Many industries today are data-driven. The amount of data, its variety, and the speed at which it is collecting means that it needs to be analysed scientifically if any intelligence is to be extracted.
A few years ago, the demand for Data Scientists was limited to research purposes. Nowadays, their expertise is in high demand throughout many industries because of the Information Explosion we have experienced in recent years. This extreme influx in demand has resulted in a profound increase in the development and acquisition of Data Scientists to deal with the data deluge.
The role of a Data Scientist is to analyse various data and extract knowledge and insights that can be used to gain information about a demographic or individual. They are responsible for performing a prescriptive analysis of the data history of the company, so that you can not only anticipate what will happen in the future and when, but also give a reason why. In this way you can establish what decisions will have to be made to take advantage of a future business opportunity or mitigate a possible risk, showing the implication of each option as a result.
To create functioning AI, a combination of Data Scientists and Machine Learning is required. Machine Learning is based on the idea that machines can be built to provide systems with the ability to improve and learn automatically, without being specifically programmed or supervised. It´s main focus is to access the data and use this data to learn, acting as a connection between Data Science and AI.
Put simply, AI means machines that can perform tasks intelligently and adapt to changing situations. For both processes, large amounts of data need to be collected, stored, and then used intelligently to generate performance.
Although AI is effective, it is still nowhere near human intelligence. As humans, we use data all our lives from past to present to assess everything we do. We are able to sense and feel, experience and think, and most importantly we are able to use understanding, logic, and reasoning, to make decisions; intuition, an ability AI does not yet possess. As the amount of data AI needs to perform simple tasks such as recognising letters is enormous, human intelligence is needed to sort, analyse and link this data efficiently so that AI can use it appropriately in the future. If we compare the two, Human Intelligence and AI, we can see that humans have had thousands, if not millions, of years of evolution, whereas AI has only been around for 50 years.
The assumed reasoning behind the creation of AI is to improve our human capabilities. If we consider a human´s ability to recognise a person in a photo, it is something the majority would perceive as simple. But for AI, thousands of data sets need to be analysed to carry out this same task and very little accuracy has been achieved so far. However, if we look to a human´s ability to multiply large numbers, it becomes a difficult task for our brains, but relatively simple one for AI.
By creating AI that mimics human cognitive functions but can also carry out tasks we find hard, we are able to create an extremely powerful tool. As highly social animals, we are able to communicate with others and establish connections- wether this be in the workplace or in the street. AI does not have this capability or anything close to it. It has been said that this creation is a ´Team Effort´, that ultimately serves to aid us.
As we look to the near future, demand will continue to increase for Data Scientists as the technological race continues. Due to the mainly unpredicted rise in demand for data and the amount that it has reached, caused by the big data boom, Data Scientists are often able to earn a high salary due to the basic principle of demand exceeding supply and the unique knowledge they bring.
With many universities and other education platforms offering education and training in this field at an increasing rate, some experts have predicted this run of demand will begin to decline in 10 years, and along with increased education and talent development, Data Scientists will experience more average salaries due to a greater equilibrium between the supply and demand of Data Scientists.
Overall, the need for human intelligence remains fundamental in our development of AI. A combination of the Big Data Boom, the Information Explosion, and the technological advancements that are taking place every day have led to a significant increase in the demand for Data Scientists. We now live in a world driven by technology, and it´s the people who are able to create and aid the production of this technology that we need the most. Our brains continue to be the most valuable and powerful asset we have, and we must ensure we respect that fact. AI can be brilliant, but only as brilliant as the minds that create it.
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