Counterspeakers' Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hate

TL;DR

This study explores counterspeakers' perspectives on barriers and AI needs in online hate countermeasures, highlighting concerns about authenticity, agency, and functionality to inform AI tool design.

Contribution

It provides in-depth qualitative insights into counterspeakers' barriers and AI requirements, emphasizing the importance of maintaining authenticity and agency in AI-assisted counterspeech.

Findings

Identified four main barriers: resources, training, impact, personal harms.

Revealed overarching concerns about authenticity, agency, and functionality.

Discussed design considerations for AI tools to support counterspeakers.

Abstract

Counterspeech, i.e., direct responses against hate speech, has become an important tool to address the increasing amount of hate online while avoiding censorship. Although AI has been proposed to help scale up counterspeech efforts, this raises questions of how exactly AI could assist in this process, since counterspeech is a deeply empathetic and agentic process for those involved. In this work, we aim to answer this question, by conducting in-depth interviews with 10 extensively experienced counterspeakers and a large scale public survey with 342 everyday social media users. In participant responses, we identified four main types of barriers and AI needs related to resources, training, impact, and personal harms. However, our results also revealed overarching concerns of authenticity, agency, and functionality in using AI tools for counterspeech. To conclude, we discuss considerations for designing AI assistants that lower counterspeaking barriers without jeopardizing its meaning and purpose.