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Los Angeles Palo Alto
Richard Albright, ―What can Past Technology Forecasts Tell Us About the Future?‖, Technological Forecasting and Social Change, Jan 2002 © 2004 Accelerating.org
Los Angeles Palo Alto
© 2004 AcceLeabharlann Baiduerating.org
Relative Growth Rates are Also Amazingly Predictable
Los Angeles Palo Alto
Brad DeLong (2003) noted that memory density predictably outgrows microprocessor density, which predictably outgrows wired bandwidth, which predictably outgrows wireless. Expect: 1st: New Storage Apps, 2nd: New Processing Apps, 3rd: New Communications Apps, 4th: New Wireless Apps © 2004 Accelerating.org
Los Angeles Palo Alto © 2004 Accelerating.org
Systems Theory
Systems Theorists Make Things Simple (sometimes too simple!)
"Everything should be made as simple as possible, but not simpler." — Albert Einstein
© 2004 Accelerating.org
Los Angeles Palo Alto
Intro to Future Studies
Four Types of Future Studies
–
–
– –
Exploratory (Speculative Literature, Art) Agenda-Driven (Institutional, Strategic Plans) Consensus-Driven (Political, Trade Organizations) Research-Predictive (Stable Developmental Trends)
© 2004 Accelerating.org
Los Angeles Palo Alto
Observation 2: The Prediction Crystal Ball
What does hindsight tell us about prediction? The Year 2000 was the most intensive long range prediction effort of its time, done at the height of the forecasting/ operations research/ cybernetics/ think tank (RAND) driven/ ―instrumental rationality‖ era of future studies
Los Angeles Palo Alto
(Kahn & Wiener, 1967).
© 2004 Accelerating.org
Lesson 1: Forecasting in certain domains of the modern environment is highly predictable
We practice ―developmental future studies,‖ that is, we seek to discover a set of persistent factors, stable trends, convergent capacities, and highly probable scenarios for our common future, and to use this information now to improve our daily evolutionary choices.
Many Technology-Related Transformations are Amazingly Predictable
Miniaturization (per linear dimension) Price Performance in Computing (Moore‘s Law) Input-Output, Storage, Bandwidth Network Node Density (Poor‘s Law) Protein Structure Solution (Dickerson‘s Law) Algorithmic Efficiency (Statistical NLP, etc.) Software Performance (6 year doubling) Economic Growth (2-4% year, over long spatial scales)
Example: Information and Communication Technologies
Evaluating the predictions of The Year 2000, technology roadmapper Richard Albright notes:
―Forecasts in computers and communication stood out as about 80% correct, while forecasts in all other fields (social, political, etc.) were judged to be less than 50% correct.‖ Why? Here TY2000 used trend extrapolation (simple). The major ICT change they missed was morphological (nonsimple) the massive ―network transition,‖ to decentralized vs. centralized computing.
The last is the critical one for acceleration studies and singularity studies
It is also the only one generating falsifiable hypotheses
Accelerating and increasingly efficient, autonomous, miniaturized, and localized computation is apparently a fundamental meta-stable universal developmental trend. Or not. That is a key hypothesis we seek to address.
Thought Question: Is annual economic growth a function of exponential technological surprise interfacing with human expectation? (Remember: Efficient market hypothesis in Economics would predict zero annual growth)
Specifically, these include accelerating intelligence, immunity, and interdependence in our global sociotechnological systems, increasing technological autonomy, and the increasing intimacy of the human-machine, physical-digital interface.
Adapting to the Future: The Impact of Accelerating Change
淘 宝 网 htttp://www.tejiashuo.net
Challenges for World Security Policy
John Smart
USAWC, August 2004, Carlisle, PA
Los Angeles Palo Alto
© 2004 Accelerating.org
Institute for the Study of Accelerating Change
ISAC (Accelerating.org) is a nonprofit community of scientists, technologists, entrepreneurs, administrators, educators, analysts, humanists, and systems theorists discussing and dissecting accelerating change.
Los Angeles Palo Alto
© 2004 Accelerating.org
Observation 1: The “Prediction Wall”
The faster change goes, the shorter-term our average business plans. Ten-year plans (1950's) have been replaced with ten-week (quarterly) plans (2000's). Future appears very contingent, on average. There is a growing inability of human minds to imagine some aspects of our future, a time that must apparently include greater-than-human technological sophistication and intelligence. Judith Berman, in "Science Fiction Without the Future," 2001, notes that even most science fiction writers have abandoned attempts to portray the accelerated technological world of fifty years hence.
Some Tech Capacity Growth Rates Are Independent of Socioeconomic Cycles
There are many natural cycles: Political-Economic Pendulum, Boom-Bust, War-Peace… Ray Kurzweil first noted that a generalized, century-long Moore‘s Law was unaffected by the U.S. Great Depression of the 1930‘s. Conclusion: Human-discovered, Not human-created complexity here. Not that many intellectual or physical resources are required to keep us on the accelerating developmental trajectory. (“MEST compression is a rigged game.”)
