Artificial intelligence, or AI, is the ability of a machine to perform all tasks performed by a human. It has pretty much taken over most of our gadgets. On a much larger scale, we have AI in robotics, automobiles, i.e., self-driving cars, and an extension to our phones, the Internet of Things (IoT), which are intelligent devices like Siri and Alexa. Overall, we are surrounded by artificially intelligent beings everywhere around us. In addition, these beings drive our economy too. We have always talked about the food, industrial and service sectors in the economy. However, have we rightly analysed the contribution of AI to India’s economic growth or the lack thereof?
Stephen Hawking once said, “Computers will take over humans in the next 100 years. When that happens, we need to make sure the computers have goals that align with ours.” This statement rightly sums up the fact that there needs to be a proper balance between the human mind and AI algorithms.
The term ‘Artificial Intelligence’ is relatively new, coined in the 1956 Dartmouth conference among many renowned scientists and researchers. Studies emphasise that AI will have a significant impact in all fields, including a country’s economy. Artificial intelligence can increase the precision and efficiency of things, and using such latest technologies results in the creation of new products and services.
The digital revolution began during the 1950s with the introduction of mainframe computers, the internet, and information and communication technology. Major AI reforms started in the early 21st century, with robotics, biotechnology, 3D printing, blockchain, and more. The below pie chart shows the influence of the Internet of Things (IoT) in everyday businesses.
In economics, the most well-known and established use of AI is for prediction. Since the future is relatively unpredictable, AI is used to study past behavioural patterns, predict future conventions, and input it as a framework for allocating resources or tackling an unstable economy. According to a study by PricewaterhouseCoopers (PwC), global GDP is estimated to increase by 14% due to the involvement and development of artificial intelligence, which is about $13 trillion by 2030 and increasing by 1.5% a year. p>
Source: https://www.neowin.net/news/microsoft-predicts-ai-to-contribute-5-trillion-to-global-gdp-growth-among-other-advantages/ Some of the familiar situations where we can notice predictive algorithms are personalised feeds on social media like Instagram, predictive search results on Google, and recommendations on Netflix. Similarly, such forecasting algorithms take up a significant part of analysing economics on a larger scale. Entrepreneurs fully utilise the benefits of AI with chatbots, automation, and predictive analysis in the retail sector.
Artificial intelligence boosts the ‘random forest regression’ technique, found by two researchers from the University College of London. As for what “random forest regression” is, it is a forecasting algorithm similar to the structure of a forest with different trees. Similar to how a huge forest has numerous trees with thousands of branches and sub-branches, real value GDP variables are predicted by partitioning a set of data into large subsets and then refining it into smaller categories without overfitting the data. Compared to humans analysing this data, AI is more reliable to predict the GDP this way.
Foreign exchange trading or forex trading is also seeing a massive shift towards AI. Machine learning along with predictive analysis is the base of the predictions, where existing data and trade algorithms are used to predict market variations. AI is applicable here as it can analyse a vast amount of data for more accurate predictions and fewer mistakes. An example of AI’s success is how Nikkei, a Japanese company, made a quarterly “Dollar-Yen derby” to predict future exchange rates accurately. However, it is not always feasible to go the AI way. There has to be a suitable algorithm for predicting the data, and many traders might not know how to do so. Relying on inaccurate and wrong information can prove disastrous for trading. Even if the data is accurate, improper utilisation of it can also hurt the effectiveness of trading.
On a smaller scale, one has always debated about whether automation can genuinely help an economy grow. The productivity of a firm indeed increases by leaps and bounds when AI comes into play. However, much investment goes into the software and hardware. Apart from just investing money into the software, an appropriate algorithm that would help the business is required. AI needs enormous chunks of data for possible predetermined predictions, and there is no possibility of predicting an unexpected outcome.
A survey funded by Facebook showed that AI would have a lasting impact on the economy’s GDP, jobs, and productivity. Focusing on the ‘jobs’ part of the previous statement, A 2018 report from the World Economic Forum states that 75 million jobs would be eradicated by 2022 but mentions creating 58 million new jobs in the same breath.
Source: https://www.pwc.co.uk/automation
However, logically, AI-related jobs are indirectly related to education. Moreover, from a scientific perspective, we need to keep in mind that it is challenging to incorporate AI in many careers where human resources are essential. People can lose their job when a factory becomes fully automated, leading to unemployment. In the middle ground, not all jobs will be lost, and instead, new opportunities can be created under AI maintenance.
Source: https://www.oxfordinsights.com/ai-readiness2019 There is also another factor to keep in mind while automating the world. Not every country is well-off to invest in AI, and it is clearly visible in the above map that developing economies are pretty behind the developed ones.
Overall, there are always positive and negative effects of any technology. The same scenario of hesitation had occurred when computers were newly introduced. If AI displaces some jobs, new jobs like data analysis, marketing professionals, technology specialists, and most importantly, IT services will receive a big boost. It can also result in a better literacy rate all over the world. The government can take up training initiatives as a readiness measure to incorporate AI into people’s everyday lives. When it comes to AI applications in the finance sector, predictions can never be 100% accurate, as they are just an estimation of the future. Humans have been adapting to changes ever since their existence, and artificial intelligence is also just a new development in our lives.
