The Power of Multi-cycle Thought: How Great Minds Develop New Ideas

Multi-Cycle Thought Leads to Bold New Ideas

Daniel Kahneman’s book — Thinking, Fast and Slow — helps readers avoid cognitive pitfalls and encourages everyone to double-check any quick, “intuitive” response they may have to a problem. This is immensely helpful (letting one avoid many common mistakes), yet progress on really hard problems requires a different, “extra-slow” method that I refer to as multi-cycle thought. 

This mode of thought involves a recursive process in which one gradually updates and refines ideas, and it can be used in a wide variety of settings. It’s needed in almost every professional setting — when designing a new building, writing a legal brief, starting a company, or addressing new problems in science or technology. However, I’ll focus on some extreme cases where the benefits of multi-cycle thought profoundly impact the course of the human future. Here I’ll consider ways in which this method has been used by some of the great minds of history and some of the ways it can help as society struggles to deal with the challenges of the Anthropocene.

History offers some wonderful examples of the power of this deeper, multi-cycle method of thought. We see this in the work of Charles Darwin: Asking a good question and setting out some tentative ideas helped to guide and direct the process of thought long before he could solve the riddle of evolution. Similar modes of thought were needed when James Madison and other delegates developed the US Constitution in the summer of 1787. 

Unfortunately, few descriptions of any relevant methodology for multi-cycle thought have yet been offered. This type of thought is hard to study in the laboratory, and examples like those cited above may seem radically different. Yet, there are some clear patterns. Taking Darwin as an example shows how multi-cycle thought depends on 1) a willingness to repeatedly revise and reshape ideas and 2) a subtle kind of judgment that’s needed at intermediate stages. That is: long before Darwin could see the full answer, he could begin to see what types of information were likely to be relevant. Darwin cast a wide net as he gathered information — studying geology, zoology, paleontology, botany, animal breeding, and horticulture.

Obviously, we have no way to know all the neurophysiological details behind the process of thought that Darwin used, but his reading, correspondence, and notebooks all draw attention to the way that neural networks must have changed over time. There is no way that Darwin could have written The Origin of Species immediately after returning from the voyage of the Beagle. He needed to work indirectly at first — gradually expanding his command of relevant fields of knowledge, gradually developing neural/synaptic networks that would allow him to think at a level that could change the world.

Work on other really hard problems starts in a similar way. One doesn’t have enough information to immediately see the path to an answer, yet there may be enough clues to begin the search. Progress then proceeds in a series of cycles, repeatedly updating the process and using the best information available at the moment to guide the ongoing search. It is necessary — as suggested in the figure below — to 1) seek out and absorb new information; 2) reconsider all prior assumptions, interpretations, and hypotheses in light of this new data; 3) ask new questions; and 4) then repeat the cycle dozens, hundreds, or thousands of times.

Multi-cycle thought diagram

Each of the key steps in this figure can be instantiated in a variety of different ways, and thus a menu of options is shown to the right of the first two steps. Efforts to seek out and absorb new information (in this first main step of each cycle) might involve reading, observation, experiments, discussion with others, consulting a chatbot, or running some other computer program. And, likewise, a variety of different approaches can be used when processing this information — when double-checking and updating internal mental models, when setting out questions for the next cycle of thought. Writing in a notebook or discussing new ideas with colleagues may help, and — sometimes — ideas may begin to “re-sort themselves” overnight or while taking a break and getting out for a walk. Yet, with the kind of hard problems now facing humanity, each cycle of thought (almost inevitably) leads to new questions. As with the work of Darwin, Madison, and the Continental Congress, thousands of cycles may be needed as this process plays out over a period of months and years.   