Richard Albright, ―What can Past Technology Forecasts Tell Us About the Future?‖, Technological Forecasting and Social Change, Jan 2002 © 2004 Accelerating.org
Los Angeles Palo Alto
© 2004 AcceLeabharlann Baiduerating.org
Relative Growth Rates are Also Amazingly Predictable
Los Angeles Palo Alto
Brad DeLong (2003) noted that memory density predictably outgrows microprocessor density, which predictably outgrows wired bandwidth, which predictably outgrows wireless. Expect: 1st: New Storage Apps, 2nd: New Processing Apps, 3rd: New Communications Apps, 4th: New Wireless Apps © 2004 Accelerating.org
Los Angeles Palo Alto © 2004 Accelerating.org
Systems Theory
Systems Theorists Make Things Simple (sometimes too simple!)
"Everything should be made as simple as possible, but not simpler." — Albert Einstein
© 2004 Accelerating.org
Los Angeles Palo Alto
Intro to Future Studies
Four Types of Future Studies
–
–
– –
Exploratory (Speculative Literature, Art) Agenda-Driven (Institutional, Strategic Plans) Consensus-Driven (Political, Trade Organizations) Research-Predictive (Stable Developmental Trends)
© 2004 Accelerating.org
Los Angeles Palo Alto
Observation 2: The Prediction Crystal Ball
What does hindsight tell us about prediction? The Year 2000 was the most intensive long range prediction effort of its time, done at the height of the forecasting/ operations research/ cybernetics/ think tank (RAND) driven/ ―instrumental rationality‖ era of future studies
Los Angeles Palo Alto
(Kahn & Wiener, 1967).
© 2004 Accelerating.org
Lesson 1: Forecasting in certain domains of the modern environment is highly predictable
We practice ―developmental future studies,‖ that is, we seek to discover a set of persistent factors, stable trends, convergent capacities, and highly probable scenarios for our common future, and to use this information now to improve our daily evolutionary choices.
Many Technology-Related Transformations are Amazingly Predictable
Miniaturization (per linear dimension) Price Performance in Computing (Moore‘s Law) Input-Output, Storage, Bandwidth Network Node Density (Poor‘s Law) Protein Structure Solution (Dickerson‘s Law) Algorithmic Efficiency (Statistical NLP, etc.) Software Performance (6 year doubling) Economic Growth (2-4% year, over long spatial scales)
Example: Information and Communication Technologies
Evaluating the predictions of The Year 2000, technology roadmapper Richard Albright notes:
―Forecasts in computers and communication stood out as about 80% correct, while forecasts in all other fields (social, political, etc.) were judged to be less than 50% correct.‖ Why? Here TY2000 used trend extrapolation (simple). The major ICT change they missed was morphological (nonsimple) the massive ―network transition,‖ to decentralized vs. centralized computing.
The last is the critical one for acceleration studies and singularity studies
It is also the only one generating falsifiable hypotheses
Accelerating and increasingly efficient, autonomous, miniaturized, and localized computation is apparently a fundamental meta-stable universal developmental trend. Or not. That is a key hypothesis we seek to address.
Thought Question: Is annual economic growth a function of exponential technological surprise interfacing with human expectation? (Remember: Efficient market hypothesis in Economics would predict zero annual growth)
Specifically, these include accelerating intelligence, immunity, and interdependence in our global sociotechnological systems, increasing technological autonomy, and the increasing intimacy of the human-machine, physical-digital interface.
Adapting to the Future: The Impact of Accelerating Change
淘 宝 网 htttp://www.tejiashuo.net
Challenges for World Security Policy
John Smart
USAWC, August 2004, Carlisle, PA
Los Angeles Palo Alto
© 2004 Accelerating.org
Institute for the Study of Accelerating Change
ISAC (Accelerating.org) is a nonprofit community of scientists, technologists, entrepreneurs, administrators, educators, analysts, humanists, and systems theorists discussing and dissecting accelerating change.
Los Angeles Palo Alto
© 2004 Accelerating.org
Observation 1: The “Prediction Wall”
The faster change goes, the shorter-term our average business plans. Ten-year plans (1950's) have been replaced with ten-week (quarterly) plans (2000's). Future appears very contingent, on average. There is a growing inability of human minds to imagine some aspects of our future, a time that must apparently include greater-than-human technological sophistication and intelligence. Judith Berman, in "Science Fiction Without the Future," 2001, notes that even most science fiction writers have abandoned attempts to portray the accelerated technological world of fifty years hence.
Some Tech Capacity Growth Rates Are Independent of Socioeconomic Cycles
There are many natural cycles: Political-Economic Pendulum, Boom-Bust, War-Peace… Ray Kurzweil first noted that a generalized, century-long Moore‘s Law was unaffected by the U.S. Great Depression of the 1930‘s. Conclusion: Human-discovered, Not human-created complexity here. Not that many intellectual or physical resources are required to keep us on the accelerating developmental trajectory. (“MEST compression is a rigged game.”)