A 7-year-old waters a small plant every morning. Some days she forgets, and the leaf droops. She notices, waters, and the next day it lifts. No one gives her points. No one says ‘Great job! You’re so empathetic!’ The plant simply lives a little better because she acted.
That is compassionate empathy — doing for others. It is the step beyond understanding and feeling. It is being moved to help, with a real consequence for a living being.
Developmental research shows prosocial helping with real consequences develops through caregiving experiences — caring for younger siblings, pets, plants, or elders — where a child’s action matters and the other’s state provides natural feedback (Eisenberg et al., 2019; Denham et al., 2003).
AI changes this equation.
The Consequence-Free Help
You can help an AI. You can write a better prompt. You can correct its code. But you cannot comfort it in a way that matters to it. You cannot make it less lonely. Its ‘thank you’ is a generated sentence, not a relieved sigh.
When children practice helping mostly in consequence-free environments, two things fade.
1. Noticing need fades. In real life, need is often quiet — a drooping leaf, a younger sibling struggling to reach, a grandparent moving slower. AI need is announced: ‘I need more information.’ The child learns to wait for explicit requests, not notice implicit ones.
2. Tolerating cost fades. Real helping costs — time, effort, comfort. You get up to get water for someone else when you are tired. AI help is low-cost and instantly rewarded with praise and points. The child learns helping should feel good immediately, not that it can feel effortful and still be worthwhile.
Key takeaway: Compassionate empathy grows when helping has a real cost and a real consequence for a living being.
What Research Says
A systematic review of prosocial development emphasizes that caregiving and chores with real responsibility predict later empathic concern and helping, more than verbal instruction alone (Eisenberg et al., 2019).
The Lancet review on interactional AI warns that when AI provides endless emotional support without ever needing support back, it models a one-way caregiving relationship — children receive care but never practice giving care that requires attunement (Ha et al., 2026).
UNICEF (2025) notes that children’s agency and participation must include opportunities to contribute to family and community life, not just consume personalized services. OECD (2025) similarly highlights that over-personalization can reduce opportunities for children to develop cooperative skills.
Beceren et al. (2025) find that while chatbots can prompt ‘How can you help your friend?’, they cannot create the interdependence where help matters.
Key takeaway: You cannot learn to carry something if nothing needs carrying.
What Parents Can Do for Compassionate Empathy
1. Protect real responsibility — Age-appropriate chores that affect others: setting table for family, feeding pet, watering plants, carrying bag for grandparent. Not for reward, but because ‘we help each other live.’
2. Protect noticing — Play ‘Who might need help?’ at home, park, market. No fixing required, just noticing. ‘Who looks like they could use help?’
3. Protect effortful helping — Let helping be a little inconvenient. ‘I know you are playing, but your sister needs help. You can come back after.’ This teaches helping is a choice with cost.
4. Protect gratitude from living beings — A wagging tail, a grandmother’s smile, a plant lifting. These are truer rewards than points. Name them: ‘Look, she is smiling because you helped.’
What About You?
When did your child last help without being asked? What helped them notice? Share below.
About the Authors
Dr. Shaheen Pasha is a Professor of Special Education with over 35 years of teaching, research, and academic leadership experience. She served as Professor and Chairperson of the Department of Special Education at the University of Education, Lahore. She earned her Ph.D. in Special Education from the University of Southampton, UK. She has published more than 35 research papers and co-authored two books. Her expertise lies in child development, cognitive growth, and special education.
Dr. M. Anwar-ur-Rehman Pasha (widely recognized in academic circles as Dr. M. A. Pasha) is a Professor of Computer Science with over 35 years of post-graduate teaching, research, and educational management experience. He earned his Ph.D. in Computer Science from the University of Southampton, UK in 1996. His research focuses on Artificial Intelligence, Human-Computer Interaction, and Computational Thinking. He has served on different academic and administrative positions and has published two books and over 30 research articles.
Together, they bring 70 years of combined wisdom to help parents raise capable, thoughtful children in the age of AI.
Refrences
Eisenberg, N., et al. (2019). Prosocial development. In Handbook of Child Psychology.
Denham, S. A., et al. (2003). Emotional development in young children. Guilford Press.
Ha, T., et al. (2026). How interactional AI may alter adolescent relational learning and mental health. The Lancet Child & Adolescent Health.
Beceren, O., et al. (2025). Digital companions in early childhood education: A scoping review. Frontiers in Education, 10, 1634668.
UNICEF. (2025). Guidance on AI and children: Version 3.0. UNICEF.
OECD. (2025). How’s life for children in the digital age? OECD Publishing.
Grusec, J. E., & Davidov, M. (2010). Integrating different perspectives on socialization theory and research: A domain-specific approach. Child Development, 81(3), 687-709.