No doubt Artificial Intelligence or AI has affected our life in a great way. The effect is quite tangible and it becomes major AI issues.
As monetary benefits lure more and more companies to adopt AI into their systems, firing automation that leads to layoffs.
The large-scale adoption of AI no longer requires human intervention.
As a result we have seen a huge head reduction in the job market recently.
Apart from the job loss there are other concerns that trigger anxiety among the community.
It includes safety, trust, computation power etc.
In this section we will take a close look at this gray area of AI.
In recent times, we have seen that Artificial Intelligence or AI has rapidly grown into a crucial technology.
As said earlier, it is changing our daily lives in numerous ways.
Now you will find virtual assistants in every middle class home.
The idea of self-driving cars is on the horizon. Not very far away.
The human-machine interaction has become seamless.
And, no doubt, it causes a major disruption in almost every field.
However, the silver lining is every sphere needs assistance of knowledge workers which we had not seen in the recent past.
At the same time, AI poses a set of challenges and ethical concerns before us.
As we discuss the major issues concerning AI we will try to understand the most significant problems.
The foremost major AI issues
Firstly, is the Bias and Fairness.
Why? The reason is simple.
Any AI driven UI relies on the data they are trained on.
As an outcome, we might question the nature of data that has been given to train the AI model.
Right?
That being the case, the data might perpetuate the bias in its predictions and decisions.
The issue is critical and we cannot ignore it.
What happens if AI generated output leads to discriminatory outcomes?
It will unnecessarily further establish inequality.
We have already seen it enough.
For that reason, we need diverse, inclusive, and fair data sets.
But who will look after that crucial matter?
Secondly, AI generated output might make things perplex and add blurriness.
That is why in some cases, we don’t understand the reasoning behind AI’s decisions.
Lack of transparency leads to more suspicion among people and can lead to distrust.
Consequently regulators will never be able to hold developers accountable.
Therefore, we need AI models that an average person can understand and explain.
But, is that possible?
Thirdly, one of the most crucial parts of AI and its related issues is safety and reliability.
An AI guided missile often falls on schools and hospitals instead of army barracks.
The risk of unintended consequences are always there.
How can we avoid these types of unethical or harmful decisions?
Catastrophic consequences might welcome us.
Who will ensure that all AI systems are robust, reliable, and safe?
In real-world scenarios, before the decisive deployment this decision needs a thorough introspection.
Along with safety the concern for privacy also gets us into tizzy.
Why so? Because AI systems collect a sizable amount of personal data.
After that it stores, and processes large amounts of personal data.
Who will offer a guarantee that no one will misuse, steal, or sell the personal data to third parties?
We have seen such serious consequences before.
It’s true that AI is becoming more advanced and capable of automating an increasing number of tasks.
For that reason, it directly impacts the job market which we have seen recently.
On the government part, there is a lack of clear regulations.
It can lead to confusion and ethical lapses.
Which happens pretty often.
No doubt, we need to establish a clear regulatory framework.
But who will bell the cat?
Who will ensure that there is no cyberattack?
We cannot ignore such issues.
To make AI a positive force for change and improvement in our lives, we need to think of all the above issues.
What Next?
TensorFlow, Machine Learning, AI and Data Science
Leave a Reply