Challenges in Artificial Intelligence
Artificial intelligence, or AI, is a technique created by humans.
Artificial intelligence or AI as it is widely quoted in the news media is a top technology buzzword. If you are on social media platforms, such as Twitter, you will find that AI is often a trending topic. Facebook and Instagram may not let AI become trending. There, people share pics and don't share/expect tech news.
Artificial intelligence or AI stands for the human brain's intelligence mimicked by executing computer programs on the computing device(s) or machine(s).
AI uses real-world data through programmatic iterations and evolves into decisions/results faster and better than a single or a group of humans.
AI technology is a creation of humans and requires expert human intervention.
Common people's minds are overwhelmed by the hyped superpower of AI programs.
In reality, AI incurs heavy expenditure on computational resources.
If experts do not handle AI projects, the end products may sometimes turn into a useless catastrophe.
World leaders are driven mainly by political ambition and may sometimes ignore the ethical aspects of AI devices and software implementation on the common mass.
The citizens must have a clear awareness of the scientific, technological and ethical implications of using AI devices and programs in the living kingdom.
Challenges in Artificial Intelligence
AI is not only a buzzword. AI is a super complicated subject that requires a lot of computational resources and knowledge. You may join the trending news and clap your hands, expecting a "better future by AI."
The truth of implementing an AI project is a complex task that requires subject matter expertise, proficient computer programing skill, and enormous computational resources.
AI requires enormous computing power
Do you know that AI requires huge computational power? The power-hungry AI algorithms eat up an enormous amount of computer resources. Thus, running AI programs on our home computers and laptops remains a dream.
Machine learning (ML) and deep learning (DL) are the stepping stones of artificial intelligence. ML and DL algorithms may ask for several numbers of CPU cores and GPUs to execute the programs satisfactorily. Personal computers are insufficient for such AI project implementation.
Big AI projects for the real world may require supercomputing infrastructure costing a considerable amount of money and expert manpower. A single person or a small company can't afford to create an in-house facility for supercomputing. Government labs or big tech corporations can only initiate and execute an AI project with real-world use cases.
AI may overrule data privacy, data security, ethics, and health hazards
The most important aspect of AI is the real-world data from diverse courses. AI algorithms must utilize the data from real-life situations to train the neural network.
There is no way one can get real-life data without compromising personal and private data. The big tech corporations extract data from their global users by introducing clauses in user agreements and licenses.
For example, suppose a health service provider company utilizes their patients' data to train their AI algorithms and provide improved services. If somehow, the server storing the data is leaked into the hands of data hackers on the dark web, what will happen to the data privacy and security of the patients?
You might have heard about the neural link project of Elon Musk. What are the ethical issues of inserting a circuit inside the brain of a living being who is a human? Who will take responsibility for the health hazards of the implanted brain?
AI can't super pass human intelligence
Machines and computers can try what they are programmed for in a very limited way. A complex AI algorithm may consume challenging times to recognize and distinguish between human individuals. A child can instantly distinguish between and identify human individuals.
AI algorithms are sold at a huge cost to the government labs and small companies assuring high (say ninety percent) accuracy of results. But, many of the tasks can be done efficiently by humans. For example, distinguishing between an umbrella and a pen, or a cat and a bird.
To use AI for any task is not necessary. First, the incumbent scientist/engineer must analyze the actual requirements of the tools or instruments. If the task is very complex and analysis suggests the use of AI, the project may only be tried for AI adoption.
Closing thoughts
The future of the AI industry is bright, and so as the career opportunities for tech professionals with knowledge and expertise in AI.
Students and professionals go for AI training more than in any other field.
Every company wishes to incorporate AI in its products and solutions.
AI is a technology that has to be utilized with optimum human intervention.
That means AI has pros and cons.
No AI algorithm should run single-handed. It requires expert human intervention. Otherwise, there may be unwanted catastrophes.
The scientific community must use judicious power and cautious strategy to adopt and implement AI.
Cheers!
Unity (Debesh Choudhury)
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Unite and Empower Humanity.
June 22, 2022
No matter how advanced AI is, it can't surpass human knowledge.