The Educator Magazine U.K. Sept-Dec 2026 issue - Magazine - Page 26
The rise of Ai
Chatbot engagement
Linguistics and safeguarding
implications
Alex Dave), Safeguarding Lead
at edtech charity LGfL-The National
Grid for Learning
As artificial intelligence becomes increasingly
integrated into the everyday lives of children
and young people, schools are beginning to
observe new forms of online behaviour that
extend beyond conventional safeguarding
models. A growing concern in this area is the
fascination with AI chatbots, where ongoing
interaction with conversational AI may start to
indicate emotional dependence and patterns
of behavioural reliance.
principle: language is not just descriptive, but
behavioural. The way individuals talk about
their experiences can provide insight into
underlying emotional states and potential
vulnerability.
This thought leadership article draws on
collaborative safeguarding work between
Alex Dave, Safeguarding Lead at edtech
charity LGfL- The National Grid for Learning
and Dr Charlotte-Rose Kennedy, Safeguarding
Language Specialist, exploring how linguistic
analysis can help identify early indicators of
risk in how individuals describe and
experience their interaction with AI chatbots.
Why users engage with AI chatbots
A recurring theme across the data is that
individuals often engage with AI chatbots to
meet emotional and social needs that are not
being fully satisfied elsewhere.
The rise of AI chatbot interaction: an
emerging safeguarding risk
According to Vodafone, AI chatbots are
increasingly becoming part of everyday life
for young people, with 81% of children aged
11–16 reporting that they use the technology.
Students commonly turn to these tools
for learning support, companionship,
entertainment, guidance, and informal
conversation. Designed to mimic
human-like dialogue and emotional
responsiveness, these systems can encourage
users to develop a sense of relational
connection with them.
While this undoubtedly enhances and
prolongs engagement, it also introduces
safeguarding complexity. Chatbots are not
always designed with child safety as a primary
focus, and concerns have been raised across
the sector about exposure to inaccurate
responses, inappropriate content, and
potentially harmful interactions.
The safeguarding challenge is therefore not
simply about access to AI tools, but about the
emotional and behavioural impact of
sustained engagement with systems that
mimic human connection.
Linguistic analysis and behavioural insight
Recent linguistic analysis of a large anonymised dataset of forum posts – over
280,000 words – was conducted as part of this
collaborative work, exploring how individuals
describe attempts to reduce or stop their use
of AI chatbots. Drawing on Dr Charlotte-Rose
Kennedy’s expertise in safeguarding
language, the analysis examined the use of
emotional expressions, particularly phrases
such as “I feel”, to identify recurring patterns
in motivation, experience, and withdrawal.
This approach reflects a key safeguarding
Three key themes emerged:
• Why people turn to AI chatbots
• The negative consequences of sustained use
• The challenges of reducing or stopping use.
Individuals describe loneliness, isolation, and
a lack of meaningful connection in offline
environments. Others report using chatbots
as a coping mechanism during periods of
emotional distress or as a way to manage
stress and escape from real-world pressures.
These patterns are particularly relevant in
safeguarding contexts, as they mirror known
indicators of vulnerability such as social
withdrawal and emotional reliance on digital
environments.
Potential negative effects of prolonged AI
chatbot use
The analysis further points to several selfreported negative outcomes associated with
prolonged chatbot use.
These include reduced wellbeing, feelings
of shame, and concerns about loss of
control over usage. Some individuals describe
difficulties concentrating, reduced
motivation, and a perceived decline in
real-world social engagement.
From a safeguarding perspective, these
indicators are significant where digital
behaviour begins to correlate with emotional
or functional impact in everyday life.
Struggles with chatbot disengagement
A further theme is the challenges individuals
face when trying to reduce or cease AI
chatbot use. This has been found to be a
design feature of some sites which mimic
controlling behaviours within human
relationships.
Because emotional attachment may develop
over time, disengagement is often described
in relational terms, with users expressing
feelings similar to loss or separation. This can
be accompanied by loneliness, low mood,
and repeated return to the platform despite
intentions to stop.
These patterns suggest that for some users,
AI chatbot use moves beyond functional
Dr Charlotte-Rose Kennedy,
Safeguarding Language
Specialist.
interaction into emotionally reinforced
behaviour
Interpreting behaviour in context
For schools nationwide these findings
reinforce the importance of contextual
safeguarding approaches that consider not
just what young people are doing online,
but why they are doing it.
In practice, this means combining
professional judgement with a broader
understanding of digital behaviour patterns,
rather than relying on isolated indicators.
Within this wider safeguarding ecosystem,
filtering and monitoring tools such as Senso.
cloud are used in many LGfL schools to
support DSLs in interpreting digital activity
patterns. This sits within a broader framework
where technology is used to surface potential
concerns, but always alongside human
oversight, school context, and existing
safeguarding procedures.
Conclusion
The rise of AI is reshaping young people’s
communication, relationships, and helpseeking behaviours. With chatbot use
increasingly woven into everyday digital
experiences, safeguarding frameworks must
adapt to capture not just behavioural change,
but also the emotional and linguistic
indicators that emerge alongside it.
Linguistic analysis offers one way of
deepening this understanding, helping
schools interpret patterns that may
otherwise go unnoticed. When combined
with contextual safeguarding practice, it
supports, more effective preventative work
as well as earlier recognition of risk and more
informed decision-making.
The priority is clear: to ensure schools are
equipped with the insight and confidence to
respond to emerging digital behaviours in a
way that is evidence-based, proportionate,
and rooted in safeguarding best practice.
Box out:
In order to support schools in responding to
these emerging challenges, LGfL’s free AI
Policy Toolkit provides practical guidance
on key considerations including filtering,
monitoring, and the safe deployment of
AI technologies in education settings. It
brings together safeguarding, technical, and
leadership perspectives to help schools take
a structured and proportionate approach to
managing risk. By aligning policy, practice,
and oversight, the toolkit supports schools
in embedding AI safely while remaining
responsive to the evolving digital behaviours
of children and young people.
