---
id: "contrarian-machines-teaching-human-skills"
type: "contrarian-insight"
source_timestamps: ["¶ Last Paragraph", "\\\"§ In Pursuit of Personalization and Efficiency", "at Scale\\\""]
tags: ["contrarian", "irony", "soft-skills", "edtech"]
related: ["concept-gen-ai-tutor", "claim-lower-competency-gains"]
challenges: "The assumption that human 'soft' skills require human teachers and classroom environments to be effectively developed."
speakers: ["Sagar Goel", "Shubhankar Sohoni", "Lisa Krayer"]
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-cl-86-genai-transform-l-and-d"
sourceUrl: "https://hbr.org/2025/09/how-gen-ai-could-transform-learning-and-development"
sourceTitle: "How Gen AI Could Transform Learning and Development"
---
# Machines are the Best Teachers of Human Skills

## Contrarian Insight: Machines are the Best Teachers of Human Skills

**Challenges:** The assumption that human 'soft' skills require human teachers and classroom environments to be effectively developed.

Conventional wisdom holds that uniquely human 'soft' skills (empathy, [[concept-problem-framing]], vulnerability) are **best taught by human mentors** in highly interactive, interpersonal settings. The authors argue the **exact opposite**: because machines offer **infinite patience, total personalization, and a completely judgment-free zone** — which *encourages* vulnerability — they can be **superior vehicles for teaching the most human of skills**, especially for **lower-competency learners** (empirically, the **+32%** gain in [[claim-lower-competency-gains]]).

**Enrichment / verification — split verdict.** The *weaker* form is well supported: AI tutors teach many cognitive and procedural skills effectively, at scale, in psychologically safe conditions, sometimes outperforming active-learning classes (physics RCTs). The *stronger* form — that machines are **better than humans** at teaching **empathy, vulnerability, and collaboration** — is **speculative and only partially supported**; empirical evidence in complex interpersonal domains is still emerging. Brookings cautions AI tutors must be carefully designed and **complement** human teachers. The honest boundary is captured in [[question-complex-teaming-skills]]: excellent for practice, reflection, and foundational skills; not yet a substitute for live human team dynamics.