I’m back bitches. I’ve spent the last several months in a deep writer’s block, and even though I’m still suffering from a lack of desire to write, I’m actively trying to ideate and get back into the flow. In this post, I’m going to be discussing how society operates according to both the Pareto Distribution and Price’s Law, and how AI will only serve to magnify their effects; for the good and the bad. And if you’ve never heard of the Pareto Distribution or Price’s Law, don’t fret as I didn’t know what these things were until recently either. And hopefully after reading this entire article, your opinion on my writing has not degraded in the slightest as I’ve been out of practice for over 100 days.

Pareto Distribution

You’ve probably heard of the “80/20 rule.” And if you haven’t, then you’ve probably been living under a rock (I joke of course). The Pareto Distribution is a phenomenon observed in nature which suggests that, in many events, roughly 80% of the effects come from 20% of the causes. Here are some examples observed in our world:

• Wealth Distribution: Approximately 20% of the world’s population controls 80% of the wealth (United Nations Development Program [1992])
• Business Sales: In many businesses, 20% of products or customers account for 80% of total sales
• Software Bugs: About 20% of the code errors cause 80% of the software crashes or issues
• Crime: 20% of criminals commit 80% of crimes
• Health and Social Outcomes: In 2009, the Agency for Healthcare Research and Quality said 20% of patients incurred 80% of healthcare expenses due to chronic conditions

So you might be asking yourself, why does this matter and why should I care? Well for one, it shows that society operates at the poles and extremes of the distribution. If 20% of the world’s population controls the majority of the wealth, it’s no wonder taxing the rich has become such a popular concept and is now a key component in the left’s argument for economic equality. Another reason why it matters is that the observation of the Pareto Distribution allows us to allocate resources accordingly and improve efficiencies by providing a framework of what to focus on. If a small proportion of inputs leads to the majority of outcomes, then we can prioritize and focus on what matters rather than what doesn’t. This leads to a problem of “equality” in our society where the outcomes might never be even and, frankly, that’s not what we should be striving for (we should be seeking equality of opportunity, NOT equality of outcome; the latter has shown to not work).

So how does AI relate to this? Well, because the Pareto Distribution has been observed in nature for so long and is well-established, it begs the question if there’s anyway to change it and what that would look like. If AI is simply operating on data that has already occurred, trained on the inevitable 80/20 rule, then the Pareto Distribution will continue to be observed forever, which could potentially lead to increased polarization between the poor and the rich, the sick and the healthy, and other disparities, leading to social unrest. In other words, as AI becomes a normal part of everyone’s lives, it could potentially drive us further apart.

Price’s Law

Price’s Law describes a different, but related phenomenon to the Pareto Distribution, where the square root of the number of people in a domain does half of the work. For example, if you have a group of 100 people, 10 of them (the square root of 100) will produce half of the output, whether it’s in terms of contributions, results, or productivity. Here are some examples:

• Academic Publishing: In academia, a small number of researchers contribute to a large proportion of the publications and citations. According to Price’s Law, if there are 100 researchers in a field, about 10 of them will be responsible for 50% of all publications
• Software Development: Within a software company or project, a small group of developers often contributes the majority of the code or key features. For example, in a project with 100 contributors, 10 would typically be responsible for half of the contributions, aligning with critical developments or innovations
• Sales Performance: In many sales organizations, a small subset of the sales force generates a large portion of the sales. If a company has 100 salespeople, Price’s Law would predict that about 10 of them are responsible for achieving 50% of the sales.

As you can see, Price’s Law is related in some sense to the Pareto Distribution, but focuses primarily on contributions and productivity. It can also be said that Price’s Law proves that a small number of inputs creates the majority of the outcomes. So here comes the age old question, why the flying f*ck should I care about Price’s Law, and where does AI play into this? Here are some reasons:

• Concentration of Expertise: In the AI field, Price’s Law can result in a concentration of knowledge and expertise within a small group of researchers and developers where this elite group drives most of the innovation and breakthroughs. While this accelerates progress, it also risks creating a knowledge gap where the majority of the field struggles to keep up with the leading edge, potentially widening the divide between the top AI contributors and the rest.
• Economic Disparities: The advancements in AI, driven by a few, can lead to significant economic benefits for those directly involved or those who can quickly adapt and integrate these technologies. Companies and individuals who harness AI effectively can achieve disproportionate gains in productivity and profits, potentially exacerbating wealth and income inequalities. Smaller entities or those late to adopt may find it increasingly difficult to compete.
• Influence on Media and Information: AI technologies, particularly in areas like algorithmic content recommendation and automated news generation, are concentrated in the hands of a few major platforms. These entities have significant control over the information landscape, potentially amplifying biases, misinformation, or the visibility of certain viewpoints over others, influencing public opinion and democracy itself.

Conclusion

The observation of the Pareto Distribution and the effects of Price’s Law are undeniable axioms that exist in the real world and lead to the magnification of extreme outcomes. As progressive tendencies in society seek to unify us all through equality of outcome, there remains a widening gap between different groups, forcing individuals to choose an extreme perspective to support. For example, the political environment in the United States is becoming increasingly polarized and the mentality of “with us or against us” is as strong as ever. This seems to have peaked during the Trump vs. Biden electoral race, as people tended to vote AGAINST someone rather than FOR someone.

The Pareto Distribution and the effects of Price’s Law will only serve to enhance societal disparities when combined with AI. If a small portion of academically published articles are written by the same professionals, and AI is trained on academic data, then the small proportion of academic professionals will continue to represent a larger and larger portion of published information, leading to an echo chamber of the same narrative, not allowing external thougth to penetrate. The same can be said for media powerhouses like CNN, FOX, and others where their content has become increasingly focused on one extreme viewpoint (right vs. left respectfully), and strayed away from bipartisan and middle ground, unbiased information. This exaggeration at the poles of the distribution, combined with AI that learns from what you give it to make future predictions, will only continue to enclose us in an echo chamber of information we WANT to hear rather than challenging us with what we SHOULD hear.

Now that you’re aware of what the Pareto Distribution and Price’s Law are, it’ll be hard to look at the world the same, without wondering who the 20% actually is.