Family co-play of video games is common and linked to family closeness and positive intergenerational interaction. Mixed-age co-play exposes controller-skill gaps that cause frustration and exclusion, yet most party games lack ability-inclusive assists. We explore ability-inclusive co-play for unmodified party and family games: We contribute (1) an open-source controller-skills benchmark; (2) the first lifespan study combining both broad age and deep skill coverage (ages 6–90; n=80; six skills), showing that gaps between children and older adults are skill-specific rather than uniform; (3) we present PartyAssist, a real-time, computer-vision-to-input system that detects on-screen state and injects micro controller-input assistance without altering game code; (4) in a feasibility study with 16 mixed-skill dyads (n=32; assisted player <10 or >50), assistance improved children’s survival time and success rate while remaining largely unnoticed and was viewed positively, while older adults detected assistance and reported mixed views. Interviews surfaced socially-considerate design nuances and implications to inform future designs to support ability-inclusive co-play across the lifespan.
ACM CHI Conference on Human Factors in Computing Systems