decade, and will this change bring about positive or negative impact in terms of global resilience, transformational development, and human evolution?”

My answer begins:

“All human systems and technologies are ultimately embedded within the larger natural ecosystem of the planet. As we’re now beginning to witness across all such domains, nature is applying more and more pressure on civilization to force it into better alignment with the principles of conservation and homeostasis critical to balanced living systems. As massive aggregations of society, technology, commerce, industry, resource consumption, and waste production, cities will feel tremendous impact from the corrections imposed by the natural world. Megacities in the developing world like Lagos, Jakarta, Delhi, and Mexico City already exhibit enormous stress due to rapid urbanization, rising populations, and the energetic consumption and waste production that attends their growth. With aging populations and over-burdened consumer economies, first world cities like London, Los Angeles, and Tokyo will find it more & more difficult to support their resource demands. Indeed, given projections for energy prices, food stocks, and clean water & sanitation, cities across the world are trending towards a lower common standard of living.

Continued at KedgeForward…

Notes From the IFTF 2010 Ten Year Forecast

Last month I attended & participated in the Ten Year Forecast conference presented by the Institute For The Future. This event at Cavallo Point was the culmination of several months of research looking at the signals, trends, and possible futures of five global domains: the carbon economy, the water ecology, adaptive power, cities in transition, and molecular identity. I contributed research for the carbon economy & adaptive power, looking at carbon markets and the distribution of energy resources for the former and investigating insurgency, narcoterror, and the emerging shadow economy for the latter.

Over two days we presented very challenging content, both in scope & complexity, as well as tone. These are major foundational systems that intersect with every aspect of civilization. Most of the forecasts & scenarios were undercut with a tone of constraint and great challenge given the turbulent nature of these modern transitional times. In attendance were many high-level representatives from some of the largest corporate entities on the planet, as well as from NGO’s, government, and private research. The scenarios presented them with a near-future significantly constrained by resource shortages, rising costs of production, and the growing urgency of climate change. All of these constraints were very clearly articulated to highlight the need to reduce consumption, engineer positive behavioral change, and identify new measures of prosperity & wellness unhinged from growth & GDP.

I spoke directly with several VP’s, some responsible for guiding multi-billion dollar corporations, and all expressed a surprising awareness & understanding of the deeply challenging realities we face. I was met again & again with the sentiment that energy constraints will corral growth and compel companies to both modify their operations to reduce energy use and evolve their products and services to be more sustainable. Indeed, everyone acknowledged the impact of sustainability on their business, admitting that nature has now entered the boardroom. To be clear, some of these companies are the largest transporters on the planet – major keystone energy consumers. So when they start admitting that business-as-usual has to change, it’s hard not to feel the gravity of our times.

The first day was especially powerful. There was a distinct thickness to the large ballroom by the time Jane McGonigal was giving her after-dinner keynote on the Epic Win. We had thrown so much really overwhelming information at the attendees, all of which heralded significant changes that will likely impact all human systems in the next ten years. We painted pictures of a civilization that will either adapt quickly & effectively or spiral into a malaise of constraint, decline, & chaos. Yet the tone of the room and the comments & conversations that emerged were radically optimistic, embracing the dire news and ready to press on into the cold night for a better tomorrow.

Undeniably, we live in interesting times. Things seem increasingly out of control. Or at least, we now see so much of the world in such minute detail that our historic models of what order should look like are failing against the vast interconnected global systems laid bare before us. What we know for sure is that inevitable growth is a cancer and cannot be sustained. We know resources are finite and expensive and their industrial use is poisoning the planet. And we know that the planet itself is the ultimate Invisible Hand that will easily wipe us clean if we don’t acknowledge it’s centrality and honor the necessity of it’s health. Perhaps in more pragmatic terms these realizations are now reaching into the boardrooms and staff rooms of our global institutions. Economics, humanism, and ecology – the triple-bottom line – is making it’s way into the machines of commerce. And more and more people are looking for a meaningful future in their own triple-bottom-line of happiness, resilience, and legacy.

Outliers & Complexity

Or, The Risk of Extrapolating Linear Trends Against Non-Linear Systems.

