https://en.wikipedia.org/wiki/Thinking%2C_Fast_and_Slow
The book delineates rational and non-rational motivations or triggers associated with each type of thinking process, and how they complement each other, starting with Kahneman's own research on loss aversion. From framing choices to people's tendency to replace a difficult question with one which is easy to answer, the book summarizes several decades of research to suggest that people have too much confidence in human judgment. Kahneman performed his own research, often in collaboration with Amos Tversky, which enriched his experience to write the book. It covers different phases of his career: his early work concerning cognitive biases, his work on prospect theory and happiness, and with the Israel Defense Forces.
In the book's first section, Kahneman describes two different ways the brain forms thoughts:
System 1: Fast, automatic, frequent, emotional, stereotypic, unconscious.
System 2: Slow, effortful, infrequent, logical, calculating, conscious
Kahneman describes a number of experiments which purport to examine the differences between these two thought systems and how they arrive at different results even given the same inputs. Terms and concepts include coherence, attention, laziness, association, jumping to conclusions, WYSIATI (What you see is all there is), and how one forms judgments. The System 1 vs. System 2 debate includes the reasoning or lack thereof for human decision making, with big implications for many areas including law and market research
So, while it is true System 2 thinking is sluggish at best, a great deal of our mental labor is handled by System 1. The System 2 processing takes more resources and more time, but produces more accurate results.
Much of our modern intellectual infrastructure is intended to off-load tasks from System 2 to System 1, allowing us to rely on heuristics instead of the plodding manual labor of information processing. You don't need to mentally track the time of day when you can just remember to glance at a clock. You don't need to have every recipe memorized when you can consult a cookbook page number. You don't need to do higher level math when you can just plug numbers into an Excel spreadsheet.
In theory, direct human augmentation could further refine this process. You don't need to "do math" as a System 2 task, just invoke your link to an internal calculator instinctively as a System 1 task.
But in practice we simply don't know enough of how the human brain works. The latest edition of Sean Carroll's Mindscape discusses this problem with Jeff Lichtman, a National Academy of Sciences neurologist who is working to physically map the wiring of brains of simple species.
How do neural networks form and invoke one another? What work do individual neurons do internally and what needs to be part of a composite process of neurons acting in concert? How is information encoded in the brain and retrieved? How is action invoked? There aren't good answers to any of these questions. Certainly not good enough to start shoving silicon and steel into anyone's heads with the intent of improving cognitive processes.
Therein lays the rub.