Is Artificial Intelligence A Threat To Software Testing?

Is Artificial Intelligence A Threat To Software Testing?

It is a well-known fact now that Artificial intelligence (AI), robotics and other forms of ‘smart automation’ are advancing at a rapid pace and somewhere along the line they do pose a threat to the current jobs across the globe.

However, AI based automation testing will definitely disrupt the markets and it would be interesting to see the outcomes around new opportunities that get generated. 

With these continuous advancements in robotics, machine learning (ML) and artificial intelligence (AI), the new age of automation is getting redefined.

Machines have now started to match or even outperform their human counterparts in a wide range of activities including the ones that earlier required cognitive capabilities.

George Neal, chief analytics officer at PrecisionLender, says AI won’t take over testing. But he also says that testing is going to get much harder as we introduce machine learning into applications because we won’t know what the application is supposed to do in all cases.

With the most difficult problems, machine learning will be making choices based on likelihood, not certainties. Testers, we’re not in Kansas anymore.

“For people who don’t like to do what humans do well, the future is a very scary place,” Neal says.

The idea being that humans are very good at creativity, exploration, understanding, analysis, and the application of knowledge. So folks who don’t like these activities are going to find challenges in doing what they like in the future.

To give a little perspective of what AI can do, let’s see what are some of the mind-blowing stuff that it has done till date.

  • Google’s AI builds its own AI which outruns all the human-made AIs
  • AI learns to write its own code by stealing lines of codes from an existing software
  • AI defeats world’s top poker players
  • Self-taught AI outperforms skilled doctors at predicting heart attacks.
  • AI discovers two new planets for NASA

Many scientists perceive this potential as a threat. In fact, this has caused a huge divide among well-known scientists and entrepreneurs.

It is very difficult to predict whether AI could be a threat; however, one thing is for sure that QA testers don’t need to lose their sleep over it. Having said that, they must be alert and ready to incorporate this new technology.

“Artificial intelligence is a tool not a threat”
-Rodney Brooks

Higher Accuracy – To err is human. The most experienced of us are prone to mistakes, varying under circumstances and with repetitive tasks. This was one of the topmost reasons why automation testing services gained prominence in the software testing industry.

However, automation is still only as smart as we design it to be. AI on the contrary performs the task exactly as intended, even in repeated case scenarios with no exceptions and also stretching itself to learn and unlearn as trained.

While AI performs, automation engineers can easily invest in other automation solutions which can be otherwise performed by human counterparts only.

Greater Flexibility – Test failures can happen even due to the slightest changes in the application code and can create a negative impact due to traditional testing scenarios which are, at times, rigid. Flexible testing process is one factor which is highly enjoyed by AI – ML. The systems based on these technologies are made to adapt in real time by being reliable and flexible.

Validating Visually – AI has the ability to visually recognize and validate a pattern or image for potential bug detection while performing visual testing of the application.

It seamlessly ensures proper functioning of the elements. Irrespective of shape and size, AI can detect UI controls, by analysing them at pixel level. Though AI is not fully capable of handling a test on its own, without its human counterparts, it can still speed up the testing process by reducing the time and increasing the accuracy.

Highly Cost Effective – The integration of AI into the automation testing process greatly reduces the cost of manual efforts done by human resources and effectively manages repetitive tasks for continuous delivery and increased productivity.

The AI based app testing services of the future is projected to be promising with the entire process becoming more efficient.

It will effectively take a huge amount of the tester load, while QA testers will have bandwidth to acquire new skills because working in-sync with AI would require diversified competencies such as logical reasoning, mathematical optimization, algorithmic analysis and business intelligence.

This will ensure higher investments by digital businesses on their QA teams for their skill development.

If AI will change our perspective the same way power windows forced giggles out of Arbon’s kids, maybe our lives as testers are about to get a whole lot easier. AI’s interactions with the system multiply results you’d have with manual testing.

“The coming era of Artificial Intelligence will not be the era of war, but be the era of deep compassion, non-violence, and love.”

-Amit Ray, Pioneer of Compassionate AI Movement.

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