New types of data
Cryptocurrenies on the Blockchain will be numbered in the thousands. As currencies develop around varied aspects of commercial activities, these economic systems will serve as quantifiable measuring tools of human behavior. This abundance of new data points comes along at a time humans are starting to employ machines to observe, learn and set favorable real world conditions.
The Blockchain’s ability to assign value to anything will result in powerful market incentives to measure the biosphere in great detail. When nations earn for producing clean water, air and proper waste management; the same effort to measure and find fossil fuels will be shifted to measuring the greater Environment. Playing into the truism attributed to Hewlett Packard “what gets measured, gets fixed.”
Digital coin economies will be built around energy, water, carbon capture, among many, many other commercial activities. The aggregate of all these new economic systems will be subject to computer-aided monitoring and learning systems. Over time, this data and computer analysis will start to understand and predict economic and environmental outcomes.
The more cryptocurrencies the better the data
Cryptocurrencies tailored to different commercial activities will provide continuous detailed real-time data. Before we know it our digital wallets will be categorized by fuel coins, energy coins, pizza coins, airline coins. The wallets of the near future will be able to do analysis of personal finances, recommend spending habits and financial strategies.
Armed with thousands of micro-currencies as data points the human condition will be quantifiable and measurable like never before. Over time, group behavior will be measured and learned to an almost creepy accuracy.
Biosphere economy
Coins will soon appear based on the value of clean water, renewable energy, clean air, and waste. These coin systems will create enormous and easily consumable data sets about how humans and the biosphere interact.
In the competent hands of Machine Learning (ML) analysis, the more detailed economic data around human behavior and the environment will lead to predictive machine analysis. Further, this computer analysis can recommend economic tools and procedures that best balance desired economic and environmental outcomes.
The core purpose of analysis is to provide warning and avoid surprise. The more data points we create, collect and analysis, the outcome is less suprise. This new certainty of the future will allow for better environmental planning and public policy.
At the individual level, our new wallets will be able to recommend spending and earning habits that will maximize our impact on the environment. In more strategic ways, national and international policy will benefit from this detailed and consumable data. From micro to macro ML will help individuals and communities make environmentally profitable decisions. The imparticality of the machine automation returns benefits for the entire ecosystem instead of a select few mega conglomerates interests.