A common habit in forecasting, particularly in energy futures & economic growth, is to take roughly linear trends and extend them over the next few decades. The notion is that there is inertia in what has already happened that will make the future look markedly similar, or at least there will likely be a more-or-less linear movement along an existing path. For example, many forecasts suggest that energy consumption will increase by 50% towards the year 2035. This is based on data over the past 30 years that is then extrapolated forward along expectations, so you get graphs that look like this one from the EIA’s 2009 Annual Energy Outlook Early Release Overview:

The graph shows mostly linear growth in energy consumption. The assumptions here are that, given previous growth rates, and given a rough set of expectations about future growth, energy consumption will steadily grow across all sectors. Yet you’ll notice a few bumps & dips for transportation & industrial in the later months of 2008 and early 2009. These suggest outlier events. Outliers are the unexpected events, the Black Swans that come out of nowhere and blow expectations out of the water. In this case, economic activity got a big boost by the inflated gains of the securities market, then took a dive after all the hidden risks came to the surface. The following graph from the same EIA report highlights the 2008 economic black swan:

Here we see the market prices for the primary energy sources. This graph really shows the instability churned up by the securities outlier. As the ultimate determinant of just about all economic activity (nothing happens without energy) we can see energy prices climbing at the same time demand was ramping up (compare to the last graph of consumption). Then heading into the crash energy prices plummet as fears mount, workforces are downsized, factories go dark, and productivity retracts in the face of economic doom. In spite of expectations the market collapse came as a surprise. Yet, forecasts still commit global energy consumption to a future of roughly 50% growth in demand (see those post-2010 consumption lines in the first graph?). In spite of obvious turbulence in past performance the forecasts assume typical, linear economic growth out to 2035.

While such linear approximations offer hope of anticipating and, hence, preparing for the future, to some degree they represent a logical fallacy of projecting linear trends onto complex, non-linear systems. Living systems like weather patterns, anthills, and global economics are approximately non-deterministic. That is, they’re so complex and have so many feedback mechanisms that they’re mostly unpredictable (weather predictions are still only more-or-less valid for about 5 days out). Much of this complexity arises from the turbulence generated by feedback loops and interconnections across every scale of the system. The power laws underlying dynamic systems take small values and iterate them over time into very large values. This is the mechanism underlying the oft-mentioned Butterfly Effect and one of the drivers for outlier events. Imagine a dust devil spinning up on an otherwise calm desert floor.

Nature seeks homeostasis – a dynamic equilibrium around a point of stability. The counterpoint to runaway feedback loops and suddenly emergent outliers are the damping effects of control elements. In climate, the tendency for hot & cold to equalize will usually mitigate a storm and return clear skies. The dust devil gives up it’s angular momentum to shifting pressure & temperature gradients. Looking at our current affairs we see that total economic collapse has (so far) been averted through aggressive attempts to dampen the turbulence by injecting massive amounts of state capital into the financial system. These interventions & market regulations are control structures put in place to govern for relative economic homeostasis. When they work and things are relatively quiet, they keep those trend projections nice & linear.

Linear projections help us continue to get things done based on fairly reliable expectations. But avoiding the next economic catastrophe requires a deep study of the many threads & amplifiers that drive black swan events. Outliers occupy the thin edge of statistical possibility yet almost always have tremendous consequences. They are, by nature, entropic & disruptive, shifting the territory and demanding new adaptations. To return to the global energy domain, what outliers might be slowly iterating to challenge the forecasts of 50% growth in demand? What catastrophic black swans might be lurking off the radar? What scientific breakthroughs and game-changing innovations might be weaving together towards a complete re-orientation of power requirements, transport, or industrial fuel?

The mobile phone is a great example of a high-impact outlier with a small physical footprint that achieved global ubiquity within 10 years, shredding the linear projections of numerous industries. The pace & breadth of it’s adoption suggests that interventionary technologies can rather quickly have major impacts, challenging heavily invested and entrenched businesses. Imagine an energy outlier with a similar device profile that enabled people to generate & store enough power to run a small home or drive an electric car 100 miles.

Studying a system for outliers and looking for the signals & trends that might lead to the next Black Swan, as well as examining the conditions that have led to previous outlier events, can inform forecasts that are much more attuned to resiliency and adaptation.

