By Kalevi Rantanen
From the Editors: The practice of creating predictions about the future has been conducted for centuries. Predicting the future is part of Strategic TRIZ – a part of the DMAPI roadmap – and can be utilized to assist in the creation of multi-generation product plans (MGPPs) and/or technology forecasts. Used in this fashion, the application is based upon a set of customer and/or societal needs. Open-ended predictions, like those in this article, have been used to help understand the creative persona.
Abstract
Many technology forecasts from Jules Verne's novels in the 19th century to Herman Kahn's and Anthony Wiener's scenarios in the 1960s come to pass. Hypothetically, if the patterns of evolution are added to futurology, predictions can be still improved. To test the hypothesis, this paper presents a list of 100 predictions for the years 2007-2040 (comparable to Kahn's and Wiener's list for years 1967-2000), based on journalistic research from 2002-2006.
Keywords
TRIZ, foresight, prediction, journalism
Significant Statistical Evidence
In The Year 2000, Herman Kahn and Anthony Wiener presented "One Hundred Technical Innovations Very Likely in the Last Third of the Twentieth Century." [7, p. 52] Some forecasts were incredibly accurate.
About 20 innovations had happened by 2000, including:
- "70. Simple inexpensive home video recording and playing"
- "74. Pervasive business use of computers"
- "88. Inexpensive…rapid high-quality black and white reproduction"
The remaining 80 predicted innovations either did not happen or the outcome remains unclear. For example:
- "1. Multiple application of lasers and masers" (They are used, but less than predicted.)
- "27. Use of nuclear explosives for excavation and mining"
- "99. Artificial moons and other methods for lighting large areas at night"
Some innovations, most notably personal computers, were not predicted. If we subtract lacking innovations from the list, we can crudely conclude, that about 10 percent of the future is predictable.
More than one thorough evaluation studies has been produced – notably in Japan. In 1996, the Japanese Science and Technology Agency evaluated a forecast made in 1970-1971 – 26 percent of 588 topics were realized. A second forecast was made in 1976; of 549 topics 21 percent were realized. [15, p.12] But what do these figures mean? Is ten or twenty percent a good or bad result?
There is much talk of failures. People who deny the possibility of any reasonable predictions often cite Thomas Watson, the founder of IBM, who said, "I think there's a world market for about five computers." The founder of Microsoft, Bill Gates, stated in 1981 that 640K memory "ought to be enough for anybody." Both companies have been successful in business for decades, but every successful person and company has made wrong predictions.
Insurance companies do well, although they cannot predict a single event. There is significant statistical predictability in the world. Ten percent is better than guessing. In the lottery, chances of winning are usually one of millions – as you select from some tens of numbers. In technology there are many more combinations of elements that can form myriads of mixtures, alloys and compounds. Expert knowledge allows for the selection of a limited set of possible futures. One good idea has a better chance than ten bad ones. The rule of thumb is that one successful project compensates ten failures and still provides profit. But, do we want to know the whole future? If 100 percent of the future is predictable, then nothing could be changed – there would be no freedom of choice. The ideal accuracy, therefore, would be somewhere between 0 and 100 percent
There are, then, two conclusions:
- Scientific and technical knowledge enables predictions that are reliable enough to improve business and political decision making.
- It is not at all necessary to know all the future: we do not want to know the future precisely. Totally predestined future can equate to lack of choice and space for creativity.
While saying that predictions based on expert knowledge are useful, there is still room for improvement:
- How much more accurate do the predictions need to be? At the moment the question is academic. We need to focus on improving forecasts. Improving business is an obvious reason to make predictions. If you know 30 percent of the future, while your competitors know 10 or 20 percent, you will win.
- Make predictions more specific.
Science and Technology Journalism
A look at journalism demonstrates the previous conclusions. I have written about 140 articles about science and technology in the last four years; nearly all of them contain predictions. A reader of technology news wants to know not only what happened, but also what will happen in the future.
The following are some examples of recent predictions in scientific and technological journalism:
- Light emitting diodes (LED) will replace bulbs in the 2020s.
- Tissue engineering will allow for the manufacturing of new organs in the 2010s.
- Robots will play soccer in 2050 better than humans.
- Nanorobotic toothpaste will prevent tooth decay in the 2020s.
- "Smart dust," Real World Web of smart sensor networks or mesh wireless networks will be used in 2015.
A Hypothesis: Patterns of Evolution Improve Predictions
The accuracy of predictions is an everyday concern. Readers require reliable, balanced and non-biased stories. Traditional predictions are based on knowledge of different sciences and technologies. They are made by one person or by groups of subject matter experts. The most important method for prediction is the Delphi Method, developed by RAND Corporation in the 1960s by one such group. The work can consist of several rounds as experts comment upon and correct eachother's work.
