At TalentLogiQs we're often asked about our view on and what we do with it. It's surprising to some that, unlike many in AI is not our core USP.
At TalentLogiQs we're often asked about our view on and what we do with it. It's surprising to some that, unlike many iAI is not our core USP. In fact, you willhardly find it in our documentation. This article shows why: AI may be innovative, but it's not a substitute for decent science.
This study comparing the predictive ability of AI with common techniques in talent intelligence shows no improvement in most cases. Only with non-standardized data, low sample sizes, or for dimension reduction can AI algorithms outperform standard models.
In other words: Are you dealing with garbage data or hardly any data at all? Then AI is your weapon of choice. If you can have scientifically validated data (which is abundant for HR), then AI may just be an expensive, risk-laden and difficult-to-interpret tool to 'fiddle in the margin'.
AI is useful to grind high-volume, low-quality data, to outsource non-critical, repetitive, or supervised tasks efficiently, or to enrich pattern identification steps in your analysis. We too experiment and work with ChatGPT and other AI companions to write first drafts, orient literature reviews, ALM to speed up statistical analyses, ...
Yet, when it comes to intelligence to support people decisions, Scientific Best Available Human Intelligence (BAHI) still beats AI in cost and performance!
Find out how BAHI is applied in our Talent Intelligence Suite.
