12 Ways to Get Smarter in One Infographic - Universal Mental Models
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12 Ways to Get Smarter in One Infographic

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Cognitive Bias Infographic

12 Ways to Get Smarter in One Infographic

View the high resolution version of today’s graphic by clicking here.

The level of a person’s raw intelligence, as measured by aptitude tests such as IQ scores, is generally stable for most people during the course of their adulthood.

While it’s true that there are things you can do to fine tune your natural capabilities, such as doing brain exercises, solving puzzles, and getting optimal sleep—the amount of raw brainpower you have is difficult to increase in any meaningful or permanent way.

For those of us who constantly strive to be high-performers in our fields, this seems like bad news. If we can’t increase our processing power, then how can we solve life’s bigger problems as we move up the ladder?

The Key: Mental Models

The good news is that while raw cognitive abilities matter, it’s how you use and harness those abilities that really makes the difference.

The world’s most successful people, from Ray Dalio to Warren Buffett, are not necessarily leagues above the rest of us in raw intelligence—instead, they simply develop and learn to apply better mental models of how the world works, and they use these principles to filter their thoughts, decisions, strategies, and execution.

This infographic comes from best-selling author and entrepreneur Michael Simmons, who has collected over 650 mental models through his work. The infographic, in a similar style to one we previously published on cognitive biases, synthesizes these models down to the most useful and universal mental models that people should learn to master first.

Concepts such as the 80/20 rule (Pareto’s principle), compound interest, and network building are summarized in the visualization, and their major components are broken down further within the circle.

Mental Model Examples

Example #1: Pareto’s Principle (80/20 Rule for Prioritization)

In a recent Medium post by Simmons, he highlights a well-known mental model that is the perfect bread crumb to start with.

The 80/20 rule (Pareto’s principle) is named after Italian economist Vilfredo Pareto, who was likely the first person to note the 80/20 connection in an 1896 paper.

In short, it shows that 20% of inputs (work, time, effort) often leads to 80% of outputs (performance, sales, revenue, etc.), creating an extremely vivid mental framework for making prioritization decisions.

80-20 law Pareto's principle

The 80/20 rule represents a power law distribution that has been empirically shown to exist throughout nature, and it also has huge implications on business.

If you focus your effort on these 20% of tasks first, and get the most out of them, you will be able to drive results much more efficiently than wasting time on the 80% “long-tail” shown below.

Power law distribution

Example #2: Metcalfe’s Law (Network Building)

Metcalfe’s Law is one of network effects, stating that a network’s value is proportional to the square of the number of nodes in the network.

From a mental model perspective, this is a useful way to understand how certain types of technology-driven businesses derive value.

If you have a smart grid that is only connected to one power source, that’s alright—but one connected to many different energy sources and potential consumers is much more useful for everyone on the grid. Each additional node provides value for the rest of the connections.

Metcalfe's Law illustrated

This mental model can be applied outside of strict technology or business terms as well.

For example, if you build a personal network of connections, each additional relationship can provide more value to the other people in your network. It’s the same principle that Harvard or other prestigious universities operate on: the more value a student can get from the alumni network, the higher price they can charge for tuition.

It’s hard to compete with a fully formed network at scale, as they create massive economic moats for the owner. Modern social networks and messaging apps like Facebook, Instagram, LinkedIn, TikTok, WhatsApp, and Snapchat all operate with this in mind.

The Power of Mental Models

These are just two examples of how powerful mental models can be effective in making you think clearer and work smarter.

If you want to be a top performer, it’s worth looking into other mental models out there as well. They can help you better frame reality, so that you can harness your intelligence and effort in the most effective way possible—and it’ll allow you to deliver results along the way.

This post was first published in 2018. We have since updated it, adding in new content for 2021.

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Misc

A Logarithmic Map of the Entire Observable Universe

Scientists believe we’ve only discovered about 5% of the universe. Here’s a map of what we’ve found so far, visualized using a log scale.

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A Logarithmic Map of the Entire Observable Universe

Among the scientific community, it’s widely believed that so far humans have only discovered about 5% of the universe.

