Can Artificial Intelligence Help Answer HR’s Toughest Questions?

Running Head: BUSINESS MANAGEMENT
Business Management
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1
BUSINESS MANAGEMENT
Artificial intelligence is the one of the fastest growing technological advancements in
today’s world and is increasingly playing a bigger role in several industries across the world,
replacing human workforce with far more efficient and precise results. In the field of Human
(HR) Resources as well, Artificial Intelligence (AI) has made its mark as a growing number of
leaders are considering an optimized combination of human and digital efforts for managing
the workforce of their organisations (Bhardwaj, 2019). In this essay, I will try to analyse the
article “Can Artificial Intelligence Help Answer HR’s Toughest Questions?” by Peter
Cappelli and Prasanna Tambe.
According to the article, the incorporation of AI involves the use of certain algorithms,
which generally look back at the pre-installed data from the past. However, following such an
algorithm may not always work out as the best hiring strategy as trends and systems are
changing at a rapid pace. The task of human resources often deals with questions regarding
fairness, which is essentially a morally subjective concept, and fairness does not always
comply well with optimization and machine learning (Cappelli & Tambe, 2019). With the
introduction of AI in the scope of human resources, companies are seeing a growing influx of
data analysts in HR (Nicastro, 2018). Data scientists have always faced difficulty in gathering
data on employee performance and hiring and analyzing it, therefore the ability to
successfully incorporate that into AI is another hurdle.
Another important discussion in this article is in reference to the difference between
the traditional HR practices and the new methods developed by AI. In the old days, candidates
had to undergo a number of rounds like IQ test, aptitude test, personal interviews, etc. They
were marked according to different criterion. The hiring manager would consider the different
scores and weigh them based on his own scores and discretion and make a judgment (Cappelli
& Tambe, 2019). The modern digital systems however take into account such scores, along