"Children are not small adults. Pediatric innovation requires more than reduced doses or scaled-down engineering; it demands a fundamental redesign of the UX/UI and the overall approach to children's interactions with AI. We partner with pioneering teams to drive this next frontier—integrating intelligent safeguards that foster resilience and creating adaptive systems that evolve with a child’s development. The decisions we make about AI in child health today will define the human potential and neurodiversity of tomorrow."
Amir Lahav ">
To scientifically investigate how daily interactions with AI systems, social robots, and AI companions influence neuroplasticity and cognitive development from infancy through adolescence.
We’re developing algorithmic “circuit breakers” that adjust how AI engages with children, ensuring interactions foster critical thinking, emotional resilience, and a grounded, realistic understanding of the world.
To fuse continuous biosensor data with adaptive AI, catching early warning signs in preterm infants and newborns before symptoms appear—preventing life-threatening events in NICU and newborn care.
Building fail-safe systems with human oversight protocols, ensuring AI predictions enhance—never replace—human clinical judgment. Rigorous validation across diverse populations to prevent algorithmic bias in life-critical decisions.
To create AI-powered tools that adapt to each child’s unique developmental trajectory, providing personalized support for children with learning disabilities, autism spectrum disorder, ADHD, intellectual disabilities, and developmental delays.
Designing systems that amplify children’s strengths rather than focusing solely on deficits. Ensuring AI recommendations preserve family autonomy and cultural values in treatment decisions.
To design integrated gamified interventions tailored to each child’s developmental stage, emotional needs, personal strengths, and support system—creating reward systems that engage without encouraging digital compulsions.
Engineering adaptive AI systems that evolve across developmental stages to deliver age-appropriate interactions while closing pediatric data representation gaps across cultures and backgrounds.