How will AI affect existing kinds of harmful online content (e.g. online abuse, scams) and what new kinds of online harmful content might it give rise to?
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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AI Safety Platform: Generative AI and Cybersecurity Training SaaS for Schools and Families
**Problem statement:** The rapid rise of **generative AI** has introduced **unprecedented cybersecurity risks**, particularly for students and families. **Deepfakes, AI-driven scams, misinformation, identity theft, and c...
Funded by: Innovate UK
Lead research organisation: UNIVERSITY OF EAST LONDON
Why might this be relevant?
The project addresses AI-driven cybersecurity risks, deepfakes, scams, and cyberbullying, which are relevant to the question on the impact of AI on harmful online 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 focuses on controlling harmful multimedia sharing among children, addressing concerns about online safety, cyberbullying, and exposure to harmful content.
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Equally Safe Online
We address the timely topic of online gender-based violence (GBV): Almost 1 in every 2 women and non-binary people (46%) reported experiencing online abuse since the beginning of COVID-19 (Glitch report, 2020). Our aim i...
Funded by: EPSRC
Lead research organisation: Heriot-Watt University
Why might this be relevant?
The project specifically addresses online gender-based violence and aims to create safer online spaces through advanced Machine Learning algorithms.