Arguably there have been three scientific revolutions. The first in ancient Greece associated with the growth of materialism, in which matter became the fundamental substance in nature.
The second in the 17th century in which empirical observation and mathematics emerged as a highly effective means of acquiring instrumental knowledge about the world.
And the third revolution, that we are experiencing today, in which computers provide a combination of simulation platforms for experimental observation, structured and searchable storage for large data sets, and interpretive algorithms for prediction.
All three revolutions have been felt far beyond the academy and have transformed culture, from commerce through to conflict. The world in which we live is in large part defined by these revolutions.
Science among computing machines raises a range of fascinating and important new questions. Included among these are:
1. What will happen to efforts at human understanding when computing platforms equal or outperform our best mechanistic sciences? What will this mean for the structure of knowledge and institutions that create, curate, and manipulate knowledge?
2. What are the limits of insight and prediction associated with computational science? And how will the scientific revolution of the 17th century be combined with the revolution of the 21st century? Combining the best of fundamental theory with the best of prediction.
3. Can we map out those areas of activity, from engineering, the economy, health care, and national defense, where computational and data science will continue to be transformative?
4. What might society look like when human strategy and reason is outsourced to global algorithms? Specifically, what changes might we see in the areas of education, sovereignty, international law, and resource scarcity?
These are some of the key questions that we shall be exploring at the forthcoming topical action meeting, Science Among the Machines.
At the meeting we shall have experts in complexity science, computational social science, machine learning, neuroscience, and economics.
ACtioN Meetings are open to members of the Applied Complexity Network and invited special guests. Please contact firstname.lastname@example.org if you would like more information on becoming a member.