How can AI be used to identify harmful content?
Background
Although there is already material evidence on the types of serious harms individuals encounter online, there still remain a number of emerging harms, where the evidence base is still yet to mature (e.g. epilepsy trolling, online animal abuse). SOH would like to close this significant gap in understanding the impact of encountering different types of serious harms online and understanding the best approaches to measuring the impact of the Online Safety legislation.
SOH highlights the importance of Media Literacy in the digital age and asks for further studies to uncover barriers to engagement as well as the effectiveness of DSIT programmes. This issue closely relates to Counter-Disinformation interventions, which requires evidence for its effect on bystanders, topic specific disinformation and what tools can be used to combat this issue.
Research on Safety Technology would greatly develop SOH’s understanding of the relationship that DSIT online safety objectives have with the technology market today. A primary focus lands on improving Age Assurance (AA) measures. This includes ensuring transparency and assessing opportunities for the sector.
Next steps
If you are keen to register your interest in working and connecting with DSIT Digital Technology and Telecoms Group and/or submitting evidence, then please complete the DSIT-ARI Evidence survey - https://dsit.qualtrics.com/jfe/form/SV_cDfmK2OukVAnirs.
Please view full details: https://www.gov.uk/government/publications/department-for-science-innovation-and-technology-areas-of-research-interest/dsit-areas-of-research-interest-2024
Source
This question was published as part of the set of ARIs in this document:
Topics
Related UKRI funded projects
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An innovative, AI-driven application that helps users assess/action information pollution for social media content.
Sway is a UK-based social media safety technology SME with a core project team of Mike Bennett (CEO and serial entrepreneur), Daniela Fernandez (CXO and entrepreneur) and Alan Simpson (CTO and digital transformation stra...
Funded by: Innovate UK
Lead research organisation: SWAY AS LIMITED
Why might this be relevant?
The project aims to help users assess and take action against information pollution on social media, which is relevant to identifying harmful content.
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PrivacyEye: Controlling Harmful Multimedia Sharing Among Children
The increasing use of electronic devices and online applications among children in the UK has raised significant concerns about their online safety. Nearly 90% of children aged 0-18 go online daily, with those aged 5-15 ...
Funded by: Innovate UK
Lead research organisation: DE MONTFORT UNIVERSITY
Why might this be relevant?
The project addresses harmful multimedia sharing among children, aligning with the question's focus on identifying harmful content online.
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Shear: The next generation of video understanding technology to automate content moderation across the internet.
In this project, Unitary Ltd and Oxford University will develop novel algorithms to address the core challenges of video moderation. This technology will form Unitary's new product, _Shear_, to automatically detect harmf...
Funded by: Innovate UK
Lead research organisation: UNITARY LTD
Why might this be relevant?
The project focuses on developing AI technology for automated content moderation, specifically targeting harmful video content online, which directly addresses the question of using AI to identify harmful content.