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Is AI Really Bad For Human Future?

Is AI Really Bad For Human Future? Is it? Let’s see. There are very common myths about Artificial Intelligence (AI) that AI is taking over the working positions of human. After a few years, there could be robots everywhere. I personally heard from people who said, “Robots will take all jobs”, “Machine will destroy the future of humans”, “Robots will kill people”, blab blab.…

Those people believe that artificial intelligence is bad for human because it could lead to machines becoming smarter than humans, which could lead to humans becoming obsolete.

Others believe that artificial intelligence is good for human because it can help us achieve things that we couldn’t achieve on our own, and it can help us make better decisions.

We could analysis these myths and do our best to bust them.

What causes different people think “AI is bad for human!”

The only people who really unaware of AI subject, are spreading such kind of frustrated news that Artificial Intelligence will destroy human in near future. They listen chunks (hearsay) of latest AI technology randomly from several source and develop their own views about it. Whenever they have chance to spread these unreal views whilst talking to friends and family. Unawareness about AI, is the gigantic cause to develop the bad imprints.

There are many different reasons why different people think “AI is bad for human!” Some people may think that AI is bad for human because of the negative impacts it could have on the economy, such as jobs being replaced by robots. Others may think that AI is bad for human because it could lead to the development of powerful autonomous weapons that could be used to harm people. Additionally, some people may think that AI is bad for human because it could be used to track and control people’s behaviour.

You might be interested to read more articles as follows:

What really Artificial Intelligence is!

Artificial Intelligence is the way to make machines capable to do work according to the algorithms developed in them. After training, Machines are learning by themselves and perform tasks.

The term ” artificial intelligence ” ( AI ) has been around since the mid- 1950s, but what does it really mean? AI is the ability of a computer system to perform tasks that ordinarily require human intelligence, such as understanding natural language and recognizing objects in pictures.

In practical terms, this means that AI-powered systems can be used to process and make decisions on a wide range of tasks, including:

Let us assume a regular calculator. A developer has programmed to perform a task, for example,

(input ) operator ( input ) —>>> after applying rule (+) to add 1 and 2
Calculator performs operation and display result 3

In terms of AI calculator would be trained through specific algorithms by providing it a data set of values of inputs and outputs extracted from authentic source. During training it would develop the rule by itself to determine the result, for example,

(input data) + Result (output) -->>> Rules(defined by ML model

In this way, AI applications could be created to analyse data sets and make their predictions in very short span of time. Until now, AI can not be considered as Super Power that can do everything.

There are a lot of myths regarding AI due to lack of knowledge. Let us have a brief overview upon the limitations of artificial intelligence.

Limitations of Artificial Intelligence

Artificial Intelligence technology is limited in its ability to accurately recognize and respond to every possible scenario. As such, it may not be able to accurately interpret all human speech or respond in a way that a human would deem as helpful or appropriate.

1. Assuming and thinking: AI is super power!

People with no knowledge always assume that AI is a super power. This is absolutely not true. It is super power but not too.

2. Neither too optimistic nor pessimistic about AI

Suppose we have ten points of AI to think about. 1 to 5 band is AI is HERO and 6 to 10 band is AI is NOTHING just wasting time and money.

Now if we think only 1 to 5 band then we are too optimistic about AI and if we think only for 6 to 10 band then we are pessimistic. The best approach to assume and think about AI is to take all the ten points at a same time. Otherwise AI could experience again AI WINTER (it means the interest of people go down with lack of investment).  So Goldilock Rule for better understanding,

Neither too optimistic nor pessimistic

3. AI can’t do every thing, but will transform industries

Some manual tasks in industry could be automated. AI can’t do all the tasks in industry. Human has to manage AI applications that could transform industry. There is a live example of driver less cars which are still not super cars in current era. It will take more time, might be tens of years.

4. Performance limitations with small amount of data

AI is also facing lack of availability of proper data to train machine learning models. As more and perfect data could yield better results by machine learning. To get and maintain proper data is a giant milestone.

For example, in medical field, there are millions of patients go daily to doctors but there is no proper data collection fashion in medical industry except a few organisations only in the whole world. Mostly patients don’t want to share their personal details for the sack of data collection. With biased data AI can learn unhealthy stereotypes which could predict wrong deceases and medicines.

5. Explain-ability is hard (sometimes doable): How should we trust!

AI could be very hard to explain to the investors, as sometimes humans are also not good at explaining. That’s why to accept AI of things, we have to pass a large barrier.

For example, AI engineer is talking to a physician that AI can recognise brain tumour from x-rays. After listening these sentences, physician could imagine about killing of his job, he could assume AI app, could replace him. But if an AI expert would talk to physician in the way that AI application could help you to recognise brain tumour with more accuracy, he could be satisfied properly that AI is not killing his job but helping him to grow his career further more.

6. Machine Learning is not Foolproof

Machine learning works by considering past instances and using that data to make predictions or decisions in the present. However, if the data set is incomplete or inaccurate, the machine learning algorithm can produce erroneous results. For example, if a machine learning algorithm is taught to distinguish between pictures of cats and dogs using a data set that only includes pictures of dogs, it will be unable to correctly identify cats in new pictures.

7. Machines Cannot Grasp Complex Ideas

Machines are not yet able to understand complex concepts or ideas. For example, a machine may be able to identify that a picture contains a cat, but it will not be able to understand that a cat is a domesticated animal or that it can be used for transportation. Similarly, a machine may be able to understand simple math problems, but it will not be able to understand more complex math problems.

8. Machines Cannot Create New Ideas

Machines are not yet able to create new ideas or concepts. For example, a machine may be able to understand that a cat is a domesticated animal, but it will not be able to create the concept of a pet cat. Similarly, a machine may be able to understand that two plus two equals four, but it will not be able to create the concept of mathematical addition.

Conclusion

Nobody should have any danger from Artificial Intelligence. It will transform industries to only help human not to get them out from their jobs. AI is just at starting point. Its evolution could take many years to do the things like human.

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