"What are your favorite information streams?" My good friend Evan's question towards a distinguished
speaker was clearly an intriguing one, and it prompted me to ponder why the information other people
consume sparks my curiosity.
To a certain extent, the old adage of "you are what you eat" extends to the information we consume. Our
thinking and ideas and perspectives are shaped by the information that passes through our brain. Like
our diets, there needs to be intention behind choosing newsletters, podcasts, videos, and
different goals require different information streams, beyond quantity and quality, variety in topics,
authors, perspectives should also be considered.
This question speaks to a fundamental concept that I think is currently under-considered: personal
Although this term already exists, as a
naive player in the language world, I have not heard it applied
to the individual where we serve as the information system. My belief is that each person holds an
internal abstract space, constantly evolving with new information, processing information, updating
information and pruning information. The way we interact with it is through an abstract
visualization (which I will come back to later) which I consider another process integral in shaping
We read an article, process that information, think about the links between previous concepts that exist
in our information space, and a new representation of the ideas described in the article are created
within our personal information spaces. When we read a confounding article or better linkages through
further consumption or conversation, this representation shifts within our information space. This
process, I believe, dictates how we organize and interact with ideas; thus, it is extremely interesting
to consider the information that shapes other thinkers' information spaces.
How do we practically peer into others' information spaces? One day, highly sophisticated Brain-Computer
Interfaces like BrainNet (interview) will allow us to explore others'
information spaces. But the
traditional and current method is to read and listen. Great thinkers on Twitter share thoughts, and some
who are more committed to sharing information may have a personal blog or podcast. These are amazing ways
to interact with others' information spaces (in the language space). However, for the majority of people
who are inactive on Twitter and not actively publishing their thoughts, we almost have no way to glimpse into
their information space without conversations (which would be ideal, but everyone has limited time).
As a writer for NeurotechJP, I've
already come to the realization that writing
takes time, inevitably - publishing takes doubly as long. And personally, I'd love to peer into the minds
of those whose day job is not primarily writing: researchers, founders, athletes, etc.
If writing takes too much effort and time, what is the alternative? Going back to Evan's question of
information streams, others' information diet is still an incredibly rich resource with insights
into their information spaces.
Tools like Notion and Raindrop.io can serve as shareable public databases to collect, label, and
organize existing information; a low effort method to share and educate the audience through
information streams. Already, many use database tools as their "second brains," and for many, it
is likely a matter of a quick set up and simple organizational habits to maintain this content.
To a certain extent, we already do this through sharing sources. We share links to articles and podcasts,
but timing is also an important factor in consuming information. Irrelevant links now could be our
lifeline in two months, so having this information in a database can be critical.
In scientific research, new publications should present significant findings that contribution to the
existing literature. Similar to this peer-review filter, thinkers should consider how they are
contributing through their time; in the context of this article's theme of personal information spaces,
I want to highlight where current methods of content stand in relation to each other.
The first way to contribute is through proprietary content. This can be science, applications, novel
ideas, and to a certain extent, opinions. As highlighted above, although this type of content contributes
the most in sharing ideas from our personal information spaces, publishing takes considerable amounts of
The second is the one proposed above: organizing personal information streams in public databases.
Requiring less time and energy, this is a great way to peer into what new information shapes their
The third is secondary literature, or those that reorganize non-proprietary information. An example would
be Medium articles that explain how to implement algorithms in python. When you break these down, the
algorithm and the python implementation are not proprietary information: they exist in primary
literature and in the package's documentation (likely). Though it may present a novel dataset, the
individual components are not inherently novel. What is the contribution here?
When we interact with the information space, we often change "perspectives," which can be thought of as
changing the visualization of our information space. We may read an article that presents an idea in a
way that we may not fully comprehend, but when reading a different author's interpretation of it, things
could "click." You can think of reorganization as shifting the dimensions of the information space to
create a unique visualization of the topic covered. Thus, the Medium tutorials we read serve as
a way for different authors to share their visualization of the same concepts, which could help readers
realign their information space.
Although these articles, in my opinion, do not directly contribute to the overall information space, they
are integral in helping readers (and the author) reorganize their information spaces.
I envision a future in which we are more cognizant about information from a "personal" perspective. The individual
is not solely made unique by the forces of nature. We should harness data on an individual scale and
create systems and algorithms to enhance and share these unique discrepancies.
Recent advances in NLP are exciting, but I believe there should be a heavier emphasis on the individual
understanding of language. Although there is a ground truth for language in grammar and dictionaries,
language is understood at an individual level. The evolution of language does not happen first in dictionaries,
rather in people. If we can better capture our information space, we could one day see personal language models
that augment our reading, writing, and conversations.
In terms of personal information spaces, I do hope that busy people can make time to either publish or
organize their information streams so those aspiring to become great thinkers can be inspired to try
different information diets. I have personally started a Raindrop.io database with some of my favorite
reads and listens; looking to both help others get a glimpse into my naive mind but also hear from
others about the streams I am missing.