Let’s have an insight into the decentralization of AI and its pros and cons
The internet is everywhere; anyone from anywhere can access and learn many things. The same applies to Artificial Intelligence (AI). Anyone with access to the internet could learn and explore the areas of AI without relying on any external factor such as intelligence, this is where AI education is accessible to all. But this is where the real problem arises: The democratization of artificial intelligence: a blessing or a curse?
Boon
There are so many reasons it is a blessing: for those who do not have access to prestigious universities and degrees, for those who are deprived of their passion, and for those who urgently need to quench their thirst for knowledge, Everyone likes this, YES ! It’s a blessing. The democratization of AI will have an enormous impact on AI engineers, researchers and developers, especially in the years to come. This would also help accelerate the growth of AI and reach a large part of society. However, it depends on how willing we are to accept that it has spread very quickly. This move also makes AI extremely affordable and accessible. From static algorithms to cool ML algorithms, anything would be available for those looking to explore AI and its denominations.
Bane
In all fairness, there aren’t many downsides to AI accessibility, but the most important and obvious ones are ethical concerns. An important point to note is that almost all beginner AI courses cover areas where AI can be implemented that have significant ethical issues, such as in real-world systems that get them carried away, Go straight to a project without considering the damage. This is why I fear democratization as it puts AI in the hands of people who may not understand what it is building and why their work is potentially dangerous.
This is now putting everyone at risk, students and professionals, so the only solution is to incorporate the ethics of AI into the curriculum and make sure everyone knows it so that they learn AI, your techniques and research, and then ethics and related practices at the same time .
The other main concern is a lack of understanding. Understanding now means a deep insight into the theory and the practical concepts. Conceptual understanding is the cornerstone of any theory / practice. For example, if you take an On Udemy on AI course now, you will learn the subtleties instead of the basics. It’s good for you if you’re an expert, but for newbies, Keras and Pytorch can look like Greek and Latin. This is a big problem for the AI community as it creates engineers. Without proper technical training, lack of proper theory leads to lack of practical application. Now the candidate gets the certificate and everything but while working on real-time projects and attending job interviews, those with poor basics are left behind and the creamy layer takes over the industry.
Because “it is always the survival of the fittest” In short, the democratization of artificial intelligence is like a two-headed sphere. Spin the wheel and take turns carefully. You will win the game.
