The internet is accessible from any place, and anyone can learn a great deal from it. The same can be said for Artificial Intelligence (AI). Anyone with an internet connection could learn and explore the world of AI without the need for an external factor such as a course or a degree. Anyone with a desire to learn AI from the ground up might do it using the publicly available resources. This is the idea of the Democratization of AI.
This is where anybody and everyone can learn about artificial intelligence. But is it a boon or bane?
For all those who are unable to attend famous institutions and earn prestigious degrees, for those who are denied the opportunity to pursue their passions, and for those who are in desperate need of information, YES! It’s a blessing. Above all, the democratization of AI has had a significant impact on AI engineers, researchers, and developers for the coming years. This would also help to speed AI’s development and spread to a wider audience.
This approach also lowers the cost of AI and makes it more accessible. Everything from static algorithms to fascinating machine learning algorithms would be easily available for individuals interested in learning more about AI and its various manifestations.
There aren’t many drawbacks to AI’s accessibility; however, the most significant and obvious one is ethical concerns.
One important difficulty is that practically every introductory AI course highlights areas where AI can be used that have significant ethical implications, such as healthcare. Younger children who are learning AI feel that they can construct AI systems that can be used in real systems, leading them to get swayed. Young brains, eager and determined, will not take no for an answer and will jump right into a project without thinking about the consequences. This is why democratization is facing opposition since it places AI in the hands of people who may not understand what they are doing or why their work could be destructive.
The lack of understanding is the other major difficulty. Comprehension here refers to a thorough understanding of both theoretical and practical issues. Any theory or practice is built based on conceptual understanding. If you take an AI course on Udemy you’ll study the complications rather than the essentials. If you are an expert, it is beneficial, but for newbies, Keras and Pytorch may appear to be Greek and Latin. This is a serious issue for the AI community since it results in engineers with insufficient technical knowledge. Because there isn’t enough theory, there isn’t enough practical enforcement. Now the applicant has the diploma and everything, but when it comes to working on real-world projects and attending interviews, the candidates with weak foundations fall behind, and the creamy layer takes over the industry.
In a nutshell, Artificial Intelligence democratization is a two-headed sphere. Spin the wheel and choose your next move carefully. You are going to win the game.