These slides empirically analyzes predictions made by MIT’s Technology Review. Technology Review has produced a list of 10 breakthrough technologies for many of the last 10 years (2001, 2002-2014). These predictions are based on conversations with academic experts from a variety of scientific disciplines. To analyze these predictions, I gathered recent market sales data for the predictions done in 2001, 2003, 2004 and 2005. I found that many of these technologies still have small markets (<$1Billion), markets that are smaller than technologies not chosen by Technology Review such as smart phones, Cloud Computing. Tablet Computers. Big Data, Social Networking, and eBooks/eReaders. The slides then use theories of cognition to explain these relatively poor predictions and propose an alternative way of predicting breakthrough technologies
2. The Context
MIT’s Technology Review produces a list of 10 breakthrough
technologies each year (2001, 2002-2014)
These lists are based on conversations with academic
experts from a variety of scientific disciplines
In July 2014, I gather recent market sales data for the
predictions done in 2001, 2003, 2004 and 2005
This was done by Googling market, size, and sales for each
technology,
sometimes changing the name of the technology or broadly
defining it in order to find data
Reports by market forecasting companies were the major
sources of data
3. The Basic Conclusion
After excluding 7 technologies that were too broad to gather data, there
were 33 technologies
1 has greater than $10 Billion in sales
smart grids (power grid control)
2 have sales between $5 and $10 Billion
micro-photonics, personal genomics
11 have sales between $1 and $10 Billion
Grid computing, Molecular imaging, Synthetic Biology, Distributed Storage
RNAi Interference, Brain-Machine Interface, Data mining, Biometrics
Digital Rights Management, Natural Language Processing, Microfluidics
5 have sales between $100 million and $1 Billion
14 have sales less than $100 million
4. How Good were these Predictions?
Difficult to assess, but
More than half still have small markets of less
than $1Billion in sales
Might these markets grow in the near future?
Or have they been abandoned?
Did MIT’s Technology Review miss any
technologies that have become big markets in the
21st century?
5. Some Big Markets that Have Emerged in
the 21st Century
Smart Phones: $335 Billion in 2013
Cloud Computing: $110 billion in 2012
Tablet Computers: $61 billion in 2012
Big Data: $11.6 Billion in 2012
Social Networking: Facebook had revenues of $7.8 Billion in 2013
eBooks and readers: >$5 billion just in the U.S. for Amazon
Adjusting for global markets, these technologies have larger
markets than $10B, which is larger than 33 of the 34 technologies
chosen by MIT
6. What Technologies were Chosen in Place of the Big Markets?
2005
Airborne Networks
Quantum Wires
Silicon Photonics
Metabolomics
Magnetic-
Resonance Force
Microscopy
Universal Memory
Bacterial Factories
Enviromatics
Cell-Phone Viruses
Biomechatronics
2004
Universal
Translation
Synthetic Biology
Nanowires
T-Rays
Distributed
Storage
RNAi Interference
Power Grid Control
Microfluidic
Optical Fibers
Bayesian Machine
Learning
Personal Genomics
2003
Wireless Sensor
Networks
Injectable Tissue
Engineering
Nano Solar Cells
Mechatronics
Grid computing
Molecular imaging
Nanoprint
lithography
Software
assurance
Glycomics
Quantum
cryptography
2001
Brain-Machine
Interface:
Flexible Transistors
Data Mining
Digital Rights
Management
Biometrics
Natural Language
Processing
Microphotonics
Untangling Code
Robot Design
Microfluidics
7. How could this have Happened?
Why did MIT’s Technology Review choose these esoteric
sounding technologies in 2001, 2003, 2004 and 2005 in place of
smart phones, cloud computing, tablet computers, Big Data,
social networking services, and eBooks?
A good question for fields of cognition and behavioral science
MIT is a leading if not the leading engineering university in the
world
Clearly there are major cognitive biases in predicting
breakthrough technologies, even for smart people
Let’s consider one from Daniel Kahneman, Nobel Laureate in
Economics
8. Cognitive Biases: Nobel Laureate Daniel Kahneman
People assess relative importance of issues, including new
technologies
by ease of retrieving from memory
largely determined by extent of coverage in media
E.g., media talks about solar, wind, battery-powered vehicles, bio-fuels and thus
many think they have rapid rates of improvement - but only some are
Second, judgments and decisions are guided directly by feelings of
liking and disliking
One person invested in Ford because he “liked” their products – but was Ford stock
undervalued?