Praneetha KWriting Mentorship, 2021
References
1. https://www.oxfordeconomics.com/thought-leadership/artificial-intelligence2. https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/637967/EPRS_BRI(2019)637967_EN.pdf 3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204330/ 4. https://seekingalpha.com/article/4090229-this-machine-learning-technique-can-predict-gdp-better-forecastersgetRandomImage(‘Artificial-Intelligence-VS-Artificial-Growth’)
The digital revolution began during the 1950s with the introduction of mainframe computers, the internet, and information and communication technology. Major AI reforms started in the early 21st century, with robotics, biotechnology, 3D printing, blockchain, and more. The below pie chart shows the influence of the Internet of Things (IoT) in everyday businesses.
In economics, the most well-known and established use of AI is for prediction. Since the future is relatively unpredictable, AI is used to study past behavioural patterns, predict future conventions, and input it as a framework for allocating resources or tackling an unstable economy. According to a study by PricewaterhouseCoopers (PwC), global GDP is estimated to increase by 14% due to the involvement and development of artificial intelligence, which is about $13 trillion by 2030 and increasing by 1.5% a year. p>
Source: https://www.neowin.net/news/microsoft-predicts-ai-to-contribute-5-trillion-to-global-gdp-growth-among-other-advantages/ Some of the familiar situations where we can notice predictive algorithms are personalised feeds on social media like Instagram, predictive search results on Google, and recommendations on Netflix. Similarly, such forecasting algorithms take up a significant part of analysing economics on a larger scale. Entrepreneurs fully utilise the benefits of AI with chatbots, automation, and predictive analysis in the retail sector.
Artificial intelligence boosts the ‘random forest regression’ technique, found by two researchers from the University College of London. As for what “random forest regression” is, it is a forecasting algorithm similar to the structure of a forest with different trees. Similar to how a huge forest has numerous trees with thousands of branches and sub-branches, real value GDP variables are predicted by partitioning a set of data into large subsets and then refining it into smaller categories without overfitting the data. Compared to humans analysing this data, AI is more reliable to predict the GDP this way.
Foreign exchange trading or forex trading is also seeing a massive shift towards AI. Machine learning along with predictive analysis is the base of the predictions, where existing data and trade algorithms are used to predict market variations. AI is applicable here as it can analyse a vast amount of data for more accurate predictions and fewer mistakes. An example of AI’s success is how Nikkei, a Japanese company, made a quarterly “Dollar-Yen derby” to predict future exchange rates accurately. However, it is not always feasible to go the AI way. There has to be a suitable algorithm for predicting the data, and many traders might not know how to do so. Relying on inaccurate and wrong information can prove disastrous for trading. Even if the data is accurate, improper utilisation of it can also hurt the effectiveness of trading.
On a smaller scale, one has always debated about whether automation can genuinely help an economy grow. The productivity of a firm indeed increases by leaps and bounds when AI comes into play. However, much investment goes into the software and hardware. Apart from just investing money into the software, an appropriate algorithm that would help the business is required. AI needs enormous chunks of data for possible predetermined predictions, and there is no possibility of predicting an unexpected outcome.
A survey funded by Facebook showed that AI would have a lasting impact on the economy’s GDP, jobs, and productivity. Focusing on the ‘jobs’ part of the previous statement, A 2018 report from the World Economic Forum states that 75 million jobs would be eradicated by 2022 but mentions creating 58 million new jobs in the same breath.
Source: https://www.pwc.co.uk/automation
However, logically, AI-related jobs are indirectly related to education. Moreover, from a scientific perspective, we need to keep in mind that it is challenging to incorporate AI in many careers where human resources are essential. People can lose their job when a factory becomes fully automated, leading to unemployment. In the middle ground, not all jobs will be lost, and instead, new opportunities can be created under AI maintenance.
Source: https://www.oxfordinsights.com/ai-readiness2019 There is also another factor to keep in mind while automating the world. Not every country is well-off to invest in AI, and it is clearly visible in the above map that developing economies are pretty behind the developed ones.
Overall, there are always positive and negative effects of any technology. The same scenario of hesitation had occurred when computers were newly introduced. If AI displaces some jobs, new jobs like data analysis, marketing professionals, technology specialists, and most importantly, IT services will receive a big boost. It can also result in a better literacy rate all over the world. The government can take up training initiatives as a readiness measure to incorporate AI into people’s everyday lives. When it comes to AI applications in the finance sector, predictions can never be 100% accurate, as they are just an estimation of the future. Humans have been adapting to changes ever since their existence, and artificial intelligence is also just a new development in our lives.
Praneetha KWriting Mentorship, 2021
References
1. https://www.oxfordeconomics.com/thought-leadership/artificial-intelligence2. https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/637967/EPRS_BRI(2019)637967_EN.pdf 3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204330/ 4. https://seekingalpha.com/article/4090229-this-machine-learning-technique-can-predict-gdp-better-forecastersgetRandomImage(‘Artificial-Intelligence-VS-Artificial-Growth’)
