The “future of work”. It promises so much, yet I fear it may deliver very little. The issue is an age-old problem that has existed since the dawn of technological time. We are stuck in the cycle of applying computer science rather than brain science. Let’s take email as one example. Yes, it’s an incredible tool that has transformed communication (faster, bigger and cheaper being the most obvious barometers for success), but it fails to replicate the way humans interact with physical mail. When we receive a stack of letters (paper emails), we instinctively sort it based on immediate relevance, creating dynamic piles for bills, personal correspondence, or urgent matters. It’s a fluid and adaptive process, driven by a complexity of context that sits well outside that pile. It aligns perfectly with our brains, which are hardwired to understand spatial relationships. Yet email, deeply rooted in computer science, requires us to predefine categories, assign labels, and navigate through rigid structures that do not naturally fit our cognitive processes. The science of managing digital stuff There’s a great book called The Science of Managing Our Digital Stuff by Ofer Bergman and Steve Whittaker, which delves into how our brains handle information. It highlights how traditional computer science overlooks our evolutionary predispositions. For instance, when managing digital documents, we often struggle with predefined folder structures and naming conventions. In contrast, our brains are adept at organizing physical items spontaneously based on their immediate importance. This discrepancy underscores the need for more intuitive, brain-friendly design in our computing environments. These thoughts are echoed by Cal Newport’s concept of the "hyperactive hive mind" workflow; another observation that perfectly encapsulates the chaotic, fragmented nature of modern work driven by poorly designed digital tools. Brains as computers, not computers as brains Our interaction with computers often feels disjointed because today’s desktop interfaces were not designed with human productivity as the primary focus; instead they emerged from the necessity to solve computer science problems, such as how to get multiple programs running simultaneously and interacting smoothly on a single screen. While this approach enhanced productivity by making computers more user-friendly, at a human-level they are still difficult to work with. From my perspective, the future of work hinges on integrating brain science into our computing environments. If we prioritized maximizing human capacity  from the start, our digital tools would look very different, enabling seamless collaboration and effectively supporting multiplayer modes of work. Take situational awareness as just one example. In digital environments it is crucial for both individual and business productivity. Modern software can notify us about new messages or changes in documents, but it doesn’t understand the context of why these updates matter to us, even if smart filters do their best to fulfill that role. This forces us to sift through notifications and decide what's relevant, often leading to information overload. According to a study by Stripe and Harris Poll, knowledge workers spend around 60% of their time on work about work, rather than the skilled labor they were hired to do. Our brains are evolutionarily wired to understand spatial relationships far better than abstract tags or folders, and so it is critical that we design tools that align with our instinctive ways of sorting and prioritizing. Unlocking value in meaningful work What is the immediate value in redesigning our computing environments with brain science principles? It goes beyond incremental gains at task-level, and can unlock the potential of both the individual and the organization. For example, better alignment between human cognitive processes and digital tools can reduce wasted effort and minimize the compounding confusion of misdirected work. This results in more accurate first-pass work, accelerating project completion and creating a virtuous cycle of productivity. Too often I see teams pushing collectively in the wrong direction; efficiency and being inefficient. There’s significant loss of value attached to this too. If numbers are more your thing then consider that a report by the IDC estimated that - just for the Fortune 500 companies alone - the cost of being unproductive is over $30 billion annually. Brain science-based computing environments will fundamentally change how businesses operate. While traditional task-level improvements offer incremental gains, aligning human and computer understanding promises exponential productivity boosts. Proper alignment ensures that people are doing the right tasks, reducing wasted effort and creating a more efficient, innovative work environment. The future of work shouldn’t be about getting that “edge”, it should be about opening up a productivity chasm. There’s a massive, untapped opportunity in rethinking how we integrate brain science with computing. By focusing on these areas, we can unlock unprecedented productivity and creativity in our work environment, creating a more engaged, efficient, and innovative workforce, and achieving true operational excellence. The “future of work”. It promises so much, yet I fear it may deliver very little. The issue is an age-old problem that has existed since the dawn of technological time. We are stuck in the cycle of applying computer science rather than brain science. Let’s take email as one example. Yes, it’s an incredible tool that has transformed communication (faster, bigger and cheaper being the most obvious barometers for success), but it fails to replicate the way humans interact with physical mail. computer science brain science. When we receive a stack of letters (paper emails), we instinctively sort it based on immediate relevance, creating dynamic piles for bills, personal correspondence, or urgent matters. It’s a fluid and adaptive process, driven