The End of the Scientific Method

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The (Old) Scientific Method

Science as we currently understand it is ready for a makeover.

Listened to an awesome podcast today by Economist Radio’s Charles Babbage, with the same title as this post, and the punchline is a rather jarring one.

Especially if you are some empirical traditionalist, or high school science teacher.

The advent of artificial intelligence just may upend the entire paradigm of knowledge gathering as we know it.

Kind of like how the printing press changed what it meant to write a book, or how the internet radically altered how we consume and share information.

That’s a Big Claim Buddy

Okay, granted.

But before we get there, what exactly is science?

Simply a set of rules?

Or some methodology we’ve adopted?

As explained in the podcast (btw, you should really give it a listen here) it as the process of accumulating a set of agreed upon facts, from whence we can produce a theory.

A process began by Galileo, and systemized by Francis Bacon (also known as the ‘father of empiricism’).

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The always cool — Mr. Neil DeGrasse Tyson

“Science is a way of querying nature using methods and tools to establish something that is objectively true…”

– Neil DeGrasse Tyson

But, in order to get to the meat of what we collectively know, we have to come up with a system of knowing.

This being; hypothesis, experiment, observation, and theory.

Alas, we have the oft revered scientific method.

But really and truly, the scientific method is just one tool in the grander box we have for discovering universal truths in a way that is reproducible.

Though, not the most efficient. Most religions simply say “Hey you. Here’s truth. Believe it. Have faith.”

Language can be better, as it distills and disperses the notions inherent in a population. Making it possible for us to create a sort of marketplace of ideas.

Though, the limitations are quite obvious.

For one, our minds are not computers. We make prejudgments about our world all the time.

Thus, even scientists enter their sanctified experiment rooms rife with preconceptions and biases.

It’s not wrong, per se.

Just human.

What I’m trying to say, is that It’s impossible, even for the most pragmatic and objective of us, to rid ones self of the need to understand what is not yet understood.

Which inherently leads to biases popping up, whether latent or explicit. These biases then can profoundly alter the direction of whatever experiments you decide to conduct.

This is the first ‘advantage’ of a supercomputer running the experiments for us, because computers see inputs and outputs as they are — unrelated.

That is, until they become so.

The second limitation we have as carbon-based vehicles, is that of time.

We can only run so many experiments between nine to five.

And the beauty of a computer, is that it can run ad nauseum, and at a rate that far outpaces even the most diligent researcher.

One example of this, can be found in a research startup called Lab Genius, where machine learning is being used to help spot patterns at a rate that we humans could never achieve.

These great people, headed by Dr. James Fields, are doing some groundbreaking work in the field of biology where they allow computer algorithms to form hypotheses (such as, which drug might work in a specific illness) and then, allow AI systems to test them.

This turns out to be a much better way of discovering new information.

Not by just ten or fifty times… but by tens of thousands of times better.

One such experiment searches through a log of over one billion DNA sequences in order to find protein designs which are deemed as ‘high performers’

in a period of 27 days

Less than a month, for what would probably take a human multiple lifetimes.

Fact is, if we want to truly arrive at a firm conclusion, and not just a glorified guess propped up by a small group of inefficient humans, it is probably best that we allow the AI to do what the AI does… think fast.

But don’t worry, it is not this type of ‘thinking’ that we do best anyway.

Humans like to think different.

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The famous words of founder Steve Jobs.

You are expressly more adept than any computer thats ever been constructed (or that will ever be constructed) at seeing the bigger picture.

Not with your eyes. But with your soul.

Bear with me.

We have this phenomenal ability to connect disparate parts and create meaning from seemingly random data points and bits of information.

It is our critical thought paired with this unique sense of creativity that separate us from machines.

In this, we have a daunting challenge ahead of us.

With knowledge (in the sense of accumulated data) becoming more ubiquitous, we’re freed up to find true significance, while pursuing action steps that push the entire race forward.

No more living to work.

Soon, we will work in ways that will allow us to better live.

And science will play a critical role in that evolution.

But, doesn’t it already?

Not really.

Science often takes a back seat to political pressures nowadays.

Also, it tends to answer the questions of “what” +“when”, rather than the much more difficult ones of “how” +“why”.

This is why corporations love running ‘experiments’ on their products.

Or why scientists are often pulled into fields of study that have the highest returns on investment. The answers are more black and white.

So it makes sense, to study what’s approachable. That tends to be where the flow of money is; and nobody likes to conduct research with intermittent gaps in funding.

A good basic understanding of politics, in my estimation, is simply… who gets what, and how they get it.

Information is a huge part of how this process plays out, because frankly, if you know more than the next person, you can make better decisions.

This creates a divide between the haves, and the have-nots.

A divide that continues to expand as those with information continue to make increasingly informed decisions with which the rest of us couldn’t even begin to make sense of.

But in the future, that will no longer be a problem.

Information will be democratized.

And then… the search for real stuff can begin.

Stuff like wisdom, and insight.

When the race for knowledge is over, the race for imagination can begin.

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The Great Albert Einstein — Just riding a bicycle.

“Imagination is more important than knowledge”

– Albert Einstein

We are getting VERY close to knowing everything there is to know. At least, with the what and when questions. Objectives measures of our physical reality have become increasingly calibrated, and the questions that remain lie within the domain of why.

The next paradigm of human evolution will be in our ability to take the vast swaths of knowledge and use it both productively and imaginatively, making well-informed decisions in a way that no mere computer could conceive.

Thus ushering in a new generation of thinkers, leaders, and problems solvers who will help fix our ailing world.


Personally, I like learning about outer space.

But I can’t.

Well I can… but, not that much.

All the crucial stuff that’s of actual import is hoarded by a cohort of government agencies, academic researchers, and private organizations. The cutting edge of what’s known is not yet in the public domain.

But that’s all about to change.

The stuff of quasars and black holes is only vagely understood by even the most proficient minds. It’s almost time to open the floodgates.

It is when information becomes so ubiquitous that the 1% can no longer make sense of the varying inputs — that we will arrive at a curious position.

Science 2.0

And that is where the fun starts.

So, science isn’t ‘done’.

In fact, it’s just getting started.

Only, in my estimation; guess and check season is just about over.

Humanity is getting ready to graduate to something realer.

And I for one, am here for it.

Happy searching.

Galileo and his telescope
Galileo

Published by Toso

I like big ideas and I cannot lie.

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