top of page
  • Raghav Sand

Artificial Intelligence: Evolution and Utility

Artificial Intelligence (AI) is all around us. What was once thought as science fiction is now serving humanity and is learning new patterns to get better. The self-correction feature of AI is both revolutionary and worrying. Experts in the field of computing and human behaviour do not seem to agree on a vast majority of issues. Scholars on both sides of the aisle agree on the near-term benefits of AI, but their views seem to diverge as the debate shifts to the intermediate and long-term effects of conceding decision making powers to machines.

Private enterprise has been and will be at the forefront of AI evolution, though, the regulators can no longer afford to stay behind the curve. Data is the most crucial ingredient for AI. Big data has made it possible to analyze and systematically extract information from data sets that are too large or complex to be dealt with by traditional data-processing software. The synergy between AI and big data are manifold. It will be prudent to say that AI owes its existence to Big Data.

AI: Creation During Crisis

Alan Turing, who deciphered the Enigma code, is widely credited as being one of the first people to come up with the idea of machines that think in 1950. He created the Turing test, which is still used today, as a benchmark to determine a machine’s ability to “think” like a human. His ideas were ahead of their time and like all radical thoughts, they were mocked at the onset. Turing’s concepts set the wheels in motion, and the term “artificial intelligence” entered popular awareness in the mid- 1950s, after Turing died.

AI: Reach and Riches

Path-breaking technology takes time to develop and it takes even longer to become accessible to individuals in the middle- and lower-income groups. And, once the sought-after technology becomes universally accessible, a more efficient version is already at the fingertips of large corporate houses and high net worth individuals. The true potential of a technology will only be realised when it is democratized. For achieving a wider adoption of innovations in the field of machine learning, the creators have to strike a balance between the economics and ethics of a product’s life cycle.

AI: Jobs Creator or Destroyer?

AI will destroy some jobs as machines learn to do tasks that previously required human involvement. But AI is also expected to create new jobs for workers who have the right skill sets and education. This is a story that will evolve over the next two decades; ethical dilemma of AI, and its possible bearing on the labour market are debatable issues.

The COVID-19 pandemic has not been contained yet, and it has left a dent on the economic gains made after the financial crisis of 2007-08. An enormous number of people have been affected, as lockdowns curtailed non-essential activities. Most small and medium level enterprises may not survive the crisis and the select few which stay afloat risk being gobbled up by large corporations. Technology is sprouting at an exponential pace and by the time it is safe for people to move around freely, many jobs and skills may turn redundant.

These apprehensions will not deter the adoption of sophisticated technology that has been developed after years of research and development. Upskilling can no longer be ignored and the advocates of sustainable development should start being proactive and get rid of their reactive attitude.

AI in Everyday Life

Google’s search prediction, weather forecasts, email spam filtering, and popular voice command assistants like Alexa (Amazon) and Siri (Apple) are some of the examples of AI in our everyday life. Virtual Assistants or Chatbots may seem like fun and games, but there are profound real-world uses of this constantly improving technology. The average user may ask the virtual assistant about the weather forecast or directions while riding / driving a vehicle. Visually impaired persons use the voice command feature to access their mobile devices and search for a contact they wish to send a message or give a call. There are few more impactful applications of technology than enabling ease of living for people who have encountered challenges during integration in the workforce or while performing everyday tasks smoothly.

AI and Agriculture

AI-based farming has gained momentum in the last couple of years, as techpreneurs are trying to codevelop and implement innovative ideas in agricultural activities. Predictive tools are providing impactful inputs for improving harvest quality and accuracy – what is known as precision agriculture. Seasonal forecasting, soil fertility study and farm workload management are also contributing in improving yield per acre.

Image Courtesy: Twitter (Digital India)

Data collected from past years and scenario analysis with the hep of AI has benefited the farmers who have shown receptivity to modern technology. Agriculture in India is a heavily dependent on Government subsidy. Crop failure erodes the capital of financial institutions who have exposure to farm loans and the snowball effect jolts the exchequer’s fiscal arithmetic. It is in everyone’s best interest to adopt ideas which simultaneously curtail loss and enhance income.

AI and eCommerce

eCommerce is now a way of life for most urban and semi-urban consumers. Whether it is personalized product recommendations or discount offers, AI has taken the lead in this aspect of operations and is delivering stellar results. Logistics is an important part of operations in eCommerce. If done well, it can add to the bottom line, and if there is any slackness, the whole operation will cease to exist sooner or later. AI-based technology provides suggestion for creating hubs for various product categories like books, home appliances, food and beverages, etc.

AI and Manufacturing

The present scale of manufacturing operations could not have been possible without automation. Economies of scale has made it possible to keep the cost of production under control, aiding to keep the sale price within reach of millions. Environmentalists argue that automation and large-scale industrialisation have caused irreversible damage to the environment and ecology. Something was needed to feed and move seven billion humans – technology turned out to be the saviour. The collateral damage caused in the process could not have been envisaged at the start of industrial and technological revolution.

AI and the Future of Energy

Oil, gas and electricity are the most common sources of energy. Factories, homes and transportation system are fed with energy to sustain lives and livelihood. AI-enabled electricity grids make it possible to channel electricity to deficit areas and schedule power output based on recommended surge and contraction in demand. Uninterrupted and stable power supply is essential for economic growth. AI is silently playing a pivotal role in round-the-clock energy availability.

AI has improved oil and gas production rates and lowered costs. Underperforming wells are being be identified in advance and preventive maintenance is carried out before problems arise. AI is helping to carry out tasks on unmanned and automated drilling platforms. Availability and affordability of non-fossil fuel powered vehicles and manufacturing equipment are not going to be widespread anytime soon, hence, adoption of AI is a viable option to bring quantifiable advances in the present energy value chain.

bottom of page