Roots of the Attention Crisis in History

A historian of science from All Souls College at Oxford recently reached out to me. He shared an essay he authored about Nicolaus Steno, a prominent seventeenth-century anatomist and geologist who eventually became a Catholic Bishop. Steno's scholarly education took place during an era grappling wi

A historian of science from All Souls College at Oxford recently reached out to me. He shared an essay he authored about Nicolaus Steno, a prominent seventeenth-century anatomist and geologist who eventually became a Catholic Bishop.

Steno's scholarly education took place during an era grappling with a fresh challenge: an overwhelming flood of information. The essay captures this dynamic in vivid terms:

Books emerged as a primary source of distraction during the early modern period—a time we might now view with a touch of envy. Starting in the 1500s, the invention of the printing press combined with the humanist resurgence of classical philosophies led to knowledge proliferating at an unprecedented rate.

This surge prompted critical dilemmas for emerging intellectuals, such as: How can we determine which materials warrant our reading time? For how long should we engage with each one? Is it necessary to extract notes from every chapter?

Scholars responded in part by pioneering innovative note-taking methods, like transcribing key passages into a centralized ledger known as a commonplace book. This approach helped manage the influx of ideas effectively.

Yet, as the essay on Steno further explains, enhanced note-taking alone could not fully address the issue, given the sheer volume of compelling books circulating. To counter this, Steno devised more sophisticated tactics for managing attention while pursuing his university studies in the 1650s:

He trained himself to concentrate on particular subjects instead of flitting rapidly between diverse materials. As he noted, one must steer clear of 'harmful hastening.' His strategy involved committing fully to a single topic.

Practically speaking, this translated to reserving dedicated time slots for the most challenging work. In his private journal, Steno recorded: 'before noon nothing must be done except medical things.' He confided to a colleague that he dedicated 'almost all the morning hours' to studying the writings of the Church Fathers and ancient biblical texts housed in the Medici library.

Essentially, Steno formulated a system that integrated principles we recognize today as slow productivity, deep work, and time blocking—strategies that harmonize sustained focus with structured scheduling.

The takeaways from this historical episode are straightforward and enduring. Employing our cognitive faculties for profound reflection on significant concepts is not a modern invention. It has formed a foundational element of intellectual pursuit since the early modern era, when complex information first became relatively accessible to a broader audience.

The time-tested techniques forged in that period continue to hold strong: minimize exposure to excess information, dedicate yourself to one pursuit at a time, and allocate precise blocks of your schedule for those endeavors requiring the greatest mental intensity.

AI Reality Check

Just two weeks back, Citrini Research, a boutique firm in financial services, released an essay outlining a grim projection: AI agents poised to devastate the white-collar employment landscape in the coming years. The publication exploded in popularity online and even influenced a slight dip in the S&P 500 the following trading day.

This was hardly the inaugural discussion of such a dire outlook. Over recent weeks, numerous articles and opinion pieces in prestigious outlets have echoed these concerns with notable credulity. The market's reaction, however, appears to have galvanized economists, prompting a wave of rebuttals against these speculative tales of technological upheaval. One standout critique came from a Deutsche Bank analyst, who cleverly described the Citrini piece as exhibiting a 'vibes-to-substance ratio' that was notably elevated.

For those seeking to temper concerns over AI's potential to upend the economy, a thorough counterargument from an analyst in Citadel's Global Macro Strategies group offers substantial reassurance. It opens with a wry jab at economic forecasting:

Even as the macroeconomic field falters in predicting payroll figures just two months ahead with consistency, some claim to discern the trajectory of widespread job losses with remarkable assurance from a speculative Substack post.

The analysis proceeds to methodically dismantle the economic oversimplifications underpinning these alarmist narratives about AI triggering an abrupt economic collapse. Reading it provided a significant sense of relief amid the hype.