Artificial Intelligence Development: Opportunities and Challenges

For many years, the world has talked a lot about the 4.0 Industrial Revolution. This covers different fields such as the Internet of Things, Blockchain, Biotechnology, etc., and Artificial Intelligence (AI) is seen as the core of this revolution

Big countries like the United States and China are focusing their resources on AI research with many projects of great value. According to The Future of Jobs report of the World Economic Forum (WEF) in 2020, the top 3 occupations that are forecast to grow strongly are jobs related to Data Science, AI, Machine Learning, and Big Data. In the near future, it is expected that most jobs will be influenced by AI.

What is Artificial Intelligence?

AI affects many areas in all aspects of social life that are very familiar to us. If you've ever heard of a camera-based facial authentication system, it's AI. If you've ever heard of a speech recognition system and speech-to-text software, it's also AI. If you've ever been familiar with the function of identifying information on an ID card, passport, or vehicle registration plate, it's AI too. And if you've heard a lot about Alexa or Siri, it's definitely AI.

So what is AI? In the simplest terms, AI is all about making machines smarter and doing tasks that normally require human intervention. For example, by applying AI, computers can distinguish colors, shapes, human faces or sounds, voices, etc. When it comes to AI, people often refer to technical terms like Machine Learning or Deep Learning...

Boundless Potential of Artificial Intelligence

In recent years, the development of Artificial Intelligence in the world has reached many milestones, resulting in practical applications in society. Virtual assistant applications such as Apple's Siri, Amazon's Alexa, Google's Assistant, and Microsoft's Cortana are some of a few familiar examples.

The potential of AI in life is unlimited. Let us take the healthcare industry as an example. With the application of AI, patient information can be analyzed to generate suitable recommendations for doctors, thereby contributing to improving patients' health and reducing treatment costs. For medical facilities, AI can be integrated into the chatbot platforms to improve customer services through typical functions like interactive conversations, scheduling appointments with doctors, or assisting with medical advice.

In the finance industry, AI is qualified to help businesses analyze big data, thereby making recommendations to help business leaders make accurate decisions. With its "smart" features, AI can completely provide financial analysis and customer support in the best way.

These applications are absolutely capable of changing the organizational operation of businesses, thereby helping to drive automation and enhance productivity. It can be said that if investing in AI development with a clear plan and long-term vision, people's lives will be greatly improved as AI has the ability to solve numerous aspects of life with its self-learning ability to process information and data on a large and complex scale.

In the long run, along with the evolution of technologies like Big Data or Machine Learning, AI will be applied and developed in a way to become a key in automating and digitizing the economy. This is also the foundation to form and develop many useful applications and services in the future.

But Are There any Challenges in Implementing Artificial Intelligence?

With the information above, if you think that AI can completely replace humans in every aspect, you may need to reconsider. Some difficulties in applying AI to reality make this scenario unlikely to happen.

One of the problems is that most users don't really understand the true nature of AI because AI is thought to be perfect at all times. Basically, AI is created on the basis of learning human behaviors. When it reaches a certain level, without the addition of algorithms and information, the product's performance will stop there and cannot be further improved. Cases of disease diagnosis or facial recognition are the most controversial examples.

Data privacy and security are barriers to AI-powered product development

Another problem is data limitation because AI is built on data sources provided by users and developers. Big data will make AI smarter and better respond to real-world requests. However, data collection is a hard work and time-consuming job. In particular, when it comes to important decision-making issues such as finance, banking, or national security, AI has little opportunity to use this data source.