DATA SCIENCE AND ARTIFICIAL INTELLIGENCE
As broad and complicated these two terms seem, don’t worry it’s nothing to do with Skynet and the rise of machines; Doom’s day is not here yet! Then what exactly is the objective of having sciences develop a field so complex such as Data Science itself? Let’s find out!To put it in simpler words, a Data Scientist plays with data and information in order to open a whole new world of possibilities, predictions and different outcomes. AI, on the other hand, runs through these different possibilities; records results and paves an achievable path to reach the most desired outcome. Must say, technology is pretty enticing, right?!
Without any further ado, let’s dig a little deeper in the relevance of these to fields and find out how they are impacting our world today and, given that no AI unit turns into a terminator, Data Sciences and Artificial intelligence might even have a role in revolutionizing the age of internet, i.e., the 21st century.
What can we expect from DATA SCIENCE?
The work of a Data Scientist is to understand goals of a business or company and determine ways to achieve goals, while dealing with and extracting the data that determines the market patterns. So, yeah, with this data you might as well be able to predict the future trends and practices. Excited already? Hold your horses, there’s a lot more to come further. Not to forget, the data might differ from time to time, the procedure of extracting and processing it still remains the same and involves extensive re- search, asking the right questions, dealing with data, designing modules, making changes according to feedback and repeating the process to solve a new problem. I need someone to wipe the sweat off my forehead.
Implications of Data Science.
Real life can be hard and without the existence of Data Science, trust me it can be very hard. In fact, Data Science has been deemed effective in tackling many problems faced in real life and has gradually been adopted across different industries in order to boost decision-making. While use of computers has increased from business to personal operations there is a significant high demand to learn and work on the patterns on which a human works and
behaves. Right there, that’s how interesting Data Science can be. Let’s see which all industries follow the trend of Data Science to make their lives easier and their work more fruitful.
● The Gaming industry has opted for the use of data science for a very long time. Games like FIFA, PES and MLB have highly been dependent on pure data and algorithms for players. Aren’t they the players of Sciences?!
● Sports industry has also copied the model of Data Science in order to get clear-cut information about viewership of different competitions like Cricket and Football World Cups, club competitions and many other sports. So now, Data science has penetrated its roots into sports as well.
● Data Science has made a major impact in Healthcare during COVID-19 outbreak and before that by detecting similar patterns and finding new solutions to tackle these situations. So, it did come to our aid when we needed it the most. What could be a better use of a Science than this?!
● Are you a binge watcher too? Well, guess what, the most visible use of Data Science is done by different OTT platforms. The recommendation system of your account is not really just random; it’s based on your previous watch and search history, after
analyzing the previous information Netflix and Amazon Prime suggests the same genre or category of shows and movies. Data Science’s contribution to Actuarial Science. Now, how can you leave a Science that takes you to the future, separated from the ones who tell you about the future? Seems like an absurd idea, doesn’t it? Although there are some differences between Data Science and Actuary but at times both these fields of work go together with each other from these similarities and resemblance came out the term Actuarial Data Scientist. Actuarial Data Scientist is an extension of Actuarial Science which uses machine learning techniques in problem such as pricing, claims and lapse predictions.
Data Science techniques can be used in the following areas of Actuarial Science
1) Pricing.
2) Loss and Risk Predictions.
3) Detecting fraud claims and Modeling in life insurance.
What can we expect from AI ?
Now that we are talking about the future and the rise of Technology, not to forget Skynet and the rise of Machines, how can we leave AI behind? AI technology has gained a lot of ground in the following years, it’s needless to say that the current surge of resources in AI research is unmatched. AI applications and implementation doesn’t just provide us with better results but also improves human experience in totality. Currently there is a significant number of industries dependent on AI technology. Mind blown already? Hang on, there’s more to come.
Implications of AI.
The sky-rocketing growth in AI is creating products and services that in nearby future will change a lot in which actuaries operate, but will also provide them with a new world of possibility. Crossing our fingers on this!
● One of the major impacts of AI is on the gaming and entertainment industry, from helping OTT platforms to personalize viewing experience to enhance the digital effects of the movies and being used in pre and post production AI has been experimented with in every way possible to get really creative content. If we talk about the gaming industry, they were the earliest adopters of AI from controlling
NPC of games to drive the game storyline forward. AI’s gaming behavior model enhances gamers experience in the storyline.
● AI is currently being used in a range of healthcare needs, the entry of companies like Microsoft, Google, Apple and IBM has just accelerated this process more. AI plays a critical role in planning the treatment procedure and to analyse patients’ medical records.
● Have you ever thought of robots preparing your food or a cup of tea for you? Well fortunately now you don’t have to always plan about preparing food after long work hours since AI development has touched the industrial food processing sector as well. The wide range of AI into inroad farming sectors is also visible with intelligent tractors and plucking machines.
● The logistics and transportation industry are on the verge of a new AI revolution. Using AI to find the quickest shipment route to sorting and packaging in warehouses is slowly pushing human labor out of the way and providing people with more sufficient and satisfactory results. Whereas the concept of self-driving car sounds out of this world in its own way, although this is still under heavy re-search
and probably will go through a lot of changes before reaching a final product AI replaced self-driving car will make roads much safer.
AI contribution to Actuarial Science.
The intelligence of technology is going to make the lives of Actuarial easier too. Here’s how!
AI brings more structure, consistency and unbiasedness at a point to perform actuarial work and reducing human intervention but AI combined with actuarial science is way more productive and time saving. With process automation and AI, the actuaries’ time would no longer be unnecessarily spent in processing data and crunching numbers. Instead, actuaries could spend more time performing analysis and making recommendations in areas they understand well such as marketing financial products and managing enterprise risk.
