With IBM's excellent development, organizations will experience a seamless hiring process, transforming the outdated and boring procedures into an exciting prospect. No longer will one dread working; instead, with Gen Ai playing a pivotal role, recruiters will thrive in their professional lives.
Sounds awesome. Too good to be true. Identifying where bias exists in current processes and weeding out bias in data used to train the algorithm… otherwise as women and minorities would be without jobs.
I question biase when the training data represents the actual ground truth--current or historical state of the company--vs. manipulating data it to represent a social construct that you wish to see. A couple of generations down the road the data drift will be so bad on your models will be nowhere near reality.
Very interesting indeed. However, you must be careful not to rely too much on machines. We are humans, after all, and you risk creating an artificial selection of people who know how to trick the machines with the right words and style. This is already happening to some degree. Worst still, you may not take advantage of a unique combination of people (and hence, the generation of new ideas) that would have only arisen out of the intrinsic randomness of human life. As I like to tell my wife... I am thankful that we met before the era of internet dating, for a machine would never have matched us.
With IBM's excellent development, organizations will experience a seamless hiring process, transforming the outdated and boring procedures into an exciting prospect. No longer will one dread working; instead, with Gen Ai playing a pivotal role, recruiters will thrive in their professional lives.
Sounds awesome. Too good to be true. Identifying where bias exists in current processes and weeding out bias in data used to train the algorithm… otherwise as women and minorities would be without jobs.
I question biase when the training data represents the actual ground truth--current or historical state of the company--vs. manipulating data it to represent a social construct that you wish to see. A couple of generations down the road the data drift will be so bad on your models will be nowhere near reality.
Who are watching this video from IIT, Gangapada 👍🏻😅
Very interesting indeed. However, you must be careful not to rely too much on machines. We are humans, after all, and you risk creating an artificial selection of people who know how to trick the machines with the right words and style. This is already happening to some degree. Worst still, you may not take advantage of a unique combination of people (and hence, the generation of new ideas) that would have only arisen out of the intrinsic randomness of human life. As I like to tell my wife... I am thankful that we met before the era of internet dating, for a machine would never have matched us.