Detailed decisions made within each cycle will depend on the particular problem at hand and the particular stage of investigation, yet a few aspects of this approach are so fundamental that they bear special emphasis:

  • Having a good question — focusing on an important, potentially soluble problem — is key. A good question serves as a kind of guiding north star that helps at all intermediate stages of the search. And picking a good question (or goal that can be stated as a question) also requires some ability to foresee the difference between that which is difficult and that which is impossible. (There is, for example, no direct utility in trying to foresee what human life might be like a million years from now.) In short, the effort needed for multi-cycle thought can only be justified when there is hope of some significant practical reward to the individual, family, community, or society.
  • This kind of multi-cycle thought gets real traction when it leads to some initial hypothesis, or tentative interpretation, that can provide a clear starting point for subsequent work. It still took Darwin years of work after he sketched the first branching diagram in his notebooks in 1837, but this hypothesis about the way that new species might emerge over time helped him to ask more refined questions at all later stages of his work.
  • Since the mind needs some early hints to help focus the subsequent search, this approach works only when the “best final answer” occurs amidst a larger cloud of possible starting points that provide useful clues. (This type of multi-stage thought would not help when trying to guess a long, randomly chosen password that contained a mixture of letters, digits, and special characters.) Admittedly, it’s hard to know beforehand whether one has a useful starting point. This is one of the risks involved in working on such a hard problem. Everything depends on being able to pick a good hypothesis and being ready to revise it as needed.
  • The whole process can be seen at either a conceptual or a biochemical/biophysical level. At the conceptual level, progress might be tracked by studying notebooks or drafts prepared during different stages of the work. And yet — equally — everything here will reflect neural/synaptic changes that occur during the ongoing process of multi-cycle thought. New electrochemical patterns of activity arise in the mind/brain of the individual, allowing the emergence of ideas that would (quite literally) have been “unthinkable” at an earlier stage.

This process also requires anyone employing this method to understand some of the other, auxiliary constraints that are involved:

  • Multi-cycle thought — when employed at the levels considered here — comes at a real cost: It requires time, and benefits from circumstances that can temporarily set other concerns aside (as when Darwin tried to lead a simple life at his house in Kent, as when delegates to the Constitutional Convention worked without interruption for months at a time in the summer of 1787). When practiced most seriously, the commitment to this kind of deep thought becomes almost a way of life. Anyone taking this path will need to adjust the rest of their life to ensure that they have the time and the intellectual freedom needed for multi-cycle thought. Yet there is a chance to solve problems that might otherwise prove intractable. And dedicated “multi-cyclers” — knowing the power of this approach — will also begin using such strategies for all key decisions in their personal lives.
  • Perseverance with this kind of task requires a sense that — when given a worthy task — hard thought is worth all the effort involved. One needs to get some pleasure and satisfaction from the tiny steps that are taken every day. And progress also depends on having some ability to work well amidst a fog of uncertainty — rearranging and reevaluating ideas, remembering that each new interpretation still is tentative, trying to foresee what questions and what new sources of information may be most useful at the next stage.  

Hard problems often have a difficulty on par with that needed to earn a Ph.D., and this multi-cycle process of thought thus requires a bold spirit of adventure — facing the unknown, taking a chance, and trying to expand the range of human knowledge. Few guideposts are offered by others on this kind of journey (as one aims to do something that never yet has been done), and the general approach is so flexible and open-ended that it often helps, as below, to build in some kind of auxiliary support to help ensure steady progress.

Multi-cycle thought thus fits well with ideas about how to use a notebook (helping to capture intermediate stages of thought) and about how to work with teams to promote more careful thought and develop more effective plans. At Humanity 2050, we also had developed an algorithm for thought — using multi-cycle thought to ensure that all features of a proposed plan are consistent with all expected features of the future world in which that plan will unfold, and with all aspects of the desired outcome.

This multi-cycle method of thought is open-ended enough so as to take advantage of ongoing advances in AI, and powerful enough so as to be a critical tool in addressing the challenges of the modern age. This mode of thought gives hope that we can find solutions to our most pressing global problems and help ensure a livable future for our children and grandchildren.