Project description
Humans and AI in the fight against digital hate and disinformation
In 2016, the European Commission launched the Code of Conduct together with major IT companies in an effort to respond rapidly to the proliferation of hate speech online. In this fight against online hate speech, the EU-funded AI4Dignity project will investigate the role of artificial intelligence (AI). While AI can be used to detect, decelerate and remove online extreme speech, this hinges on the quality, scope and inclusivity of training data sets. There is also a lack of procedural guidelines and frameworks. As such, the project will develop an innovative solution of collaborative bottom-up coding. It will move beyond keyword-based detection systems. The AI4Dignity solution will use a community-based classification approach that identifies fact checkers as critical human interlocutors in the fight against digital hate and disinformation.
Objective
Online hate speech and disinformation have emerged as a major problem for democratic societies worldwide. Governments, companies and civil society groups have responded to this phenomenon by increasingly turning to Artificial Intelligence (AI) as a tool that can detect, decelerate and remove online extreme speech. However, such efforts confront many challenges. One of the key challenges is the quality, scope, and inclusivity of training data sets. The second challenge is the lack of procedural guidelines and frameworks that can bring cultural contextualization to these systems. Lack of cultural contextualization has resulted in false positives, over-application and systemic bias. The ongoing ERC project has identified the need for a global comparative framework in AI-assisted solutions in order to address cultural variation, since there is no catch-all algorithm that can work for different contexts. Following this, the proposed project will address major challenges facing AI assisted extreme speech moderation by developing an innovative solution of collaborative bottom-up coding. The model, “AI4Dignity”, moves beyond keyword-based detection systems by pioneering a community-based classification approach. It identifies fact-checkers as critical human interlocutors who can bring cultural contextualization to AI-assisted speech moderation in a meaningful and feasible manner. AI4Dignity will be a significant step towards setting procedural benchmarks to operationalize “the human in the loop” principle and bring inclusive training datasets for AI systems tackling urgent issues of digital hate and disinformation.
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Programme(s)
Funding Scheme
ERC-POC - Proof of Concept GrantHost institution
80539 MUNCHEN
Germany