Many people “like” some technologies and dislike others without considering rates
of improvement
Source: Daniel Kahneman, Thinking Fast and Slow, 2011
9. How Might Kahneman’s Ideas Apply to MIT
MIT’s Technology Review didn’t pay attention to popular media
when they made their predictions
But, they used their own network of engineers and scientists,
who may be smarter than popular media but nevertheless biased
Leading academic engineers and scientists usually
research elemental technologies
emphasize new scientific disciplines or ideas
optimistic about their technologies or those of their colleagues
and thus ignore system technologies (or markets) such as smart phones,
tablet computers, and cloud computing
The upshot is that MIT’s Technology Review chose a wide variety of
“ideas,” many of which will never become big markets
10. Preliminary Conclusions
Don’t ask the experts because they are just as
biased as everyone else…..
More research on this issue is needed
A more systematic application of cognitive
biases to predictions about breakthrough
technologies is needed to understand why
predictions aren’t so good
And a more systematic method of predicting
breakthrough technologies is needed
11. Is their a Better Way?
Some technologies experience more rapid rates of
improvement than do other technologies
Do these technologies have a better chance of achieving
growth in market size than do other technologies?
For example, have integrated circuit-related technologies
(e.g., smart phones) achieved larger market sizes than
have other technologies?
Rough Analysis: using a data base on rates of improvement
for more than 100 technologies,
underlying technologies for predicted breakthrough
technologies (and those on slide 5) and their rates of
improvement were identified
See my slideshare account (http://www.slideshare.net/Funk98/presentations), Technology Change and the Rise of New Industries (http://www.sup.org/book.cgi?id=21867) and
Exponential Change: What Drives it and What Does it tell us About the Future http://www.amazon.com/Exponential-Change-drives-about-future-ebook/dp/B00HPSAYEM
12. Breakthrough Technology Underlying Technologies
Smart phones Integrated Circuits (ICs), Displays
Tablet computing
eBooks and eReaders ICs, Displays, Organic Transistors
Digital Rights Management ICs
Biometrics
Molecular imaging Computers, Photo-sensors
Microfluidics MEMS
Micro-photonics Photonic ICs
Smart Grids (power control) Internet bandwidth
Cloud computing
Big Data
Social Networking
Data mining Internet bandwidth, Computers
Grid computing
Natural Language Processing Internet bandwidth, Computers
Distributed Storage Internet bandwidth, Mag Storage
Personal genomics DNA Sequencing
Synthetic Biology DNA Synthesizing
Brain-Machine Interface Invasive Neural Interface
Techniques
Technologies DimensionsofMeasure Improvement
RatePerYear
IntegratedCircuits NumberofTransistorsPer
Chip
38%
MEMSChips Dropspersecond 61%
OrganicTransistors Mobility 94%
Photo-sensors Pixelsperdollar 49%
PhotonicICs DataCapacityperchip 39%
Displays Squaremetersperdollar 11%
MagneticStorage Bitsperdollar 39%
Computers Instructionsperunittime 36%
Bitspersecond 49%
InvasiveNeural
Interface
SimultaneouslyRecorded
Neurons
10.1%
DNASequencers Sequencingperunitcost 146%
DNASynthesizers Synthesizingperunitcost 84%
Rates of Improvements for Technologies that Impact on “Breakthrough Technologies”
13. CurrentMarketSize
> $10B
>$1B
<$10B
< $1B
Rates of Improvement
Slow (<10%)
Rates of Improvement vs. Current Market Size
Fast (>10%)
Smart Grids Smart Phones
Cloud Computing Tablet Computers
Big Data Social Networking
eBooks/readers
Micro-photonics, Personal genomics, Grid
computing, Molecular imaging, Synthetic
Biology, Distributed Storage, Brain-Machine
Interface, data mining, Digital Rights
Management, Biometrics, Natural
Language Processing, Microfluidics
Wireless Sensor Networks, Flexible
Transistors, Bio-mechatronics
Quantum cryptography, T-Rays, Quantum Wires,
Silicon Photonics, Universal Memory, Injectable
Tissue Engineering, Nano Solar Cells, Nanowires,
Microfluidic Optical Fibers, Airborne Networks,
Magnetic-Resonance Force Microscopy, Cell-
Phone Viruses, Robot Design, Glycomics,
Nanoprint lithography, Metabolomics
RNAi Interference
14. Seems to be a Correlation..
Technologies with faster rates of improvement generally have
larger market sizes
>$10B: all 7 had rapid rates of improvement
$1B >, <$10B: 10 of 11 had rapid rates of improvement
<$1B: 3 of 19 had rapid improvements
But this is just a rough analysis
Not easy to identify underlying technologies for all of the
predicted breakthroughs
Data on all relevant underlying technologies were not found
Some technologies may be experiencing rapid rates of
improvement even though data for them was not found
15. Conclusions
Predicting future “Breakthrough Technologies” is very
Difficult
Predictions made by MIT’s technology Review were not very
accurate
Missed important technologies while choosing unsuccessful
ones
Rates of improvement may be a better predictor of future
success
Understand these technologies
Then think about the types of new systems that they enable