- #Selecting human resources terjemahan dari how to
- #Selecting human resources terjemahan dari software
#Selecting human resources terjemahan dari how to
“How to ensure that the algorithm is fair, how to make sure the algorithm is really interpretable and explainable - that’s still quite far off,” he said.Īmazon’s experiment began at a pivotal moment for the world’s largest online retailer. But computer scientists such as Nihar Shah, who teaches machine learning at Carnegie Mellon University, say there is still much work to do.
#Selecting human resources terjemahan dari software
human resources managers said artificial intelligence, or AI, would be a regular part of their work within the next five years, according to a 2017 survey by talent software firm CareerBuilder.Įmployers have long dreamed of harnessing technology to widen the hiring net and reduce reliance on subjective opinions of human recruiters. It also serves as a lesson to the growing list of large companies including Hilton Worldwide Holdings Inc HLT.N and Goldman Sachs Group Inc GS.N that are looking to automate portions of the hiring process. The company's experiment, which Reuters is first to report, offers a case study in the limitations of machine learning. It did not dispute that recruiters looked at the recommendations generated by the recruiting engine. Amazon’s recruiters looked at the recommendations generated by the tool when searching for new hires, but never relied solely on those rankings, they said.Īmazon declined to comment on the technology’s challenges, but said the tool “was never used by Amazon recruiters to evaluate candidates.” The company did not elaborate further. The Seattle company ultimately disbanded the team by the start of last year because executives lost hope for the project, according to the people, who spoke on condition of anonymity. But that was no guarantee that the machines would not devise other ways of sorting candidates that could prove discriminatory, the people said. They did not specify the names of the schools.Īmazon edited the programs to make them neutral to these particular terms. It penalized resumes that included the word “women’s,” as in “women’s chess club captain.” And it downgraded graduates of two all-women’s colleges, according to people familiar with the matter. In effect, Amazon’s system taught itself that male candidates were preferable. Most came from men, a reflection of male dominance across the tech industry. That is because Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. “They literally wanted it to be an engine where I’m going to give you 100 resumes, it will spit out the top five, and we’ll hire those.”īut by 2015, the company realized its new system was not rating candidates for software developer jobs and other technical posts in a gender-neutral way. “Everyone wanted this holy grail,” one of the people said. The company’s experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars - much like shoppers rate products on Amazon, some of the people said.
The team had been building computer programs since 2014 to review job applicants’ resumes with the aim of mechanizing the search for top talent, five people familiar with the effort told Reuters.Īutomation has been key to Amazon’s e-commerce dominance, be it inside warehouses or driving pricing decisions.
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