Hedging: The language tool that can change your life | Alice Ashcroft | TEDxScarisbrick

Quick Overview

Dr. Alice Ashcroft argues that the common habit of using hedging language like "I think" or "maybe" undermines authority and credibility, especially for women, and advocates for replacing this linguistic self-sabotage with intentional, context-aware communication rooted in clearly articulated reasons, exemplified by her personal shift in professional interactions.

Key Points: The speaker, Dr. Alice Ashcroft, highlights the irony of giving a talk on hedging despite using it frequently in the past. Hedging language includes phrases like "I think," "maybe," and "sort of," which were found to be used by women more frequently than men in conversations and even in TED Talks. Research suggests that women who speak more directly face negative performance feedback compared to men using identical language, creating a 'double bind' where hedging undermines authority and directness undermines likeability/credibility. Ashcroft advocates for replacing hedging with intentional language based on context, audience, and goals, emphasizing the need to articulate the 'why' behind statements. She uses the analogy of buying a car: if you see the desired model everywhere after deciding on it, it illustrates how once you recognize hedging, you start seeing it constantly. The goal is to intentionally deploy or withhold hedging based on context, audience, and goals, rather than using it as an unconscious habit born from perceived weakness or social pressure.

Context: Dr. Alice Ashcroft delivers this TEDx talk focusing on the linguistic phenomenon of 'hedging'—the use of tentative language (like 'I think,' 'maybe,' 'sort of') in conversation. She explains how this habit, which she herself used extensively, is often unconsciously deployed, particularly by women, but has significant negative impacts on perceived authority and credibility in professional and social settings, especially when contrasted with research showing direct speakers face different negative feedback.

Detailed Analysis