Computer science has a technical barrier to entry. For newcomers, it can be an extremely daunting community, with ever-changing trends, complex jargon, and a vast ocean of resources that require training and practice.
That’s not even taking into account the complexities of computer science. It’s true that not every developer has to understand the underlying workings behind information technology, nor have a deep knowledge of math. But we can’t deny that it’s extremely helpful.
Technical barriers themselves aren’t an issue. Just look at the 20th century and how much it was accomplished in spite of the extremely high barriers of entry of science and engineering. And yet, there is cause for concern.
The problem we are facing with today’s acceleration in tech adoption is that new technologies are being deployed faster than ever before and we are having a hard time keeping up.
How to outrun technology?
Accelerated growth is something that might sound great in theory but that can have devastating consequences for infrastructure in practice.
The more we invest and integrate technology into our systems, the more likely we are to outgrow our IT support model. This is happening worldwide, and at this pace, job demands are outgrowing the candidate pool.
Tech skills are in short supply in every field from software developers to project managers. This, in turn, is driving the wages up, which is making the competition for small scale businesses even harder.
Ironically, it seems like the best way to “outrun” the demand for talented tech specialists is to rely on technology. More specifically, to use technology to create more accessible solutions for our companies. For example, no-code solutions.
The era of citizen coders
No-code solutions are a subset of a bigger movement towards what’s called “citizen coders”. It’s the idea that we have to create venues for people outside the tech field to develop software, or to implement solutions that traditionally would require coding.
Imagine that instead of writing a program, you sit down with a graphical interface and some simple scripting tools. By interacting with the interface like how one interacts with an app, you can create software that’s just as functional as one created by a senior developer.
Perhaps 2 of the biggest examples of no coding solutions are the game engines Unreal and Unity. Both have been widely used by upstarts and young talents to create animations and games with very little to no coding.
I’m using these examples specifically because both engines can be further customized with a little programming knowledge (C++ for Unreal and C# for Unity). With this kind of solution, you can have a citizen developer creating the basis of a project with a software developer at their side optimizing the product.
The possibilities for no coding solutions are nothing short of extraordinary. End users can work in tandem with software developers to create their dream applications. For small-scale projects, most of the work is done with no code. The developer just chimes in to help with debugging or with customization.
AI enhancing No-Code
No-code solutions have been around for quite a while, but the implementation of AIs to bolster these products is something that we are still exploring. Predictive tools that dynamically adapt to the user’s inputs are exactly what we need.
Critics of no-code solutions often point to the fact that citizen developers are bound to the paradigm of the application they are using. Since you are basically choosing from a list of functions and linking them together, there is a limit on flexibility.
But things are changing, thanks to AI. Much like how GitHub’s AI offers suggestions and code auto-completion, AI-powered No-code solutions offer the user options based on their choices. If you are building a dashboard to track KPIs, the AI can search for similar dashboards and recommend specific modules.
The fact that No-Code products can learn from their user inputs is already amazing enough. But there is an aspect we have yet to consider. How can we use a No-Code solution to create AIs?
First, what is No-Code AI? It’s a code-free system that empowers businesses using AI to perform activities such as data analysis, classification, and predictive models. No-code AI tends to be custom-developed and implemented into the technology stack so it can be used right away.
The interface varies from solution to solution, but in all cases, no-code AI is designed from the ground up to be as usable as possible. Think of it as a way to democratize AI so it can reach a wider audience.
Within the last 5 years, the field of AI has grown by an astounding 270%. But unfortunately, most surveyed companies agree that it’s a difficult technology that can be troubling to integrate into their systems.
What No-code AI offers is a simpler approach that integrates easily, is user-friendly, speeds up processes, and offers a low-cost solution in contrast to custom software or having a dedicated AI team.
Now picture this, you build an AI (Let’s call it HAL) with an AI-based no-code solution. HAL is capable of measuring its reliability and “learning from its mistakes”. This information, in turn, can be used by the original AI to see how a specific implementation behaves in certain contexts.
In other words, our AI building no-code solution is learning from the outcome of one of its creations, which in turn means that it will make better predictions down the line and offer better suggestions to the user.
While it’s not sophisticated enough to call it software that writes itself (after all, human input is still an integral part of the process), this kind of cycle is filled with possibilities.
Before You Jump In
Sounds exciting right? Should you adopt a No-code AI solution, then? Well, that depends, Like any business decision, it should be made by first analyzing your situation carefully and then making a choice based on data.
No-code solutions are amazing. Of course, they can never replace human ingenuity. AI is not going to take the job of software developer anytime soon. Also, since No-code products often go for a one-size-fits-all approach, they can never be as adaptable as a custom-built solution.
Having said that, the fact that we are at a point in time where people without coding skills can shape the world of Artificial Intelligence seems like something straight out of a sci-fi novel.