Yet, despite knowing about just a fraction of what’s out there, we’ve still managed to discover galaxies billions of light-years away from Earth.

This graphic by Pablo Carlos Budassi provides a logarithmic map of the entire known universe, using data by researchers at Princeton University and updated as of May 2022.

How Does the Map Work?

Before diving in, it’s worth touching on a few key details about the map.

First off, it’s important to note that the celestial objects shown on this map are not shown to scale. If it was made to scale with sizes relative to how we see them from Earth, nearly all of the objects would be miniscule dots (except the Moon, the Sun, and some nebulae and galaxies).

Secondly, each object’s distance from the Earth is measured on a logarithmic scale, which increases exponentially, in order to fit in all the data.

Within our Solar System, the map’s scale spans astronomical units (AU), roughly the distance from the Earth to the Sun. Beyond, it grows to measure millions of parsecs, with each one of those equal to 3.26 light-years, or 206,000 AU.

Exploring the Map

The map highlights a number of different celestial objects, including:

  • The Solar System
  • Comets and asteroids
  • Star systems and clusters
  • Nebulae
  • Galaxies, including the Milky Way
  • Galaxy clusters
  • Cosmic microwave background—radiation leftover from the Big Bang

Featured are some recently discovered objects, such as the most distant known galaxy to date, HD1. Scientists believe this newly-discovered galaxy was formed just ​​330 million years after the Big Bang, or roughly 8.4 billion years before Earth.

It also highlights some newly deployed spacecraft, including the James Webb Space Telescope (JWST), which is NASA’s latest infrared telescope, and the Tiangong Space Station, which was made by China and launched in April 2021.

Why is it called the “Observable” Universe?

Humanity has been interested in space for thousands of years, and many scientists and researchers have dedicated their lives to furthering our collective knowledge about space and the universe.

Most people are familiar with Albert Einstein and his theory of relativity, which became a cornerstone of both physics and astronomy. Another well-known scientist was Edwin Hubble, whose findings of galaxies moving away from Earth is considered to be the first observation of the universe expanding.

But the massive logarithmic map above, and any observations from Earth or probes in space, are limited in nature. The universe is currently dated to be around 13.8 billion years old, and nothing in the universe can travel faster than the speed of light.

When accounting for the expansion of the universe and observed objects moving away from us, that means that the farthest we can “see” is currently calculated at around 47.7 billion light-years. And since light takes time to travel, much of what we’re observing actually happened many millions of years ago.

But our understanding of the universe is evolving constantly with new discoveries. What will we discover next?

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Technology

33 Problems With Media in One Chart

In this infographic, we catalog 33 problems with the social and mass media ecosystem.

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problems with media

33 Problems With Media in One Chart

One of the hallmarks of democratic society is a healthy, free-flowing media ecosystem.

In times past, that media ecosystem would include various mass media outlets, from newspapers to cable TV networks. Today, the internet and social media platforms have greatly expanded the scope and reach of communication within society.

Of course, journalism plays a key role within that ecosystem. High quality journalism and the unprecedented transparency of social media keeps power structures in check—and sometimes, these forces can drive genuine societal change. Reporters bring us news from the front lines of conflict, and uncover hard truths through investigative journalism.

That said, these positive impacts are sometimes overshadowed by harmful practices and negative externalities occurring in the media ecosystem.

The graphic above is an attempt to catalog problems within the media ecosystem as a basis for discussion. Many of the problems are easy to understand once they’re identified. However, in some cases, there is an interplay between these issues that is worth digging into. Below are a few of those instances.

Editor’s note: For a full list of sources, please go to the end of this article. If we missed a problem, let us know!

Explicit Bias vs. Implicit Bias

Broadly speaking, bias in media breaks down into two types: explicit and implicit.

Publishers with explicit biases will overtly dictate the types of stories that are covered in their publications and control the framing of those stories. They usually have a political or ideological leaning, and these outlets will use narrative fallacies or false balance in an effort to push their own agenda.

