Artificial intelligence (AI) is all the rage these days. Everyone’s talking about the potential of AI to solve everything from cancer to climate change.
But this buzz isn’t just about science. It’s also about the potential for AI to replace human intelligence. This is especially true when it comes to data science, which uses AI to solve specific problems and make specific predictions.
So, if you’re wondering whether you should start looking into data science, read on.
Data Science And Artificial Intelligence
Although at first glance it may seem like data science and artificial intelligence are two very different fields, they have more in common than you might think. Below we discuss what exactly each field comprises, before diving into how they can be linked together.
Data science
A data scientist can be thought of as the outcome when mathematics, statistics, data analysis, and computer science combined. A range of techniques that mainly stem from these disciplines are merged, which brings the world of data science to life. There are other subject areas that are also very relevant in data science including algorithms, data mining, artificial intelligence, and deep learning.
The main focus of a data scientist is, well, data. And since almost all kinds of organisations today are generating exponential amounts of data around the world, it becomes difficult to monitor and store this data.
A data scientist focuses on data modelling and data warehousing to track the ever-growing data set. The information extracted through data science applications are used to guide business processes and reach organisational goals.
Artificial intelligence
As a very simple explanation, artificial intelligence is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. This is a very simple definition, and we know that there is much more to AI than this.
AI uses the principles of software engineering and computational algorithms for the development of solutions to a problem. By implementing Artificial intelligence, many organisations and people can develop automatic systems that provide cost savings and several other benefits to companies.
So how do data science and AI link together?
Data science is a comprehensive process that involves multiple steps for analysing data and generating insights. It revolves around the idea of building models that use statistical insights to find hidden patterns and make predictions. Artificial intelligence makes use of computer algorithms to communicate the data models and reproduce it into human cognition and understanding.
Research Within Data Science And AI
There are many areas of research which bring together data science and artificial intelligence. Many of these research topics also combine other machine learning techniques to achieve the results that are being looked for. Examples of research areas that combine Ai, data science and machine learning include:
- Trustworthy AI – Many systems use artificial intelligence and machine learning within day to day lives including vehicles, criminal justice, health care, hiring, housing, human resource management, law enforcement, and public safety. This raises the question about the trustworthiness of AI. Research into AI can be conducted to understand whether the decisions taken by AI can be trusted to be correct, fair, ethical.
- Precious data – Data can be precious for one of three reasons: the data set is expensive to collect; the data set contains a rare event (low signal-to-noise ratio); or the data set is project specific. For each of these different kinds of precious data, new data science methods and algorithms need to be researched whilst the intended use of the data is kept in consideration.
- Deep learning research – Deep learning is a type of machine learning and artificial intelligence that imitates the way humans gain certain types of knowledge. Deep learning is an important element of data science, which includes statistics and predictive modelling. Research can be conducted to understand the mathematical properties of deep learning algorithms, as well as to understand the fundamental computational limits of deep learning systems.
How is Artificial Intelligence Different from Data Science?
The title of this post is why data science beats artificial intelligence, and you are probably wondering why. Up until now, we have been discussing the features of each and how they can be applied to research. But in reality, for a data scientist, artificial intelligence can be thought of as a tool or a procedure.
This means that AI can be used to aid in the analysis of data. A data scientist also makes use of AI tools like Deep Learning algorithms to perform rigorous classification and prediction on the data.
Think of it this way – we know that data science is a comprehensive process that involves the pre-processing, analysis, visualisation and prediction of data. On the other hand, AI is the implementation of a predictive model to forecast future events into which this predicated data can be put into.
Also, the tools involved in data science are a lot more than the ones used in artificial intelligence. This is because data science involves many steps and research processes which therefore require many more tools to carry out. Artificial intelligence does not require as many tools because it isn’t used to build models that use statistical insights – artificial intelligence is for building models that emulate cognition and human understanding.
The Future Of Data Science And AI
It is fair to say that neither data science or artificial intelligence (or even machine elearning for that matter) are going anywhere anytime soon.
Many industries all over the globe have implemented one of these three fields into the way that they work somehow. This includes sectors such as healthcare, advertising, banking, education, and machinery. For instance, in healthcare, data science and AI are used to handle patients and human resources like doctors or nurses effectively.
The great thing about this is that it is helping us to evolve to the better. Artificial intelligence and data science can be separately or together to help advance technology and meet demands that are currently impossible to meet.
Data science has a very big future because it is one of the key solutions for many business problems that can be seen throughout a company’s lifecycle. Artificial intelligence is showing a promising future in terms of efficiency, speed, and meeting difficult resolutions.
By combining the two together, Data Science and Artificial Intelligence have a bright future due to the advanced automation they offer for the various systems we use daily.
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