The rise of technologies like generative AI is transforming the very nature of our digital spaces. This presents a challenge for DSLs, who are required by KCSIE to understand online threats and protect students from them. With this in mind, Smoothwall has put together 'Emerging Challenges' - a series of quick reference articles to help safeguarders understand the key digital safety trends they need to know.
This article covers machine drift - a digital risk that is becoming more prevalent as we increasingly rely on technology powered by machine learning algorithms.What is machine drift?
Machine drift occurs when algorithms and information used to build certain technology inadvertently exposes young people to problematic content as they continue to engage with it.
For example, a child may begin looking at age-appropriate video content around a computer game they enjoy. However, as they interact with more videos, increasingly inappropriate content is recommended to them, as the algorithm behind the platform makes recommendations based on the preferences of previous users with similar interests.
Current research shows machine drift is a relevant and real-time concern for today’s students. One recent example shows that children are just three clicks away from adult content on platforms like YouTube.
At the same time, graphic content driven by geopolitical tensions has intensified over the past year, spreading rapidly on social media platforms like TikTok. As user-generated content continues to proliferate online, machine drift will be a key enabler in driving the influence of questionable political agendas, unhealthy trends and disinformation.
How to remedy machine drift
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Educate students on the importance of digital literacy
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Encourage students to actively evaluate the credibility and reliability of any online sources they encounter or engage with
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Minimise inadvertent access to harmful content with digital safeguarding solutions
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Implement robust filtering and monitoring systems that protect pupils from a majority of online risks and highlight areas where inappropriate content may be accessible, so that schools can act accordingly
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Regularly review and update these systems to ensure they have the capacity to quickly adapt to emerging trends like machine drift
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Invest in tools with real-time, content-aware capabilities
- Solutions with the power to analyse content in real-time can help safeguarders identify instances of machine drift as it happens, empowering them to take action before harmful content is shown
To learn more about emerging online risks impacting schools, as well as practical steps to recognise and address them, download our free whitepaper: Student Digital Wellbeing: UK State of the Nation Report 2024
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