Unintentional filtering or skewing of information is referred to as implicit bias, and this can manifest in a few different ways. For example, a publication may turn a blind eye to a topic or issue because it would paint an advertiser in a bad light. These are called no fly zones, and given the financial struggles of the news industry, these no fly zones are becoming increasingly treacherous territory.

Misinformation vs. Disinformation

Both of these terms imply that information being shared is not factually sound. The key difference is that misinformation is unintentional, and disinformation is deliberately created to deceive people.

Fake news stories, and concepts like deepfakes, fall into the latter category. We broke down the entire spectrum of fake news and how to spot it, in a previous infographic.

Simplify, Simplify

Mass media and social feeds are the ultimate Darwinistic scenario for ideas.

Through social media, stories are shared widely by many participants, and the most compelling framing usually wins out. More often than not, it’s the pithy, provocative posts that spread the furthest. This process strips context away from an idea, potentially warping its meaning.

Video clips shared on social platforms are a prime example of context stripping in action. An (often shocking) event occurs, and it generates a massive amount of discussion despite the complete lack of context.

This unintentionally encourages viewers to stereotype the persons in the video and bring our own preconceived ideas to the table to help fill in the gaps.

Members of the media are also looking for punchy story angles to capture attention and prove the point they’re making in an article. This can lead to cherrypicking facts and ideas. Cherrypicking is especially problematic because the facts are often correct, so they make sense at face value, however, they lack important context.

Simplified models of the world make for compelling narratives, like good-vs-evil, but situations are often far more complex than what meets the eye.

The News Media Squeeze

It’s no secret that journalism is facing lean times. Newsrooms are operating with much smaller teams and budgets, and one result is ‘churnalism’. This term refers to the practice of publishing articles directly from wire services and public relations releases.

Churnalism not only replaces more rigorous forms of reporting—but also acts as an avenue for advertising and propaganda that is harder to distinguish from the news.

The increased sense of urgency to drive revenue is causing other problems as well. High-quality content is increasingly being hidden behind paywalls.

The end result is a two-tiered system, with subscribers receiving thoughtful, high-quality news, and everyone else accessing shallow or sensationalized content. That everyone else isn’t just people with lower incomes, it also largely includes younger people. The average age of today’s paid news subscriber is 50 years old, raising questions about the future of the subscription business model.

For outlets that rely on advertising, desperate times have called for desperate measures. User experience has taken a backseat to ad impressions, with ad clutter (e.g. auto-play videos, pop-ups, and prompts) interrupting content at every turn. Meanwhile, in the background, third-party trackers are still watching your every digital move, despite all the privacy opt-in prompts.

How Can We Fix the Problems with Media?

With great influence comes great responsibility. There is no easy fix to the issues that plague news and social media. But the first step is identifying these issues, and talking about them.

The more media literate we collectively become, the better equipped we will be to reform these broken systems, and push for accuracy and transparency in the communication channels that bind society together.

Sources and further reading:

Veils of Distortion: How the News Media Warps our Minds by John Zada
Hate Inc. by Matt Taibbi
Manufacturing Consent by Edward S. Herman and Noam Chomsky
The Truth Matters: A Citizen’s Guide to Separating Facts from Lies and Stopping Fake News in its Tracks by Bruce Bartlett
Active Measures: The Secret History of Disinformation and Political Warfare by Thomas Rid
The Twittering Machine by Richard Seymour
After the Fact by Nathan Bomey
Ten Arguments for Deleting Your Social Media Accounts Right Now by Jaron Lanier
Zucked by Roger McNamee
Antisocial: Online Extremists, Techno-Utopians, and the Highjacking of the American Conversation by Andrew Marantz
Social media is broken by Sara Brown
The U.S. Media’s Problems Are Much Bigger than Fake News and Filter Bubbles by Bharat N. Anand
What’s Wrong With the News? by FAIR
Is the Media Doomed? by Politico
The Implied Truth Effect by Gordon Pennycook, Adam Bear, Evan T. Collins, David G. Rand

 

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