Reactions to the Digital Industrial Revolution: Musings on Machine Learning, SEO, and What Comes Next



I am wholly and completely at the behest of Google’s search algorithm. Like most people, I rely heavily on Google for access to factual information, news, entertainment, intellectual stimulation, and mindless inanity. As an SEO, however, I dedicate much of my time to decoding, deciphering, and optimizing for its cryptically defined and constantly evolving algorithm. In my day to day routine, I simply follow the algorithmic rules that I can comprehend, while on some other plane, Google’s deep learning algorithm quietly and rapidly becomes increasingly semantic, intuitive, emotionally receptive, and, ultimately, more human. In short, I find myself at the will of this powerful machine learning algorithm in all that I do.

This morning, I listened to the TED Radio Hour’s exploration of the Digital Industrial Revolution, wherein four qualified experts from different sectors spoke about machine learning, the way it shapes society, and the potential ramifications it may have on our collective future. And it got me thinking. So today, I am going to take a step back from the tactical, procedural side of SEO and speculate on the practice and existence of SEO in the light of Google’s exponentially evolving algorithm.

As an SEO, what does the rapidly evolving world of machine learning mean for me, our clients, and life as we know it?

Human Evolution vs Machine Learning Evolution

During the episode, host Guy Raz succinctly muses, “Right now, we’re at the beginning of a new machine age, where technology is developing at such a rapid pace, that it’s kind of hard to keep up with.”

As an SEO, I can’t help but think of my ongoing quest to optimize in the wake of Google’s constantly changing algorithm. But before we delve into the SEO ramifications of Guy’s assertion, I would like to ponder our place in a world increasingly dominated by machine learning algorithms.

Like much of the cultural discourse throughout the last century or so, Guy’s statement alludes to a prevalent us vs them, humans vs robots dichotomy. He evokes a long-tenured, collective fear: in an increasingly digital world, where do we, as humans, stand?

Human Beings

On another episode of the TED Radio Hour, Juan Enriquez notes the homo sapien currently processes more data in a single day than it used to in an entire lifetime. In addition to this massive surge in inputs, changes in our diets, improvements in our living conditions, and drastic environmental shifts have put us the precipice of evolving into an entirely new species altogether: homo evolutis. After 200,000 years of homo sapien life, we are mere generations from the next iteration human life. We’re actively adapting to massive global changes and the constant intake of information, but can we keep up with machine learning?

The Robot Brain

On the flipside, machine learning evolves at an exponential rate. TED contributor and Director of the MIT Initiative on the Digital Economy Erik Brynjolfsson posits “computers get better – faster – than anything ever.” He notes, “It starts with a small exponential trend. As you know, exponential trends double and double and double, and each time you can barely detect them when they’re small. And they start becoming overwhelming. Can we adapt fast enough?”

The Verdict

When you juxtapose these evolutionary timelines, the outlook seems grim for humankind’s ability to stay ahead of machine learning. I’m not saying that robots are poised to take over the world, but trends indicate that we should not expect to indefinitely remain the preeminent intellectual force on this planet. As fast as homo sapiens are evolving, data shows that computers will be smarter and more efficient than ourselves in most areas of life. What took us hundreds of thousands of years to accomplish, algorithms learn in mere decades.

Human-Robot Collaboration

While our culture conversations have conditioned us to think in a model that positions humans and machines as opposing forces, Brynjolfsson and General Electric Chief Economist Marco Annunziata suggest that a successful future hinges upon human-robot collaboration. When people leverage machine learning, they can be more efficient and productive than the human mind or a machine algorithm alone.

While Brynjolfsson and Annunziata cite the global benefits of human-robot collaboration in the financial and medical sectors, the leveraging of machine learning is the only way one can viably function as an SEO. At its core, the mere existence and practice of search engine optimization is a concession to the fact that Google’s algorithm is bigger, smarter, and better than ourselves. As individuals, we simply cannot comprehend, decipher, and decode its increasingly complex, semantic, and nuanced algorithm. And as your Blue Magneteers deftly identified, this leads to the proliferation of SEO myths, false truths, and fake news.

To navigate the murky seas of search engine optimization, we partner with algorithms more advanced than ourselves in hopes of complying completely with Google’s search algorithm. We take advantage the brilliant robot brains of Moz, SEMrush, and Advanced Web Rankings, leveraging their tools and algorithms to help hotels rank well in search.

Catching Up with Deep Learning

With the introduction of RankBrain in late 2015, Google made it clear that its search algorithm increasingly employs deep learning techniques and gets more intuitive, semantic, and human-minded every day – and it does this without any human inputs or interaction.

In the years-old quest to stay on the heels of each big algorithm update, SEOs obsess over the ramifications of each change. But with upwards of five hundred Moz-identified algorithm adjustments each year and the exponential nature of deep learning evolution, I can only speculate that Google’s search algorithm will begin to update, change, and grow in complexity at speeds that the SEO industry will have trouble tracking. Sure, brilliant human minds will build better tools and algorithms to map Google, but it is hard to imagine an individual human mind breaking this impossibly cryptic code.