Modeling & Superstructing

A core human competency is the capacity to model outcomes. This predictive ability has contributed to our successful growth as a species and provided the stage from which we extrude our technologies. We observe our world, log our experiences, and use this information to envision & plan our future possibilities. In the rush into tomorrow we’ve deputized machines to assist in our scenario modeling as our plans grow ever greater in scope.

Today we have tremendous amounts of data available about any system we wish to model. Drive platters are bulging into the terabytes just to store all of the information gathered by sensors, services, and empowered humans. Whether we study business networks, financial models, or natural systems, our awareness of their complexity has grown exponentially. Things are far wider and more interconnected than we could have imagined even 20 years ago.

All systems are sets of nodes with properties & variables that govern their behavior, coupled together by relational rules governing their interaction. The more complex a system, the more unique nodes and the more interconnections between nodes. Given the human constraint of being able to hold only 6 or 7 unique objects in mind at any given time it’s clear that we’re overwhelmed by even the relatively simple tasks of understanding, for example, a mid-size business structure enough to predict its future, especially when you consider the business system itself as a single node embedded in a much larger global socio-economic system. Imagine the difficulties climate modelers face trying to document global circulatory systems…

One emerging strategy for modeling complex systems looks to software and the floating-point wonders enabled by Moore’s Law. Computers are phenomenally capable of managing the inconceivable amounts of operations necessary to begin modeling dynamic systems. Yet, until very recently one needed to book time on a supercomputer cluster to run weather models or robust behavioral analysis. Even today’s bleeding hardware strains under the weight of such complexity. Research institutions have pursued natural systems modeling for some time and the business world has been paying attention. SAP now offers modeling capabilities with its business intelligence ERP solutions, enabling executives to run scenarios and envision possible outcomes of strategic decisions. Oracle recently acquired Hyperion, adding “performance management” to their suite of BI tools. You can bet these technologies will work their way into government & geopolitical protocols, as well as social & personal behavioral engineering as we increasingly track & model our lives.

Effectively, this pattern emulates the deeper shift from individual enterprise to collective collaborations. You can only model a complex system with another sufficiently complex system. However, even the most interesting algorithms are encumbered by the impositions of their logic: they can only be as creative as they were written. A second emerging strategy for modeling complex systems looks to deputize humans as processing nodes, crowdsourcing future possibilities across infinitely creative sets of minds. The Institute for the Future has taken this approach with its Signtific Lab and the Superstruct platform, leveraging the principles of gameplay to engage massive participation in envisioning scenarios.

The Superstruct games have drawn in thousands of players offering their thoughts & dreams of the future. Players become processing nodes for the chosen subject (eg. “when augmented reality is everywhere”, or “when personal satellites are as easy to deploy as websites”) iterating across large sets of potential outcomes. From these inputs, patterns emerge showing trends with greater frequency & momentum among the collective. Perhaps even more interesting – and where the Superstruct method is more flexible than computational modeling – are the outliers that emerge from players. Many of the most compelling signals of the future are those that completely break from current patterns. Indeed, one of the most fundamental prevailing shifts in the global paradigm is that change is accelerating in ways we cannot even imagine.

These two approaches both consider complex systems & scenario modeling from architectures that themselves are complex, object-oriented systems. The programmatic approach brings heavy-weight numeric bit-crunching to dynamic data streams, while the Superstructing approach offers wide-reaching creativity and human sensing. Augmenting one approach with the other will mark the next phase of predictive analysis necessary to safely navigate civilization through the future. Envisioning these scenarios and building compelling narratives around them will inevitably draw them into becoming.

Our lives are more & more complex and our enterprises & collaborations are commonly reaching global scales. The need to effectively model & predict is a fundamental human trait, reinforced in the face of escalating complexity in a hyper-connected, Read-Write world.