Independent of "mainstream futurology," Genrich Altshuller and his colleagues developed the Theory of Inventive Problem Solving, TRIZ. TRIZ experts claim that there are laws, trends, patterns and evolution lines in technology and that there are tools that be used for technical forecasting.
But can you prove whether tools like the Delphi Method and TRIZ add value to forecasting?
Genrich Altshuller and Rafael Shapiro wrote of "basic trends of technology evolution" in the first paper about TRIZ. [1] In 1979, Altshuller defined and described eight laws and their use with forecasting innovations. For example, a heat-resistant diving suit for mining rescue teams predicted in 1949 was realized 20 years later. [2, pp. 215-216]. Also, Altshuller suggested developing engineering systems "without waiting until the problem arises." [2, p. 45]. Today, we frequently try to act proactively.
In And Suddenly the Inventor Appeared, Altshuller says, "We understand the logic of technical systems evolution and can foresee the arising of new problems, knowing beforehand how they can be solved." [3, p.60]
Nearly all TRIZ case studies contain, plainly or implicitly, predictions. Recent examples include:
- A forecast of digital imaging technology [17]
- The evolution trends of soil logging tools [16]
- The evolution of corrosion protection in shipbuilding [18]
However, while there are many examples of forecasting, statistical evidence remains scarce.
100 Predictions with TRIZ
There have not been packages or lists of predictions, allowing making statistically reliable conclusions. If a "TRIZ prediction" hits the mark, does it mean that the theory works? Not necessarily, since there may be ten other predictions that miss the mark. If a TRIZ prediction fails, does it mean that the tools of TRIZ are bad? Again, not necessarily, since at the same time these tools can provide ten or twenty successes. We need more than a few predictions to prove the methodology. I used TRIZ to forecast the following 100 innovations likely to come in the next 33 years – by the year 2040.
Transportation
- Zero vision realized in transportation make crashes rare
- Automated people movers that combine the benefits of public and private transport
- Automated goods movers
- Mass-customized and easily constructed roads
- Personal flying devices
- "Wingships," combining the benefits of the airplane and the ship
- Space elevators
- Micro-spacecrafts
- Super-sonic airplanes widely used
- Miniature, solar-powered automatic airplanes and helicopters
- "Smart" and automated cars
- Shared use of vehicles
- Totally networked cars with TVs, phones and computers
Energy
- Rise of nuclear, solar and hydrogen energy; decrease of oil consumption
- Use of small nuclear reactors and miniature atomic batteries
- Safer nuclear reactors
- Use of fusion power starts
- Mining helium on the Moon for fusion reactors on Earth
Food
- Functional food or food with health effects
- Smart food packages
- Conservation agriculture widely practiced
- Artificial meat
- Automated cooking
Clothing
- Mass-customization in clothing
- Self-cleaning clothing
- Clothing that collects and releases heat
- Smart clothing with embedded phones and computers
- Clothing capable of changing size
- Clothing capable of changing color
Housing and Buildings
- Elevators in all buildings
- Accessible houses and barrier-free environments
- Domes and other curved parts in buildings widely used
- Storm safe buildings
- Earthquake safe buildings
- Floating homes and cities
- Walls that change transparency and color
- Multi-store cities with elevated and underground streets
- Mass-customized housing
- Automated erection of buildings and wide use of construction robots
- Flexible shells and thin films widely used in buildings
Communication
- Mesh networks of very small smart sensors of "smart dust"
- Multimodal interfaces using voice, video and haptic interface
- Reprintable electronic office paper for computers
- Ubiquitous video conference technology and mobile video phones
- 3D-TV ubiquitous
- Tele-immersion (TV around the user)
- Good voice recognition and voice-to-text transformation
- First online interpreters
- Everyone has thousands of very small computers
- Simple and cheap, disposable and recyclable phones and computers
- Advanced telepresence
- Distance interpretation via portable video phones
- Advanced avatars or digital personalities
- "World library" provides access to all audiovisual information
- Brain-computer interfaces
- Intuitive interfaces to guess the needs of the user
- Biometric recognition instead of paper documents
- Virtual shopping
- Electronic books
- Individual GPS
- Life recording
Robots
- Robots making robots
- Swarms of many small robots
- Robotization of agriculture
- Home robots for cleaning, gardening and other tasks
- Patrol robot for public and private security
- Robots, vehicles and buildings that can assemble themselves
Health
- Distance control of health
- Health monitors implanted into the body
- Predictive genetic tests
- Individually tailored drugs
- Surgeon-robots
- Vaccination against tooth decay
- Manufacturing parts of human body
- Devices and drugs for the control of obesity
- Easily available technologies for cosmetic surgery and other ways of reshaping the human body
- Smart toilets monitor health
- Chip-assisted human memory or neural prosthetics
- First steps of bionics and cyborg technology
- Technology to change the color of skin
Environment
- Economically viable ways to collect, store and use carbon dioxide
- Effective ways to prevent dust and collecting dust
- Improved acoustic environments and noise cancellation
- Biological and other micro-level control of oil pollution
- Limited control of climate in cities and small biospheres
- Production of fresh water
Sport and Entertainment
- Cyborg athletes containing artificial muscles
- Space sports and holidays in space
- Robots playing football and other games challenge human athletes
Miscellaneous
- Improved accuracy of lie detectors
- Electronic money instead of cash
- Desktop production plants
- Automated stores
- First steps of improved animal intelligence
- Prisons without walls or electronic surveillance of prisoners
- Biosensors widely used
- Wide use of photonics
- Use of photocromic materials
- Nanomaterials, as cheap as steel and many times stronger
- Artificial photosynthesis
This list is only a partial picture of the future and nearly everyone will disagree with one or more predictions. I encourage readers to publish improved lists.
