『Ep8: Sameer Ranjan — A mining engineer turned AI builder weighs how platforms guiding career choice and soft skills can keep human judgment central when the models risk automating the decisions they claim to augment.』のカバーアート

Ep8: Sameer Ranjan — A mining engineer turned AI builder weighs how platforms guiding career choice and soft skills can keep human judgment central when the models risk automating the decisions they claim to augment.

Ep8: Sameer Ranjan — A mining engineer turned AI builder weighs how platforms guiding career choice and soft skills can keep human judgment central when the models risk automating the decisions they claim to augment.

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10月19日まで。※適用条件あり
Sameer Ranjan, a mining engineer turned AI builder, described how his platform normalizes personality and soft-skill scores inside separate cultural baselines instead of forcing a single universal scale. He stressed that the system supplies diagnostic signals only and leaves every hiring, retention, or assignment decision to a human. The exchange tested whether quantified soft skills can guide careers while keeping human judgment in front of the models. • Ranjan cited an internal hospital-system study in which attrition fell from 22 % to 12 % once managers received clarity on communication gaps rather than skill gaps. • The patent US 12198213B2, assigned to Catenate Corp, quantifies soft skills and personality to recommend courses, colleges, and careers on the premise that personality shapes long-term outcomes more than job skills alone. • To block gaming, the recommendation engine resets the question set for each user after the initial baseline is established, so no fixed right-or-wrong answers exist. • Cultural baselines are built from open-source data plus native-language assessments; a score of four out of ten on communication is interpreted relative to the local distribution rather than against a global mean. • The platform never frames problems or issues directives; it only flags gaps such as communication shortfalls, after which humans decide what action, if any, to take. • Baseline values are treated as moving targets: new assessment data are compared with prior standard deviations, and shifts are reviewed by multiple human advisors before any update is accepted. • Ranjan’s explicit design rule is that the AI remains a “decision-aiding tool, not a decisioning tool,” with follow-up assessments used to check whether any human-chosen intervention produced measurable change. Sameer Ranjan is Co-Founder & CTO of Catenate, the company behind the MayaMaya platform for workplace personality and soft-skills analysis. Find Co-Founder & CTO, Catenate: • catenate.io: https://catenate.io
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