## Building Taller Ladders

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### Science and technology coevolution: core argument
- Technological progress not only affects productivity directly but also "pulls itself up by the bootstraps" by giving science more powerful tools to work with.
- Humans have limited sensory and computational capacities; technology functions as "artificial revelation" to overcome those limitations.
- Historical precedents: 17th century scientific revolution enabled by better instruments (Galileo’s telescope; Hooke’s microscope); modern scientific advances similarly enabled by improved instruments and lab techniques.

### Instrumentation and its scientific impact
- X-ray crystallography:
  - Instrumental in discovering the structure and function of many biological molecules, including vitamins, drugs, and proteins.
  - Its most famous application was the discovery of the structure of the DNA molecule.
  - "Its use has been instrumental in 29 other Nobel-Prize-winning projects."
- Microscopy and miniaturization:
  - Scanning tunneling microscopes (early 1980s) enabled nanoscopic research.
  - Betzig-Hell super-resolved fluorescent microscope (Nobel Prize developers) compared to Leeuwenhoek’s microscope metaphorically as "what a thermonuclear device is to a firecracker."
- Telescopy:
  - Hubble telescope described as revolutionary and "soon to be replaced by the much more advanced James Webb space telescope."

### Fast computing, data science, and simulation
- Two recent, radical tools: fast computing (including practically unlimited data storage and search techniques) and laser technology.
- Computers in science:
  - Beyond analyzing large-scale databases and standard statistical analysis: advent of "data science" where models are sometimes replaced by "powerful mega-data-crunching machines."
  - Machine-learning algorithms detect patterns "so twisty that the human brain can neither recall nor predict them" (Weinberger 2017, 12).
  - Computers simulate and approximate solutions of complex equations to study poorly understood processes, design new materials, and simulate models lacking closed-form solutions.
  - Emergence of entire "computational" fields where simulation and large data processing are strongly complementary.
- Quantum computing and artificial intelligence:
  - Quantum computing may increase computational power "by a substantial factor."
  - Artificial intelligence could become "the world’s most effective research assistant," even if it may never "become the world’s best researcher" (Economist 2016, 14).

### Laser technology: breadth of applications
- Early lasers were initially considered "in search of an application" but by the 1980s were used to cool micro samples to extraordinarily low temperatures.
- Contemporary laser applications:
  - Laser-induced breakdown spectroscopy: quick chemical analysis at atomic level without sample preparation.
  - Lidar (light radar): creates highly detailed three-dimensional images used in geology, seismology, remote sensing, atmospheric physics; has revised upward estimates of pre-Columbian Maya civilization sophistication in Guatemala.
  - Laser ablation: any type of solid sample can be ablated for analysis with no sample-size requirements and no sample preparation procedures.
  - Laser interferometers: used to detect gravitational waves Einstein postulated.

### Biology, genetics, and the "century of biology"
- Framing: "if the 20th century was the century of physics, the 21st century will be the century of biology" (Freeman Dyson).
- Genome sequencing cost decline:
  - From $95 million per genome in 2001 to about $1,250 in 2015.
- Genetic editing and synthetic biology:
  - CRISPR Cas9 improvements enable editing a base pair in a genetic sequence.
  - Synthetic biology allows manufacturing organic products without living organisms; "cell-free production of proteins" concept known for about a decade but "its realization is still years away."

### New materials and nanotechnology
- Historical constraint: many past technological ideas could not be realized because available materials were inadequate.
- Recent advances in material science enable design of synthetic materials with custom-ordered properties at the nanotechnological level.
- Examples in development or perfection: new resins, advanced ceramics, new solids, and carbon nanotubes.

### General-purpose technologies (GPTs) and economic implications
- Artificial intelligence, lasers, and genetic engineering presented as GPTs with many applications across production and research.
- GPTs typically require time, complementary innovations, and investments to fully affect the economy but can produce transformative changes across many dimensions.
- The author emphasizes uncertainty in predicting specific technological trajectories: "some advances will be made that no one is forecasting, while other promising advances will disappoint."
- The central case for continued rapid technological progress rests on the symbiotic coevolution of technology and science: instruments and tools give researchers vastly more powerful capabilities, leading to unforeseen advances.

- Concluding metaphor: the high-powered computers, lasers, and many other tools of our age will lead to technological advances "that cannot be imagined today any more than Galileo could foresee the locomotive."

*Joel Mokyr, Finance & Development, June 2018.*

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_Source: https://www.imf.org/-/media/files/publications/fandd/article/2018/june/mokyr.pdf_