{"id":941,"date":"2022-04-18T23:16:04","date_gmt":"2022-04-19T03:16:04","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/?post_type=hck-submission&p=941"},"modified":"2022-04-19T15:14:43","modified_gmt":"2022-04-19T19:14:43","slug":"how-do-we-find-the-right-balance-between-robots-and-humans-making-talent-decisions","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/how-do-we-find-the-right-balance-between-robots-and-humans-making-talent-decisions\/","title":{"rendered":"Balancing robots and humans in talent decisions"},"content":{"rendered":"\n\n\n

Ever since I heard Frida Polli speak about Pymetrics<\/a> at one of my classes earlier in the semester, I could not help but wonder if using AI for hiring decisions would truly debias the process. A week later, I heard from Kate Glazebrook who spoke about Applied<\/a>. Kate firmly believes that algorithms have no place in talent acquisition, and instead she uses a mix of behavioral science with analytics, but screenings and decisions are always conducted by a human being. Once again, I was left with more questions than answers.<\/p>\n\n\n\n

\u00a0AI-powered companies for hiring seem to grow on trees these days, and each one of them claims to \u201cmake sure there\u2019s never any bias creeping into the system\u201d, like Scoutible\u2019s CEO shared in a 2019 Wall Street Journal article<\/a>. When a colleague asked Frida Polli about the human decisions behind Pymetrics\u2019 algorithms, she gave all the reasons why hers was better and more precise than others. The same happened in our class with Noah Zandan from Quantified. The fact that neither of these smart individuals questioned the system they had created, or felt their algorithms needed more probing was, in my eyes, problematic.<\/p>\n\n\n\n

Artificial Intelligence is going nowhere. Companies are demanding more cost effective and fast practices that allow them to screen piles of candidates in a more systematic and less time consuming way. Recently, companies have not only used algorithms to screen r\u00e9sum\u00e9s, or make decisions based on a particular skill set, but it seems that \u201ctechnology is displacing human interviews\u201d, according to a 2020 Financial Times article<\/a>. Gamifying the selection process seems to be capturing the interest of recruiters who choose real-life scenarios to assess the cognitive or problem-solving skills of a particular candidate. Some of these companies are willing to embrace the innovation, but are still skeptical of AI. EY, for example, still prefers the decision-making process to be done by a person: \u200b\u200b\u201dWe felt we wanted a blend of smart people and smart machines working together\u201d.<\/p>\n\n\n\n

However, not all HR managers are raving about incorporating AI into their processes, and not for the reasons I initially thought. Besides the algorithm aversion that we frequently talked in class, HR managers are seeing AI as a threat to their jobs, as People Management shares in this 2022 article<\/a>. AI seems to be forcing the HR profession to quickly go through an upskilling process. Yet, courses like People Analytics are not offered in every university across the world, and HR degrees tend to have very little analytical courses that would allow practitioners to be part of this new world. <\/p>\n\n\n\n

Between the fear of biases, the fear of admitting algorithms do not have all the answers, and the fear of algorithms stealing HR jobs, we are less ready than I thought to embrace this technological revolution. AI Organizational psychologist Tomas Chamorro-Premuzic shared that “AI should be used to take care of predictable, repetitive, and low-level tasks, leaving humans to provide the creativity, curiosity, and empathy that AI cannot provide.<\/a>” Maybe finding a balance between robots and humans in the hiring process is just about buying all of us some extra time.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

AI in hiring is here to stay. 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