Artificial Intelligence needs to become less and less artificial

Artificial Intelligence needs to become less and less artificial

Artificial Intelligence needs to become less and less artificial

For AI to win people over, its applications must incorporate interventions aimed at allaying various fears generated by it.

AI (Artificial Intelligence) is everywhere and it’s here to stay. It now powers so many real-world applications, ranging from facial recognition to language translators and assistants like Siri and Alexa. Along with these consumer applications, companies across sectors are increasingly harnessing AI’s power for productivity growth and innovation.

There are many who believe that AI has the potential to become more significant than even the internet. Availability of enormous amount of data combined with huge leap in computational power and huge improvements in engineering skills should help AI, backed with deep learning, to make huge impact across various facets of human life.

Amid all the hype, genuine and inflated, around the world of AI, it is pertinent to ask an important question. Do humans really love AI? Are humans really happy that many of their daily tasks will now be taken care of by a machine? The adoption and so the future of AI is dependent on the answers to these questions.

In 2016, AlphaGo, an AI-based algorithm, trounced South Korean grandmaster Lee Sedol four games to one in Seoul, South Korea. This was the first time a computer program had beaten a top player in a full contest and was hailed as a landmark for AI. Today there are more efficient AI algorithms that can beat AlphaGo squarely. But the moot question is whether the human Go players would want to play more games with these machines. The superior computing power of AI has taken away even the remotest chance of a human winning a game against AlphaGo. It is unlikely that a human will want to play a game

that he is sure of losing, every time. This holds a valuable lesson about the future of AI. An AI product that makes humans look like losers will not have high adoption rates.

The last time there was a serious discussion about machines making humans redundant was at the beginning of the industrial revolution. Newly invented machines and industrial engineering principles put forward by F.W. Taylor treated humans as a replaceable parts of an assembly line. No one cared for the men who lost their jobs to machines, nor the men who worked on those machines. Workers in the world’s early factories faced long hours of work under extremely unhygienic conditions, and mostly lived in slums. This soon resulted in significant resistance to the introduction of machines and several labour riots.

Government soon intervened to provide basic rights and protection for workers. Statutory regulations forced factory owners to set up formal mechanisms to look into workers’ wages and welfare. Several new studies like Elton Mayo’s Hawthorne Studies debunked Taylor’s Scientific Management approach toward raising productivity and established that the major drivers of productivity and motivation were non-monetary factors. A host of new theories and management practices emerged that started treating workers as a resource, an asset. This human-centric approach played a significant role in making the industrial revolution a success.

Source:
https://www.livemint.com/opinion/columns/opinion-artificial-intelligence-needs-to-become-less-and-less-artificial-1560965545468.html