Conclusion: Predictions Help Validate TRIZ
The potential benefits of predictions have been largely ignored. Forecasting is a good way to test and verify theories of problem solving, particularly TRIZ. TRIZ is considered science and Altshuller spoke of the "exact science" of creativity.
One requirement of scientific research is that theories should be empirically tested. Empirical evidence of the validity of TRIZ consists mainly of success stories, references and testimonials. This evidence is necessary, but not enough. But, another feature of science is its ability to predict the future. Science must give significantly more precise forecasts than pure guesswork. A new theory, like TRIZ, should give significantly more precise forecast than traditional approaches and also should be applicable to practical forecasting, research and development work. If both hypotheses and results are kept private as proprietary information, science evolves slowly. Publication allows for a rigorous verification. When hypotheses are publicized, it is not possible to fit facts to a result after the fact.
Making predictions is a good way to test TRIZ. If the theory is valid, predictions made by TRIZ should be significantly more precise than forecasts made by the Delphi Method or other conventional tools alone.
Extra: The Predictions for Comparison
To more easily compare these predictions with Kahn's and Wiener's list, the foresights are presented here as a single list:
- Zero vision realized in transportation make crashes rare
- Automated people movers that combine the benefits of public and private transport
- Automated goods movers
- Mass-customized and easily constructed roads
- Personal flying devices
- "Wingships," combining the benefits of the airplane and the ship
- Space elevators
- Micro-spacecrafts
- Super-sonic airplanes widely used
- Miniature, solar-powered automatic airplanes and helicopters
- "Smart" and automated cars
- Shared use of vehicles
- Totally networked cars with TVs, phones and computers
- Rise of nuclear, solar and hydrogen energy; decrease of oil consumption
- Use of small nuclear reactors and miniature atomic batteries
- Safer nuclear reactors
- Use of fusion power starts
- Mining helium on the Moon for fusion reactors on Earth
- Functional food or food with health effects
- Smart food packages
- Conservation agriculture widely practiced
- Artificial meat
- Automated cooking
- Mass-customization in clothing
- Self-cleaning clothing
- Clothing that collects and releases heat
- Smart clothing with embedded phones and computers
- Clothing capable of changing size
- Clothing capable of changing color
- Elevators in all buildings
- Accessible houses and barrier-free environments
- Domes and other curved parts in buildings widely used
- Storm safe buildings
- Earthquake safe buildings
- Floating homes and cities
- Walls that change transparency and color
- Multi-store cities with elevated and underground streets
- Mass-customized housing
- Automated erection of buildings and wide use of construction robots
- Flexible shells and thin films widely used in buildings
- Mesh networks of very small smart sensors of "smart dust"
- Multimodal interfaces using voice, video and haptic interface
- Reprintable electronic office paper for computers
- Ubiquitous video conference technology and mobile video phones
- 3D-TV ubiquitous
- Tele-immersion (TV around the user)
- Good voice recognition and voice-to-text transformation
- First online interpreters
- Everyone has thousands of very small computers
- Simple and cheap, disposable and recyclable phones and computers
- Advanced telepresence
- Distance interpretation via portable video phones
- Advanced avatars or digital personalities
- "World library" provides access to all audiovisual information
- Brain-computer interfaces
- Intuitive interfaces to guess the needs of the user
- Biometric recognition instead of paper documents
- Virtual shopping
- Electronic books
- Individual GPS
- Life recording
- Robots making robots
- Swarms of many small robots
- Robotization of agriculture
- Home robots for cleaning, gardening and other tasks
- Patrol robot for public and private security
