Emotional AI and Adaptive Content
Posted: Sat May 24, 2025 8:33 am
Once emotional states are detected, emotional AI enables systems to respond in a dynamically tailored way.
a. Emotion-Aware Advertising
Programmatic advertising can now be emotion-sensitive. Ads are no longer just served based on interests or behaviors—they are now matched to current moods. A sad mood? Show a comforting ad. Excited and happy? Promote celebratory purchases.
Spotify, for instance, uses emotional AI to tailor playlists vietnam phone number list based on the listener’s mood—detected through song choice, time of day, and listening habits. Ads embedded in these playlists often align with the emotional tone of the music.
b. Content Personalization
Emotionally adaptive content is used in UI/UX design, newsfeeds, gaming, and e-learning platforms. A learner frustrated with a difficult topic might receive simpler content or encouraging messages. A gamer showing signs of boredom could be offered a more intense challenge.
YouTube and TikTok tweak recommendation engines in response to user mood inferred through interaction speed, video replays, pauses, or expressions captured via phone cameras (if permitted).
c. User Interface Adaptation
a. Emotion-Aware Advertising
Programmatic advertising can now be emotion-sensitive. Ads are no longer just served based on interests or behaviors—they are now matched to current moods. A sad mood? Show a comforting ad. Excited and happy? Promote celebratory purchases.
Spotify, for instance, uses emotional AI to tailor playlists vietnam phone number list based on the listener’s mood—detected through song choice, time of day, and listening habits. Ads embedded in these playlists often align with the emotional tone of the music.
b. Content Personalization
Emotionally adaptive content is used in UI/UX design, newsfeeds, gaming, and e-learning platforms. A learner frustrated with a difficult topic might receive simpler content or encouraging messages. A gamer showing signs of boredom could be offered a more intense challenge.
YouTube and TikTok tweak recommendation engines in response to user mood inferred through interaction speed, video replays, pauses, or expressions captured via phone cameras (if permitted).
c. User Interface Adaptation