Democratization Is Leveling the Technology Playing Field

More powerful and less expesnive technology is opening up avenues of opportunity.

Access to technology for all and the availability of the most complex of innovations and solutions for individuals and small business is the promise of democratization of technology. A social phenomenon, democratization is the process by which advances in technology gradually make its benefits and its ability to lessen burdens accessible to all.


Imagine, for example, accessing very complex networking technology or the most high-level machine learning. Think about being able to leverage Industry 4.0 items as a low- or mid-level entrepreneur and having the most complex technology open up at a level that is accessible to those individuals and companies that are just starting out.


In this article we will look at four areas of technology democratization: data and analytics, development, design, and general knowledge, what the affects will be in those areas and how individuals and organizations can participate.


Democratization of Data


For data and analytics, which are a rapidly growing segment of information technology (IT), market-based access to data and algorithms will lower entry barriers and lead to an explosion in new applications of AI.


Since data is what fuels the growth of AI, companies that previously had all the data, such as Google or Microsoft, are now required to show it to you, to allow you to access it in the same manner as they do. As recently as 2015, only large companies like Google, Amazon and Apple had access to the massive data and computing resources needed to train and launch sophisticated AI algorithms.


Not all that long ago, mall startups and individuals simply didn't have access and were effectively blocked out of the market. The democratization of data and analytics gives individuals and startups a chance to get their ideas off the ground and prove their concepts before raising the funds needed to scale.


Access to data, however, is only one way in which data and analytics are being democratized. The other areas of the "level set" of the playing field will bring rise to the Google-type companies of the future.


Democratization of Development


More powerful and less expesnive technology is opening up avenues of opportunity.

The shift toward democratization of development can be seen in real time, like the open source, deep-learning software frameworks that are coming to power. A major issue in the wide-scale adoption of open source development is that there are many different software frameworks are out there. Big companies are open sourcing their code and relying on the frameworks to drive innovation, while trying to push for some standardization. This allows development's many little guy to keep pace with the big dogs.


Just as the cost of developing mobile apps fell dramatically as iOS and Android emerged as the two dominant ecosystems, so too will all development become more accessible as tools and platforms standardize around a few frameworks.


Some of the notable open source frameworks include Google's TensorFlow, Amazon's MXNet and Facebook's Torch. The tools themselves will level-set, and developer-friendly tools will emerge.


The final step to democratization of development will be the development of simple drag-and-drop frameworks accessible to those without doctorate degrees or deep data science training. Microsoft Azure ML Studio offers access to many sophisticated development frameworks through a simple graphical UI.


Amazon and Google have rolled out similar software on their cloud platforms as well. In order to let the little guy in, you must allow small players to purchase anything and everything they need. It also needs to be affordable, along with it being accessible.


A marketplace for development algorithms and datasets will need to be put in place. Not only do we have the on-demand infrastructure needed to build and run these large-scale development tools, we even have marketplaces for the algorithms themselves.


Need an algorithm for facial recognition in images, or to add color to black and white photographs? Marketplaces like Algorithmia let you download the algorithm of choice. Even better, websites like Kaggle provide the massive datasets one needs to further refine and train these algorithms.


Democratization of Design


More powerful and less expesnive technology is opening up avenues of opportunity.

For design, one does not need to look any further than Moore's law. Intel cofounder Gordon Moore's famous observation (now 55 years in the rearview mirror) that computer technology advances even as the cost of that technology drops has held true for decades, with computers steadily becoming both more powerful and cheaper to produce (and own).


Individuals and smaller companies involved in the world of video production could be forgiven for adhering to the conventional wisdom that it still necessitates custom hardware (both in computing power and cameras).


Slower design and slower processing, however, continue to give way to faster design and faster processing. At the present moment in design and general technology, I would argue that general purpose computer processing power is reaching a point where it can adequately handle the tasks laid by any higher algorithm.


For the video production crowd, it's important to keep in mind that the human eye can't distinguish any measurable improvement beyond 4K, and can scarcely tell the difference between 1080p and 4K. The point here is that the amount of data required for live video processing won't grow at an exponential rate anymore, because it is already at the upper bound of what humans can differentiate.


Democratization of General Knowledge


Computer processing power, on the other hand, will continue to soar. For general purposes of computation, like DNA sequencing and 23AndMe types of criminal tracking, the processing power will be more than adequate.


This means it will get easier and easier for common devices like your phone to handle HD video processing tasks. Another challenge with live video is an internet network's ability to transfer the video data from its origin to your device — meaning that it can't effectively livestream a 1080p video at a decent frame rate to your computer. This is sometimes more of a constraint than the video processing power of a computer, or your eye's ability to process images.


Girl with headphones watching laptop on hillside

What does this all mean? In one sentence: The rapidly improving quality of mobile wireless networks by moving to 5G and IPv6. The insane quality of the camera in your pocket and the processing power of your computers (phones, tablets, laptops) means that very soon individuals and small start-up companies will be able to produce a live video events at the same quality as you see on television. You will be able to process any sort of dataset, just from the sheer power of the computer itself.


The Future


The next key shift will be from technical constraints to the constraints of human desire. And if there is any doubt about human desire to produce live video, you can take a look at the enormous quantities of content pouring into Facebook Live, YouTube Live, TikTok, Instagram, Twitch, Periscope, etc. Look at the data sets that the next big content start-up is going to have to process.


We are on the cusp of democratization across a broad range of technology areas. The time is ripe for smaller companies and individuals alike to take advantage of these unprecedented times.


Would you like more insight into the history of hacking? Check out Calvin's other articles about historical hackery:
About the Author
Nathan Kimpel is a seasoned information technology and operations executive.

Nathan Kimpel is a seasoned information technology and operations executive with a diverse background in all areas of company functionality, and a keen focus on all aspects of IT operations and security. Over his 20 years in the industry, he has held every job in IT and currently serves as a Project Manager in the St. Louis (Missouri) area, overseeing 50-plus projects. He has years of success driving multi-million dollar improvements in technology, products and teams. His wide range of skills include finance, ERP and CRM systems. Certifications include PMP, CISSP, CEH, ITIL and Microsoft.