Accelerating Change 2005. September 16-18, Stanford University. Artificial Intelligence and Intelligence Amplification. Transforming Technology, Empowering Humanity

What is the Universal Story of Accelerating Change?

In our best current understanding, the history of universal evolutionary development has always seen an increasingly faster development of computational complexity (modeling intelligence) within special subsets of locally emergent forms. Carl Sagan first popularized this in his famous metaphor of the "Cosmic Calendar." Place all universal history on a calendar year, and the closer you get to the end of the calendar, the faster change goes, with the pace of change continually accelerating, without exception (when viewing the system as a whole, not particular evolutionary experiments).

Eric Chaisson (Cosmic Evolution, 2002) has recently given this acceleration a helpful thermodynamic explanation. He notes that as universal development moved from galaxies to solar systems to life-friendly planets to microbes to plants to animals to human brains to computing technology, each new computational system in this hierarchy has operated with significantly greater free energy rate density (energy available for computation per volume per unit time). This increased energy density has allowed each of these complex systems (whether living or nonliving) to model and react to its environment far more rapidly and extensively than its predecessors. There is also independent data that later-developed systems in this hierarchy are significantly more resource efficient (per physical or computational output), denser, and more miniaturized. This impressive energy efficiency and density of the most newly emergent systems apparently allows the leading edge of universal intelligence to continually avoid resource limits to its accelerating growth.

In human history, archeologists and anthropologists have long noted that significant cultural advances (neolithic tool kits, architectures, language, civil society, law, science) have emerged at an accelerating rate in human history. Many scholars (Jared Diamond, James Burke, Robert Wright) consider such factors as increasing population density, technological diffusion, and communication rates to be key drivers of these sociotechnological accelerations.

Over the last millennium, rates of planetary technological innovation and diffusion have broadly accelerated as a whole, with ever-briefer pauses between each new phase of acceleration. The increasingly rapid development of what may be called the "average distributed complexity" of our sociotechnological systems has been apparent even as catastrophes, declines, wars and revolutions have caused local discontinuities within specific civilizations.

In other words, while catastrophes continually occur in specific cases, a distributed and redundant network immunity, resiliency, or social learning has always occured at the leading edge of our most successful physical systems, whether we are studying civilizations, cultures, economies, or technologies. Like the human immune system, we are discovering that all complex networks encode their own forms of immunity, interdependence, and resiliency, keeping them on an accelerating growth curve, even as individual systems have their own limited lifespans.

As perhaps the most dramatic example of global acceleration, recent data show that our modern computer technology, when considered as one broadly distributed planetary system or "substrate," has been smoothly and continuously doubling in average complexity for the entire twentieth century. Ray Kurzweil's data propose that performance/price ratios in purchasable computing systems were originally doubling every three years in our 1890 mechanical computing systems, and are now doubling every 12-18 months.

As a planetary phenomenon this acceleration has been highly immune to the fortunes and catastrophies of individual technology companies – even of major national, political and economic crises, such as World Wars, the Great Depression, and our recent recession. It has been maintained through at least five dramatically different computer engineering and manufacturing paradigms: mechanical, relay, vacuum tube, transistor, and integrated circuit information processing machines.

Today we are creating a panoply of successively more miniaturized and resource-efficient computing architectures, several of which are growing measurably more autonomous (evolutionary, biologically-inspired, self-directing, self-monitoring, self-provisioning, self-repairing, and partially self-replicating) with each new computer generation. An impressive array of new commercial applications for these semi-autonomous systems (e.g., Google's cluster architecture, electronic design automation software, reverse compilers, self-diagnosing and semi-autonomic systems, pattern recognizing neural networks and genetic algorithms, innovative machine learning paradigms such as support vector machines) have further increased our breathtaking pace of technological change.

Where does this continual acceleration phenomenon come from, where is it going, and what does it mean for the near future of humanity? Accelerating Change is the place where today's leading thinkers explore science, technology, business, and humanist dialogs in accelerating change. We hope you can join us for an extraordinary weekend at Stanford this year.

Key Questions
How does computation affect our environment?
What is accelerating technological change?
Why is accelerating change important?
What is the universal story of accelerating change?
What is the "technological singularity" hypothesis?
Where might accelerating change take us in the 21st century?
What are our main benefits and risks with regard to accelerating change?
How do we improve the study of accelerating change?


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