Abhishek Rungta

First thing first – We overestimate in short term, and underestimate in long term. It is as true for change, risk, as well as our own productivity.

AI will definitely have an impact on most aspects of our life, over time. Possibilities through technology is changing faster than human ability to adapt. Sustained change happens over several years (at times decades), and this happens in waves. Let’s draw a parallel with e-commerce. I have seen the e-commerce revolution and the dot-com mania of 2000. Even in 20 years, even half the world’s shopping have not moved online. Similarly, we have seen multiple peaks of crypto, but even 10% of world’s economy has not moved to crypto even after 12 years! Human beings need time to adapt, and hence some of these big changes may take at least a generation to become commonplace and defecto.

Though Data and AL/ML will be used extensively, it will go through several cycles of experiments and evolution before it finds it societal fitment. Though technology can possibly create bots which can take an interview and assess a candidate, but most people wont be comfortable and/or find conviction in such scenarios. The human touch will be necessary for near to mid term future.

Even before talking about AI/ML, we need to focus on building a data culture in organisations, and then achieve data maturity.

– What kind of data are we capturing, and why?
– How can we make sense of the data that we have and that we desire to capture?
– What insights and correlation can we drive from these data points? E.g. Can we capture soft data points around a person’s upbringing and link it with his retention and performance?
– How will this correlation change in different industries and roles?
– How can we ensure that the AI/ML model does not learn the inherent biases? As it is anyways trained based on input data, which itself may have biases.

Once data maturity is achieved, companies should focus on building strong analytical models, correlation, causation, etc. ML & AI will follow as the data and models mature.

During this journey, AI should be used as augmented intelligence, or assisted intelligence; and not artificial intelligence. It should be used to convert faint signals into strong insights. This will offer great ROI, as less experienced people can be empowered, and move up the value chain faster.

HR and technology leaders should start their AI journey with an end-goal in mind, a specific problem to be solved with technology. Else it will deliver optics, which is great for satisfying ones’ ego, but wont deliver much ROI.

These thoughts are notes from the #HireConnectIndia program organised by LinkedIn where I was speaking on behalf of Indus Net Technologies (INT.) yesterday.