by a complexity of context that sits well outside that pile. It aligns perfectly with our brains, which are hardwired to understand spatial relationships. Yet email, deeply rooted in computer science, requires us to predefine categories, assign labels, and navigate through rigid structures that do not naturally fit our cognitive processes. The science of managing digital stuff The science of managing digital stuff There’s a great book called The Science of Managing Our Digital Stuff by Ofer Bergman and Steve Whittaker, which delves into how our brains handle information. It highlights how traditional computer science overlooks our evolutionary predispositions. For instance, when managing digital documents, we often struggle with predefined folder structures and naming conventions. In contrast, our brains are adept at organizing physical items spontaneously based on their immediate importance. The Science of Managing Our Digital Stuff This discrepancy underscores the need for more intuitive, brain-friendly design in our computing environments. These thoughts are echoed by Cal Newport’s concept of the "hyperactive hive mind" workflow; another observation that perfectly encapsulates the chaotic, fragmented nature of modern work driven by poorly designed digital tools. Brains as computers, not computers as brains Our interaction with computers often feels disjointed because today’s desktop interfaces were not designed with human productivity as the primary focus; instead they emerged from the necessity to solve computer science problems, such as how to get multiple programs running simultaneously and interacting smoothly on a single screen. While this approach enhanced productivity by making computers more user-friendly, at a human-level they are still difficult to work with. From my perspective, the future of work hinges on integrating brain science into our computing environments. If we prioritized maximizing human capacity  from the start, our digital tools would look very different, enabling seamless collaboration and effectively supporting multiplayer modes of work. Take situational awareness as just one example. In digital environments it is crucial for both individual and business productivity. Modern software can notify us about new messages or changes in documents, but it doesn’t understand the context of why these updates matter to us, even if smart filters do their best to fulfill that role. This forces us to sift through notifications and decide what's relevant, often leading to information overload. According to a study by Stripe and Harris Poll, knowledge workers spend around 60% of their time on work about work, rather than the skilled labor they were hired to do. Our brains are evolutionarily wired to understand spatial relationships far better than abstract tags or folders, and so it is critical that we design tools that align with our instinctive ways of sorting and prioritizing. spend around 60% of their time on work about work, spend around 60% of their time on work about work, about work, Unlocking value in meaningful work What is the immediate value in redesigning our computing environments with brain science principles? It goes beyond incremental gains at task-level, and can unlock the potential of both the individual and the organization. For example, better alignment between human cognitive processes and digital tools can reduce wasted effort and minimize the compounding confusion of misdirected work. This results in more accurate first-pass work, accelerating project completion and creating a virtuous cycle of productivity. Too often I see teams pushing collectively in the wrong direction; efficiency and being inefficient. There’s significant loss of value attached to this too. If numbers are more your thing then consider that a report by the IDC estimated that - just for the Fortune 500 companies alone - the cost of being unproductive is over $30 billion annually. the cost of being unproductive is over $30 billion annually. the cost of being unproductive is over $30 billion annually. Brain science-based computing environments will fundamentally change how businesses operate. While traditional task-level improvements offer incremental gains, aligning human and computer understanding promises exponential productivity boosts. Proper alignment ensures that people are doing the right tasks, reducing wasted effort and creating a more efficient, innovative work environment. The future of work shouldn’t be about getting that “edge”, it should be about opening up a productivity chasm. There’s a massive, untapped opportunity in rethinking how we integrate brain science with computing. By focusing on these areas, we can unlock unprecedented productivity and creativity in our work environment, creating a more engaged, efficient, and innovative workforce, and achieving true operational excellence.

The is an opinion piece based on the author’s POV and does not necessarily reflect the views of HackerNoon.

Read My Stories

Too Long; Didn't Read

CTA: Download the FREE AI Productivity Shift report

You’ve Got Mail… Subject: Brain Science, Not Just Computer Science, is the Future of Work

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Untitled Story

Neuroscience: The Conceptual Failure of EU’s Human Brain Project and the US BRAIN Initiative

Particle Physics - Brain Science - A New Classical State of Matter - of the Human Mind

Sidelining Genetics - How'd Research Counter Mental Disorders?

10 Tips for Using Diagrams to Ace The System Design Interview

The 10 Computer Scientists That Made Computers Mainstream

Neuroscience: The Conceptual Failure of EU’s Human Brain Project and the US BRAIN Initiative

Particle Physics - Brain Science - A New Classical State of Matter - of the Human Mind

Sidelining Genetics - How'd Research Counter Mental Disorders?

10 Tips for Using Diagrams to Ace The System Design Interview

The 10 Computer Scientists That Made Computers Mainstream

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps