The recent time has been witness to a number of situations and in there the overall reputation of artificial intelligence has not been a very favourable one. It has been considered as a threat to opportunities surrounding human employment in spite of the fact artificial intelligence is being used in the mundane lives. The advancing technologies of artificial intelligence, machine learning, robotics have had enough impacts over the economies that are still growing.
The Concept in Brief
Deep neural networks are being used on a large scale in various applications of artificial intelligence which includes extremes of functions like robotic surgery to translation functions of Google. Deep neural networks happen to be a facet of artificial intelligence that imitates the approach of learning that humans often make use of to gain different types of knowledge. In the same way as human brains contain neurons, deep neural networks also contain a number of artificial neurons which are used for the purpose of identification and storage of information.
The Infrastructural Issue
One problem that neural networks face is that they often require huge amounts of data for the purpose of learning the way to perform a task in a proper manner. Neural networks are considered to be data-hungry. When compared with other machine learning models which are simpler, neural networks demand a data storage infrastructure that is more sophisticated in nature and the processing technology involved is also quite complicated. Such infrastructure is quite expensive and it becomes a problem for developing nations to afford such an infrastructure.
The Environmental Factor
Another problem associated with this type of feature of artificial intelligence lies in the fact that it impacts the environment adversely. With the high price tag by its side, this is an additional problem that is linked with deep neural networks. For instance the estimated cost of training a neural network is around $150,000 USD and with that the emission of carbon dioxide rounds up to around 650 tonnes which has an absolute detrimental effect over the health of the environment.
The Problem with Datasets
Developing nations face a number of barriers and challenges while building the market as well as the industry for artificial intelligence. The datasets that are available for the crucial purpose of training the models are extremely limited. To add to the problem the quality of data that is available is not proper and is questionable. There have been cases where due to the inappropriate, low-quality and wrong data, many projects which were supposed to add benefits and serve a fruitful purpose have failed.
The Non-Economic Costs
Yet another issue that deserves attention revolves around the non economic costs like privacy loss that the developing countries have to bear as a result of the adoption and development of the artificial intelligence market and industry. The concerns so associated tend to appear during the different stages beginning from gathering of data to the development procedure to the final stage of actual use of the applications of artificial intelligence. For instance, China is developing applications of artificial intelligence that are not considering any kind of ethical issues. Still there are countries that are violating privacy laws as well as human rights while developing various applications like surveillance tools using artificial intelligence.
There are some developing countries that have been known to be using artificial intelligence solutions that have been built by companies of foreign origin and they tend to deliver poor performance and their usability is also limited.
The Internet Issue
When the internet connectivity is poor in the urban and the rural areas, it creates several problems and acts as a hindrance in the adoption of the artificial intelligence services by the consumers. Statistical report reveals the fact that around 267 million people in Africa and around 53 million households do not have the basic access to the internet.
Disparities associated with access to the internet exist between the urban and the rural population, also between men and women, between different age groups like the youth and the older age groups and most importantly between different income groups of people like the higher and the lower income groups.
The high cost which is associated with the internet data of mobiles and the broadband connectivity which is home-based play an active role in diminishing the market share of the services revolving around artificial intelligence and also the number of people using it.
Limited internet connectivity poses yet another problem where the regular updation of apps becomes impossible and this once again restricts the efficient functioning of the artificial intelligence services as they require data rich apps that undergo regular updation.
Smartphones capable of supporting high-tech apps have still not penetrated properly in third-world countries. Smartphone penetration is around 45% in Sub-Saharan Africa and in South and South-East Asia, it is around 64%. Though a rise is expected in the coming years, most of the devices represent models that are outdated and are incapable of supporting high-tech apps.
Lack of Apt Skills and Knowledge
Of the many, one big challenge that developing nations face is the lack of talents and skilled manpower who are capable of handling the various technologies associated with artificial intelligence. Educating people and upgrading their skills and knowledge to enable them to deal with the technologies of artificial intelligence is now the need of the hour.
Artificial intelligence brings with it a sack full of opportunities and benefits for mankind. Though it provides the society with varied opportunities, the developing nations go through a number of issues as discussed which comes as a barrier while adopting its services. Hence it is required that the challenges should be dealt with and then overcome successfully in order to ensure that the world in its entirety is not deprived of the benefits that artificial intelligence has to give.
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