IS THE WHEEL BEING REINVENTED – THE PARADIGM SHIFT OF AI FROM BC (BEFORE CARONA) TO AC (AFTER CORONA) WORLDProf. Venkatesh Sunkad Dean, INSOFE School of Data Science, Vijaybhoomi University Music and entertainment are among the fastest-growing industries today, globally and in India. Digital media and the internet have broken down the geographical boundaries, making the entire global population a potential audience to music and entertainment. While considering potential career opportunities in music and …
Prof. Venkatesh Sunkad
INSOFE School of Data Science,
Music and entertainment are among the fastest-growing industries today, globally and in India. Digital media and the internet have broken down the geographical boundaries, making the entire global population a potential audience to music and entertainment.
While considering potential career opportunities in music and entertainment, it is very common for many to limit their thinking.
On December 30, 2019, an AI-driven health monitoring platform called BlueDot spotted a cluster of unusual pneumonia cases occurring in Wuhan, China. The Canadian company sent out a warning to its customers the next day — December 31. They had identified what would come to be known as COVID-19 a week before the Centre for Disease Control and Prevention (CDC) in USA or 2 weeks before WHO was able to spot it. Artificial Intelligence, or AI, has played a key role in identifying and addressing the pandemic.
Before the arrival of Covid-19, many technology executives were expressing uncertainty about their investments in machine learning (ML), and dissatisfaction with the ways their organizations were adopting it. Since the pandemic, according to World Economic Forum’s “The Future of Jobs Report,” 50 per cent of businesses say COVID-19 has pushed them to accelerate automation in their organizations.
The recent hiring trend is a forward indicator of the future workforce. The latest survey by the leading professional and social connect company “LinkedIn” has determined the top two highest paid jobs are “AI engineer” and “Data Engineer. A couple of years ago it was a “software programmer”. So the future workforce should be “Data Savvy” meaning that everybody should be comfortable with digital technology and should be able to translate whatever the results the AI models give out into real business tangible actions and to production AI solutions.
Not every job in the field of data science involves coding and engineering. There are a lot of jobs like “Media Curator” who needs to understand how data from media can be made useful to Data Science but does not involve coding. However, if you want to be in the technical field, the most important skill sets are coding, a good foundation in mathematics and statistics, Machine Learning, AI fundamentals and cloud architecture. Another very important aspect to be good in AI is critical thinking which is the bedrock of Data Science.
If you look at India particularly there may be a handful of institutions that can create the environment and teaching that would really cater to the needs of the industry. One such institution is Vijaybhoomi University where I am the Dean for the “INSOFE School of Data Science” which is a centre of excellence in digital and disruptive technologies. We have dedicated degree programs both at Bachelor’s (BE in AI) and Master’s (MTech in AI) levels. These programs are in collaboration with the International School of Engineering (INSOFE) and Vijaybhoomi University. The most important aspect of all these programs is that nearly 50% of the time is spent on “hands-on training” with real-world problems which according to me at an undergraduate level would be the first in India. This would make the students “industry ready” starting from how to analyse data, build models and finally produce the solution.
In addition to being trained in AI and ML, the students are also intensively trained in other disruptive technologies like Block-Chain, IoT, Robotics, etc. Once the students are comfortable with fundamentals then they can adapt to the ever-changing world. AlsoVijaybhoomi follows a liberal professional education which is very critical for a successful career in data science because problems are no more one-dimensional but multi-dimensional which needs 360-degree thinking. One of the examples I always give is autonomous or self-driving cars. When a kid suddenly comes in front of the car, today if a human is driving they make a decision to avoid the kid which may result in the car hitting another vehicle or a structure. However, if it is a “self-driving car “should the car protect its passengers or the kid in front of it. These are called “moral algorithms” that an AI engineer should design, knowledge of humanities, law and other aspects play a very critical role here.
Overall, the post-pandemic world will look very different from the way we were used to. At the centre of this revolution will be AI/ML/Data Science. Truly this will be the “coming of AI Age” in the next decade.