Jeremy Howard, TED contributor, and CEO of the advanced machine learning company Enlitic, notes:

“Human performance grows at this gradual rate. But we now have a system – deep learning – that we know actually grows in capability exponentially. So currently, we see the things around us and we say, ‘computers are still pretty dumb’. But in five years time, computers will be off this chart. The better computers get at intellectual activities, the more they can build better computers to be better at intellectual capabilities.”

Even with human-robot collaboration, I find it hard to believe that the human mind will be able to keep up with Google’s deep learning algorithm. In the not-too-distant future, I expect Google will launch in a full-blown sprint into parts unknown, leaving us SEOs behind in its wake. So what do we do?

SEO in a RankBrain World

Currently, a lot of SEO hinges upon spoonfeeding Google the information we think it wants and making our websites easier to access for its bots. We strategically place keywords to tell Google what our pages are about. We optimize local listings to prove that our hotels exist and are open for business. We design the architecture of our sites so that Google can easily access the content we deem most important. Put simply, much of search engine optimization relies upon providing on a silver platter the inputs Google needs to confidently determine a website will satisfy searcher intent.

In his White Board Friday delve into SEO for Rank Brain, our pal and SEO hotshot Rand Fishkin posits, “you can’t do SEO for RankBrain specifically or not in the classic way that we’ve been trained to do SEO for a particular algorithm. This is kind of different.” Unlike Hummingbird or Penguin, “it’s not a classic algorithm that we do SEO against”.

In the not-too-distant future, I anticipate the fundamental nature of SEO will change. Currently, Rank Brain adjusts the algorithmic ranking factors for every query to most accurately satisfy searcher intent. As Google’s deep learning algorithm better understands human semantics, thought processes, patterns, and emotions, it will develop far more advanced ranking factors and become much more deft satisfying searcher intent. I speculate this will play out in a number of ways:

Bridging the Gap Between the Digital and Real World

Google will become exponentially better at understanding businesses, their clienteles, their strengths and weakness, and their unique selling points. Based on personal searching habits, GPS data, searcher behavior, and a bevy of other signals, I foresee Google effectively bridging the gap between the digital realm and the physical world.

Google strives to deliver the best, most accurate results and currently relies disproportionately heavily on digital signals. However, as it better understands the real world, it can more heavily weigh real world information in its search algorithm. By bridging this gap, Google will be able to serve results for hotel queries based on the quality of the hotel, the consistency of the guest experience, and other on-property factors.

Personalized Results

I also think we will see a great leap forward in personalized search results. As Google more efficiently tracks individuals’ personal, search, spending, and lifestyle habits, I imagine the way in which we search will fundamentally change. In the future, dynamic, niche content may become increasingly useful to satisfy searcher intent.

Reimagined SERP Formats

Five years from now, it is quite possible that the SERPs will hardly resemble the formats and layouts we see today. For years, Google has been tweaking, updating, and changing SERP formats to more efficiently, effectively, and accurately satisfy user intent. It’s getting to the point where it almost feels like Google is slowly phasing out the blue organic links for some types of searches; in this regard, Google increasingly acts more as a personal assistant than a web directory. For example, if I searched “When did Jerry Garcia die?”, and Google did not provide a knowledge graph answer, making me click through to a website, that would feel like a major inconvenience. Going to websites is so 2012.

I have a sneaking suspicion Google will make major format changes to create a more seamless user experience, wherein bouncing from website to website will feel obsolete. Over the last few months, Google has been integrating more and more pricing, pins, price comparison resources, and ways to book in its map results for hotel searches. You can book directly with a hotel, through the hotel’s official booking engine, without ever visiting their website or a 3rd party website. As Google’s search algorithm becomes exponentially complex, I expect to see more SERP integrations that satisfy searcher intent before the user ever considers clicking through to a website.

Security Against Growing Threats

Not all deep learning is good. As benign and helpful machine learning algorithms evolve at exponential rates, so do maliciously designed algorithms. News stories about hacking, identity theft, and devious digital doings occupy a growing amount of space in the public eye, and safe secure websites will become increasingly favored by Google as these malicious threats evolve.

So, Robots Are Going to Take Over the World…

As deep learning algorithms evolve at exponential rates, our role in society becomes increasingly unclear – and any half-fleshed probe into the nature of machine learning is bound to raise some loaded questions. The history of human life has been marked by the quest to understand things greater than ourselves, and the fact that we’ve created something more intelligent, efficient, and powerful than the human mind challenges many core beliefs we hold to be true.

Is humanity doomed? Are we on the precipice of an Augmented Age wherein human and robot minds coauthor the next iteration of our global society? In some ironic twist, will a machine learning algorithm completely map every corner of the human brain? Should I pack up, drop out, move to the desert, and embrace the natural world in all of its visceral, apathetic glory? Who’s to say?

If you found this remotely interesting (or if I’ve left you utterly confused), check out the Digital Industrial Revolution episode of NPR’s TED Radio Hour. It’s fun.

A Meeting of the Minds

Do machine learning’s endless possibilities fill you with hope that a better world is just around the corner? Have I reignited an existential dread that you had carefully suppressed into the void? We would love to muse, speculate, and theorize on the potential ramifications of machine learning! Get in touch with the Blue Magnet team for some heady and intellectually stimulating digital marketing chats!