The history of life's development on Earth has apparently been an increasingly faster emergence of computational complexity (or modeling intelligence') within a special subset of locally emergent forms. Curiously, these new forms are often much more resource efficient (per physical or computational output), denser, or miniaturized, so that they continually avoid resource limits to their accelerating growth. Historians have long noted that significant cultural advances (language, civil society, law, science) emerge 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 social transformations.

Over the last millennium, rates of planetary technological innovation and diffusion have broadly accelerated as a whole, with ever-briefer pauses between new phases of acceleration. This accelerating trend in what may be called the "average distributed complexity" of our socio-technical systems has been apparent even as wars, local catastrophes, and revolutions have caused discontinuities within specific civilizations. In other words, while catastrophes continually occur in specific cases, some type of general immunity, resiliency, or social learning is apparently built in our most successful physical (civilizations, economies, cultures, technologies) on a distributed and redundant basis, like the human immune system, keeping them on an accelerating growth curve for long spans of time.

Perhaps most dramatically in recent decades, our modern computer technology, when considered as one broadly distributed system or "substrate," has been smoothly and continuously doubling in average complexity for the entire twentieth century. Ray Kurzweil's data propose that price performance was originally doubling every three years in our 1890 mechanical computing systems, and is now doubling every 12-14 months, by some estimates, in our latest computing systems. This computational acceleration has been independent of type of computer design, through five separate manufacturing paradigms (mechanical, relay, vacuum tube, transistor, and integrated circuit), and it is largely independent of the fortunes of individual technology companies – even of major social, political, or economic crisis, such as World Wars, the Great Depression or our current recession.

Today we are creating a panoply of successively more miniaturized, resource-efficient architectures, which grow measurably more autonomous (evolutionary, biologically inspired, self-directing, self-monitoring, self-provisioning, self-repairing, self-improving, partially self-replicating) with each new computer generation. Recently, a breathtaking array of new commercial applications (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? ACC2003 is the place where today's leading thinkers explore science, technology, business, and humanist dialogs in accelerating change.

At the present time, what might be called "singularity studies" (analysis of accelerating change, increasingly autonomous technology, metrics and models of exponential and asymptotic computational development) is an underdeveloped yet critically important area of study. With our collective effort, consideration of accelerating change will soon gain greater critical attention from the scientific, engineering, business strategy and forecasting, technology entrepreneur, political and social science, science and technology studies (STS), future studies (FS), journalism, technology and public policy (TPP), and other important communities that are currently engaged in science and technology assessment, diffusion, policymaking, development, and extrapolation.

Come join us in Palo Alto this September as we investigate some of the most fascinating and important issues of the modern era.