Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

Full Bio 
Follow on

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

3 Best Programming Languages For Internet of Things Development In 2018
315 days ago

Data science is the big draw in business schools
488 days ago

7 Effective Methods for Fitting a Liner
498 days ago

3 Thoughts on Why Deep Learning Works So Well
498 days ago

3 million at risk from the rise of robots
498 days ago

Top 10 Hot Artificial Intelligence (AI) Technologies
308742 views

Here's why so many data scientists are leaving their jobs
80385 views

Want to be a millionaire before you turn 25? Study artificial intelligence or machine learning
75396 views

2018 Data Science Interview Questions for Top Tech Companies
75243 views

Google announces scholarship program to train 1.3 lakh Indian developers in emerging technologies
60990 views

How to Prepare Employees to Work With AI

By Nand Kishor |Email | Jul 6, 2017 | 8307 Views

Disruption is inevitable, but also deeply feared. We've seen this with every significant technological leap -- from the printing press to automobiles to computers. But, as we enter the next iteration of technology with AI, we know it will have a profound, transformative effect on global business and society. However, we must reflect on how we want this transformation to occur.

Early adoption has already begun: AI is transforming everyday activities and processes such as virtual assistants, fraud detection and driverless cars. Various forms of AI solutions are already in the market, including automation, speech recognition, machine learning, decision-making and natural language processing. Organizations that are already investing in these technologies are better positioned for long-term success.

As a society, we must accept the fact that AI is here to stay, and realize thoughtful adoption of the technology is critical. 

But, what does this mean for the workforce? For software developers, data scientists, engineers and the full spectrum of information technology workers, AI is perceived to either be putting their jobs at risk, or changing their responsibilities to accommodate its rapid advancement. While it's difficult to predict the pace of AI adoption, some of the technology's most influential leaders and early adopters agree that it's advancing faster than anticipated. As AI's development accelerates and implementations spread, it raises the question for workers in tech and other industries: Are my skills still relevant?      

Investing in employees
A positive, counterintuitive side effect of early AI adoption is that it's requiring companies to invest in their employees. Bringing AI into the enterprise calls for investments in software and technologies that support its implementation, but also in the training and skill building for employees working alongside it. Companies can't go all-in on AI without balancing the investment ratio between technology and human workers.

Recent research by Infosys revealed that globally, 76 percent of decision makers agree AI is fundamental to the success of their organization's strategy. More optimistically, 80 percent of respondents say they'll retrain or redeploy employees whose roles are replaced or plan to be replaced with new technologies. This is why it's essential to rethink our approach to education and employee development and lay a foundation for continuous lifelong learning.

Why problem finding is still uniquely human
This shift in learning is necessary not only for the workforce today, but for future generations. We are developing and deploying AI systems that will become so advanced they will become part of the fabric of every industry. Students, academics and workers will need the skills and expertise to work intimately with AI systems. This new mentality requires a curious mindset and a thirst for knowledge and learning.

Decades from now, AI may replace cognitive tasks such as identifying and solving problems. Today, AI can identify patterns and anomalies in environments and production and notify humans about that information, which may not have been uncovered otherwise. However, human creativity and ingenuity will always be required to find the problems AI can solve in the first place. 

After all, humans do not simply endure technological disruption -- they help shape it as part of our future. The advent of the automobile didn't just help us travel faster and further; rather, it led to roads, highways and entirely new industries. 

Similarly, AI can be a great enabling force that amplifies and empowers people, improves the quality of life for all and opens up opportunities for the underprivileged. It's not a question of man versus machine, but man and machine. 

Shaping tomorrow's workforce
Providing employees with the opportunity to pursue learning and training programs to enhance their careers and help them understand new AI applications benefits employers as well. It encourages a more knowledgeable workforce that's inspired and motivated. It also creates the type of employees that become "problem-finders" seeking out the "unknown unknowns," and begin the work of turning these problems into solutions. Increasingly, this will involve the aid of AI.

To reach the full human potential offered by AI, education and training must be a priority. For this to happen, digital literacy is fundamental for every future generation. Each child must have access to computer science courses. But, doing this requires a new perspective on education by both government and the private sector -- otherwise the education and skill sets of employees now and in the future won't rise to meet the rapid adoption of AI.

This also means rethinking education, recasting it as a life-long process, and deemphasizing rewarding memorization and routine in favor of curiosity and experimentation. We must modernize courses to encourage creative problem finding and solving, and learning through doing, with mandatory computer science learning as the bedrock for enabling digital literacy. Organizations also need to make life-long learning resources available for employees to enhance skills development and can dedicate a percentage of their annual revenue to reskilling staff.

It's a pivotal point in human history. AI is under construction before our eyes as the next great technological evolution, and we must be prepared to evolve alongside it.

Source: Entrepreneur