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Artificial Intelligence is the Way Forward for Jobless Youth in Pakistan

14th January is World Logic Day & UNESCO celebrates it with the whole world. Pakistan must ensure the spirit of Logic in state operations.
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Artificial intelligence (AI) is the capacity of a digital computer or computer-managed robot to accomplish tasks commonly associated with intelligent beings. The term typically refers to the project of developing systems supported by the intellectual processes characteristic of humans, such as the capacity to reason, uncover intention, generalize, or learn from cognitive understanding. Since the development of the digital computer in the 1940s, the invention has vindicated that it can accomplish much more intricate and complex tasks than even human beings do. These include discovering proofs for mathematical theorems or playing chess with incredible mastery and proficiency. Despite persisting advancements in computer processing speed and memory capacity, there are still programs that can match human flexibility over broader domains or tasks requiring much everyday knowledge. On the other hand, some programs have acquired the performance levels of human experts and professionals in performing certain specific jobs, so artificial intelligence, in this limited sense, is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition. Hence, Artificial intelligence (AI) relates to perceiving, synthesizing, and inferring information demonstrated by machines. The process is supposedly opposed to the intelligence displayed by animals and humans. It includes recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs.

The Oxford English Dictionary of Oxford University Press illustrates artificial intelligence as follows;

“the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages”.

The scope of artificial intelligence is developing with the advancement in technology. Hence, it is the technological sophistication of machines. Primarily, it is a machine intelligence based on human imagination and creation. It may add infinite value to scientific values and codes; however, it is yet to surpass the human imagination. Hence, the social part of artificial intelligence is the most cherished domain of artificial intelligence.AI applications, including advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). As machines become increasingly capable, tasks that require “intelligence” are often removed from the definition of AI, a phenomenon known as the AI effect. For example, optical character recognition is frequently excluded from things considered AI, which has become a standard technology.

Artificial Intelligence research pursues two distinct, and to some extent contesting, methods, the symbolic (or “top-down”) approach and the connectionist (or “bottom-up”) approach. The top-down approach seeks to replicate intelligence by analyzing cognition separated from the brain’s biological structure in processing symbols. On the other hand, the bottom-up approach affects the construction of artificial neural networks in imitation of the brain’s system.

To characterize the difference between these approaches, assume the task of building a system equipped with an optical scanner that recognizes the letters of the alphabet. A bottom-up approach typically involves training an artificial neural network by presenting letters to it individually, gradually improving performance by “tuning” the network. (Tuning adjusts the responsiveness of different neural pathways to various stimuli.) In contrast, a top-down approach typically concerns writing a computer program corresponding to each letter with geometric descriptions. In simple words, neural activities are the rationale of the bottom-up approach, while symbolic descriptions are the foundation of the top-down approach.

In The Fundamentals of Learning (1932), Edward Thorndike, a Columbia University, New York City psychologist, first suggested that human learning comprises some unknown property of connections between neurons in the brain. In The Organization of Behavior (1949), Donald Hebb, a McGill University, Montreal, Canada psychologist, suggested that learning specifically involves strengthening specific patterns of neural activity by increasing the probability (weight) of induced neuron firing between the associated connections. The notion of weighted connections is described in a later section, Connectionism.

In 1957 two robust advocates of symbolic AI, Allen Newell, a researcher at the RAND Corporation, Santa Monica, California, and Herbert Simon, a psychologist and computer scientist at Carnegie Mellon University, Pittsburgh, Pennsylvania, concluded the top-down approach in what they called the physical symbol system hypothesis. This hypothesis states that processing structures of symbols is sufficient, in principle, to construct artificial intelligence in a digital computer—moreover, human intelligence results from the same type of symbolic manipulation.

During the 1950s and ’60s, Scientists pursued the top-down and bottom-up approaches simultaneously and achieved noteworthy, if limited, results. During the 1970s, however, bottom-up AI was neglected, and in the 1980s, this approach again became noticeable. Nowadays, both methods are followed and are acknowledged as facing difficulties. Symbolic techniques work in simplified realms but typically break down when confronted with the natural world; meanwhile, bottom-up researchers have been unable to replicate the nervous systems of even the simplest living things. Caenorhabditis elegans, a much-studied worm, has approximately 300 neurons whose pattern of interconnections is perfectly known. Yet connectionist models have failed to mimic even this worm. The neurons of the connectionist theory are gross oversimplifications of the real thing. Mathematical, statistical and algorithm networks are essential parts of artificial intelligence. Programming, coding, re-coding and symbolizing are the techniques to achieve the target of AI. Hence, it is a machine network. Therefore, it has complex and intricate compulsions.

The past decade, nevertheless, has shown phenomenal growth in the development of AI technologies, primarily unlocked by the availability of computing power, the enormous amount of training data made available by Internet devices, and the decrease in cloud storage and computing costs. Consequently, AI technologies are already revolutionizing most industries, businesses, and lifestyles. There are sophisticated, intelligent assistants such as Siri on our phones, self-driving cars are nearer to evolving a part of our everyday lives, robots help farmers protect their crops from weeds by monitoring and spraying weedicide on plants, AI models can paint and render images from text, and AI systems are already aiding doctors in the early detection of diseases such as cancer and cardiovascular and neurological disruptions.

The global AI software industry is increasing. Statista reports suggesting it to reach $126 billion by 2025. Many attribute it to the engine of economic growth and the next big disruptor in the world. Numerous countries have designed dedicated AI frameworks and approaches to facilitate education programmes and research and development (R&D) epicentres to deliver technological advancements and economic growth.

Examples include China’s “Next Generation Artificial Intelligence Development Plan,” the US executive order on “AI leadership,” and “AI Made in Germany”, to name only a few. Pakistan must pursue these initiatives and invest in programmes to foster youths’ enthusiasm for AI and modern technologies. Investing in education programmes, research centres, and industry readiness training programmes is of foremost importance.

After all, Pakistan has tremendous AI potential, ranging from solving local problems in agriculture, governance, climate change, and manufacturing to designing tech unicorns and services companies specializing in hi-tech/ AI software exports. A few research labs, companies, and startups are already constructing a conducive environment in the AI space and contributing to the global tech ecosystem. For example, many young IT professionals in Pakistan have already started creating an impact on IT standards and solving the issues of IT-related complexities.

One of the most exciting works from their Intelligent Machines Lab is an economic indicators predictor that utilizes satellite and aerial imagery. They are designing computer vision/ AI tech that examines a satellite image and reacts with a poverty estimate for an area, delivering government and policymakers the data to make informed decisions.

The National Centre of Artificial Intelligence (NCAI) is a technological initiative established by the government of Pakistan in 2018 to achieve the objectives of AI. It strives to evolve into a leading hub of innovation, scientific research, knowledge transfer to the local economy, and training in AI and its closely affiliated occupations. Hence, there is a dire need to employ AI techniques in the government’s administrative structures. It must be a part of administrative reforms in Pakistan. AI is the future of the world. Thus, Pakistan must adopt technology and enhance productivity in all fields, from agriculture and social integration to political transparency and economic growth.

The youth of Pakistan must comprehend the scope of AI. They must learn the skills and innovation of the technology. Our universities and research institutions must adopt AI programmes in their courses to equip the youth of Pakistan. AI is the future and the most significant model and opportunity for jobs and creating enterprising businesses. Hence, the youth of Pakistan must embrace technology!

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