Patterns: Global Systems & Human Adaptation

Overview: The top-level context for the next 10-20 years will be characterized by growing environmental challenges across the planet, notably more irregular weather patterns with increasingly severe storms, a rise in temperatures and a reduction of rainfall leading to shifting distributions of agriculture and farming. Regions that are heated but retain humidity will face rising bacterial & viral outbreaks, especially if these regions see further economic declines due to declining food production. These changes will challenge many populations, adding pressure to invest in more climate-controlled (and energy-intensive) infrastructure and/or migrate towards more wet & fertile lands. The great dependence on rainfall and water delivery infrastructure coupled to its widely distributed nature will impact drought-stricken regions considerably, as well as neighboring water-rich regions (eg. Los Angeles and Northern California) that may see growing tensions across resource inequities.

Within this global system the primary drivers remain materials technologies, energy capture & generation, health care (freemium & premium), cleaning & streamlining industrial processes, managing supply chains (particularly with respect to resource/energy overhead, social & environmental impacts), remediating toxic environments, and coping with persistent disruptions to all of these. In communities, trends are moving towards group empowerment through emerging technologies for computation, communication, collaboration, design, and fabrication. This empowerment enables both resilience & resistance, aiding some to design better civic structures & local production capacity, for example, while others design and execute disruptive events and attacks on high-value targets.

Across the species, though in no way homogeneous, lifespans are extending, health care is more reliable, mobile computing is more powerful & ubiquitous, screens and media are proliferating, and more people, objects, plants, and animals are creating digital identities and communicating across the cloud. There is a rapid movement to digitize human information and expose it to massive computational structures, iterating exponentially across literally billions of logical nodes. This movement into the cloud has a huge energetic overhead only recently being considered – not to mention the social and economic impacts rapidly rewriting much of the first world.

Computational systems are evolving to model and predict larger living systems. We now model natural systems, business enterprise, financial variables, and human behavior deriving greater ability to predict future probabilities. All in order for the species to continue its adaptive success while willfully managing our resource requirements & impacts while effectively supporting a global virtualization of human endeavor, expression, and creativity.

In a nutshell, the patterns and processes we’ve relied upon are moving into a time of great flux with all systems facing regular perturbations. Change is the only constant. Survival, as it always ultimately has, depends on flexibility, resilience, collaboration, and adaptation.

Disruptive Civil Technologies
Six Technologies with Potential Impacts on US Interests out to 2025
(National Intelligence Council):

Key trends, “most likely to enhance or degrade US national power out to 2025″
– Biogerontechnology
– Energy Storage Materials
– Biofuels and Bio-Based Chemicals
– Clean Coal Technologies
– Service Robotics
– The Internet of Things.

[The NIC report offers some interesting signals but I personally disagree with their sense of trending towards biofuels. Turning human energy sources (food) into industrial energy sources (biofuel) is exceptionally short-sighted and dangerous and has already incurred a large backlash in common sense. I don’t know enough about so-called “clean coal” to comment… but I’m highly dubious.]

From the IFTF Winter 2009 Overview and Jane McGonigal’s initial Superstructing results.

Top Signals 2009
– Geolocation
– Biometrics & accelerometers
– Handheld augmented reality
– Simulation engines
– Lifecasting platforms
– Social networks for every living thing
– Avatars everywhere
– Virtual worlds based on real worlds

Critical Factors
– Evolvability
– Extreme scale
– Ambient collaboration
– Reverse scarcity
– Adaptive emotions
– Amplified optimism
– Playtests

DRAFT 2009 Climate Action Team Biennial Report to the Governor and Legislature (California Climate Change portal):

All simulations indicate that extremely hot daytime and nighttime temperatures (heat waves) increase in frequency, magnitude, and duration from the historical period. Within a given heat wave, there is an increasing tendency for multiple hot days in succession—i.e., heat waves last longer. Furthermore, the number of days with simultaneously hot daytime temperatures in multiple regions in the state increases markedly; this has important implications for emergency response and satisfying electricity demand in the state.

…In the northern part of California, the tendency for drying fades and even reverses but in Southern California the amount of drying becomes greater, with decreases in some simulations exceeding 15% drier. became significantly wetter by the end of the century.

…The results suggest that climate change will decrease annual crop yields in the long- term, particularly for cotton, unless future climate change is minimized and/or adaptation of management practices and improved cultivars becomes widespread.

…In summary, without changes in operating rules for the water system in California the reliability of water supply will be severely affected. On the other hand, it seems that California could afford the implementation of adaptation measures that could significantly reduce the system’s vulnerability.