Gelesen: „Should Your Voice Determine Whether You Get Hired?“

In www.hbr.org lesen wir ein interessantes Stück. Es beleuchtet das Thema Stimme und Beruf und inwieweit schon jetzt die Stimme über Eignung im Job entscheidet.

Technology is changing every facet of work, including how companies profile and select their employees. The development of different apps, software, and algorithms has produced many novel methodologies for screening job candidates and evaluating their potential fit for a role or organization.

The latest of such methods is voice profiling, the use of computer-based algorithms to predict job fit based on an analysis of a candidate’s voice. According to news reports, “regardless of whether you’re happy, sad, or cracking jokes, your voice has a hidden, complicated architecture with an intrinsic signature—much like a fingerprint. Through trial and error, the algorithms can get better at predicting how things like energy and fundamental frequency impact others—be they people watching a movie, or cancer patients calling a help line.”

Although the idea that each voice is unique makes intuitive sense, some voice profiling tools, such as Jobaline, are based on a rather unconventional premise: Instead of trying to decode a candidate’s personality, intelligence, or mood state, they aim to predict “the emotion that that voice is going to generate on the listener.” In other words, the algorithm functions as a mechanical judge in a voice-based beauty contest. Desirable voices are invited to the next round, where they are judged by humans, while undesirable voices are eliminated from the contest.

As with many other innovations in the space of HR technologies, evaluating claims about the accuracy of this method is difficult until independent academic research has been conducted. The good news, however, is that there is a well-established formula for testing whether the method works: (1) measure features of candidates’ voices, (2) measure listeners’ reactions, and (3) measure whether listeners’ reactions relate to positive organizational outcomes, such as revenues, profits, and customer satisfaction. Then, correlate 1 and 2, as well as 2 and 3. If a pattern is found, … im Original weiterlesen.

 

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