- Robots, vehicles and buildings that can assemble themselves
- Distance control of health
- Health monitors implanted into the body
- Predictive genetic tests
- Individually tailored drugs
- Surgeon-robots
- Vaccination against tooth decay
- Manufacturing parts of human body
- Devices and drugs for the control of obesity
- Easily available technologies for cosmetic surgery and other ways of reshaping the human body
- Smart toilets monitor health
- Chip-assisted human memory or neural prosthetics
- First steps of bionics and cyborg technology
- Technology to change the color of skin
- Economically viable ways to collect, store and use carbon dioxide
- Effective ways to prevent dust and collecting dust
- Improved acoustic environments and noise cancellation
- Biological and other micro-level control of oil pollution
- Limited control of climate in cities and small biospheres
- Production of fresh water
- Cyborg athletes containing artificial muscles
- Space sports and holidays in space
- Robots playing football and other games challenge human athletes
- Improved accuracy of lie detectors
- Electronic money instead of cash
- Desktop production plants
- Automated stores
- First steps of improved animal intelligence
- Prisons without walls or electronic surveillance of prisoners
- Biosensors widely used
- Wide use of photonics
- Use of photocromic materials
- Nanomaterials, as cheap as steel and many times stronger
- Artificial photosynthesis
References
- Altshuller, G., Shapiro, R., Psychology of Inventive Creativity, Izobretenia vol. II, 2000, 23-27.
- Altshuller, G., Creativity as an Exact Science, Gordon and Breach, New York, 1984.
- Altshuller, G., And Suddenly the Inventor Appeared, Technical Innovation Center, 1996.
- Chuksin, P., Shapakovsky, N., "Information Analysis and Presentation in Forecasting," The TRIZ Journal, March 2006.
- Domb, E., "Strategic TRIZ and Tactical TRIZ: Using the Technology Evolution Tools," The TRIZ Journal, January 1996.
- Fey, V., Rivin, E., Guided Technology Evolution (TRIZ Technology Forecasting), Izobretenia vol. 1, 1999, 11-19.
- Kahn, H., Wiener, A., The Year 2000, The Macmillan Company, New York,1967.
- Kowalick, J., "Technology Forecasting Using TRIZ," The TRIZ Journal, January 1996.
- Petrov, V., "The Laws of System Evolution," The TRIZ Journal, March 2002.
- Rantanen, K., Domb, E., Simplified TRIZ: New Problem Solving Applications for Engineers & Manufacturing Professionals, CRC St. Lucie Press, Boca Raton FL USA, 2002.
- Rantanen, K., "Homes for Strong Families, Children, Seniors and All Others. Universal Design, Design for All and Forty Principles of TRIZ Enforce Each Other," The TRIZ Journal, May 2005.
- Salamatov, Y., TRIZ: The Right Solution at the Right Time, Insytec, Hattem, 1999.
- Salamatov, Y., "Memorandum On New Field For TRIZ Application And Development: TRIZ In Virtual World (Business Proposal For Years 2005-2020)," The TRIZ Journal, July 2005.
- Savransky, S., Engineering of Creativity, CRC Press, Boca Raton, 2000.
- Seya, M., "Tecnology Foresight in Japan," International Seminar Foresight Studies on Science and Technology: International Experiences, Brasilia, Brazil, September 27, 2000.
- Teplitskiy, A., Roustem, K., "Evolution Trends in Nuclear Soil Logging Tools," The TRIZ Journal, November 2006.
- Tompkins, M., Price, T., Clapp, T., Parker, I. "Technology Forecasting of CCD and CMOS Digital Imaging Technology using TRIZ," The TRIZ Journal, March 2006.
- Weitzenböck, J., Marion, S., "Using TRIZ to Develop New Corrosion Protection Concepts in Shipbuilding A Case Study," The TRIZ Journal, December 2006.
About the Author:
Kalevi Rantanen worked in Finnish youth organizations, primarily on problems of education, in the 1970s. From 1979-1985, he studied in the former USSR and earned his M.Sc in mechanical engineering and was introduced to TRIZ. Rantanen worked in Finnish industry until 1991, while also a TRIZ trainer. Since 1991, he has been an independent entrepreneur and has concentrated on science and technology journalism since 2002. Contact Kalevi Rantanen at kalevi.rantanen (at) kolumbus.fi.
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