Do AI, Automation and the No-Code Movement Threaten Our Jobs?
Written by Nikos Vaggalis   
Monday, 01 April 2019

The rise of the no-code movement has made tools accessible to a mass market with which end products can be produced which would normally require the involvement of a specialized professional. Is AI the last ingredient in phasing out the specialist?


Take for example Weebly or Wix. These allow store owners to create their own websites by just dragging and dropping components from within the platform's easy-to-use enhanced IDE.This is certainly productive, brings the cost down, but at the same time has the software developer losing clients. 

Then again, with the rise of AI the programmer's obsolesce becomes even more plausible.For example, tools like Shots.Ai allow anyone to upload a screenshot of their design and let Shots render it into a Bootstrapped, Responsive, HTML/CSS/JSX-ready website. What does that say about the future of front-end development? Even when you feel that the end result, the  website generated, is below human par, one thing is for sure, that technology always evolves until it gets it right.

Take, for example, the mobile app SkinVision which by taking a picture of a mole can decide if its malignant or not. The algorithm checks for irregularities in color, texture, and shape of the lesion. It indicates which skin spots should be tracked over time and gives it a low, medium or high-risk indication within 30 seconds

It's not 100% accurate yet so at this point the doctor's intervention is still necessary in order to manually verify the findings, but as time passes the algorithm evolves into achieving greater accuracies.If not convinced, take a look at IEEE Spectrum's score chart on the derby between AI and Doctors with evidence that in some areas AI right now surpasses the doctor's performance.



You would think that certainly Machine Learning requires a human in order to create and tweak those algorithms;that this intrinsic field of Computer Science should be secure.


Guess again. Ludwig is a new toolbox based on TensorFlow that: 

allows training and testing deep learning models without the need to write code.

Not just that, but it can also explain why the Neural Network worked the way it did :

Deep learning models internals are often considered black boxes, but we provide standard visualizations to understand their performances and compare their predictions

The importance of this was highlighted in our article TCAV Explains How AI Reaches A Decision.

But the rabbit hole goes even deeper as described in the Neural Networks In JavaScript With Brain.js article, which is about a code library which encapsulates all the AI logic so you don't have to, making you feel that your AI skills are worth less than you think: 

As exciting as the progress is, it’s bad news for both companies and individuals who have invested heavily in AI skills. Today, they give you a solid competitive advantage, as training a competent ML engineer requires plenty of time spent reading papers, and a solid math background to start with.

However, as the tools get better, this won’t be the case anymore. It’ll become more about reading tutorials than scientific papers. If you don’t realize your advantage soon, a band of interns with a library may eat your lunch. 

Of course, all this can be touted as enhancing productivity and if there's benefit in that, there's no stop in sight. AI will evolve and replace white collar workers, Robots will evolve and replace blue collar workers. So what about the top of the food chain, the programmers who make all this possible?

Productivity is the foremost principle that programmer's stand for; automating processes to save time and reduce erroneousness situations.Who would dispute that IDEs like Visual Studio make creating GUIs a more productive and bloat-free work? Or that automating unit tests make for better software quality?

Code generation, like what VS does when building your Windows form out of drag-and-drop block elements, metaprograming, as in “a computer program that writes new computer programs” by generating source code with the likes of CodeDOM, Roslyn or Expression trees, or the case ??for CASE tools that generate code from UML, are properties that each and every programmer welcomes.They make their life easier, more productive and more efficient.

So if Code generators and No-code tools do write code behind the scenes,does this mean that coders will be left out of job?

Difficult to say, but there's hope. First of all, code generators and no-code tools create code that quite possibly will need a human user to modify and adapt. But foremost, if the general consensus hints that the jobs that require problem solving are those that are going to survive, then coding the business rules falls within this category.

There is no, nor can ever be, AI or no-code tool that you can feed even with the most moderate rules of a business and let it generate an application. There's always going to be the human element that does the requirement to code translation.System Analysts should feel at ease after all. Then at the highest level,  the jobs of the coders who actually code the tools that make automation, AI and robots possible, should be condered safe.

The point is that what can be automated, will be automated. Automation is synonymous to Progress and Progress cannot be stopped.If that wasn't the case, then we would be still plowing fields with oxcarts and our world would be much different that it is now.

Despite the coming of the 4th industrial revolution and the rise of the machines, the human element is something that cannot be wiped out and for those job's to be lost to automation, it's a matter of how society will handle the matter, not because automation is inherently evil.Universal income, early pensions, retraining, working in new kind of jobs that will spring out of the new status quo, are just a few of the options available.

As Derek Lowe, a longtime drug discovery researcher, told the New York Times:

It is not that machines are going to replace chemists. It’s that the chemists who use machines will replace those that don’t.



More Information



Aspiring Dermatology App Under The Microscope: The SkinVision Review

Could A.I. Turn The Tables On The Physician Burnout Epidemic?


Related Articles

TCAV Explains How AI Reaches A Decision

Neural Networks In JavaScript With Brain.js



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Last Updated ( Monday, 01 April 2019 )