• Smart Assistants: AI-powered assistants like Siri, Google Assistant, and Alexa use context to provide relevant information and perform tasks. For example, they can suggest leaving early for an appointment due to traffic conditions.
• Recommendation Systems: Netflix, Amazon, and Spotify use context-aware AI to recommend content based on user preferences, time of day, and previous behavior.
• Smart Homes: Home automation systems adjust lighting, temperature, and security settings based on the user’s location and activity.
• Transportation: Navigation apps like Google Maps provide real-time traffic updates and suggest optimal routes based on current conditions.

Moving Gen AI into a ‘shaping of experience’ role

Generative AI can enhance context sensitivity in several ways by dynamically adapting content, interfaces, and responses to a user’s specific needs, environment, and behavior. Here are six areas it can contribute to a more context-aware experience:

1. Personalization at Scale

Generative AI can tailor content and interactions based on a user’s past behavior, preferences, and real-time data. By analyzing patterns in user input and contextual cues (such as location, time of day, device used, or even emotional state), AI can generate personalized recommendations, messages, or features that are most relevant at that moment.

For example, Spotify could help you discover new material by analyzing other songs with a feeling you like from a specific song (based on lyrics, mood, tempo, rhythm, sentiment) and find similar songs.

2. Dynamic and Real-Time Adaptation

Context can change rapidly, and generative AI enables products to adapt in real-time. For instance, AI can adjust the complexity of information presented based on a user’s experience level or the device being used. If a user is on mobile vs. desktop, the interface can shift to prioritize key functions and limit unnecessary interactions. Similarly, in smart homes, generative AI can adjust lighting, music, or temperature based on time of day, weather, or using predictive modeling… “We’ve been listening to upbeat songs; here’s more.”

3. Natural Language Understanding and Conversational AI

Generative AI, especially in the form of NLP (Natural Language Processing) models, can improve context-sensitive conversations. In chatbots and voice assistants, AI can track the context of a conversation and respond more appropriately. Instead of giving generic answers, it can remember what the user has said in the past, recognize mood or urgency, and tailor responses accordingly. This allows for more meaningful, human-like interactions.

4. Context-Aware Content Creation

For businesses, generative AI can create marketing materials, website content, or emails that are highly personalized based on user context. If AI knows a user is browsing a website from a particular geographic region, it can generate localized product descriptions or promotions. Similarly, AI can write tailored follow-up emails after a user interaction based on their unique customer journey.

5. Predictive Contextual Suggestions

Generative AI can analyze data to predict a user’s next action based on contextual signals. For example, in navigation apps, AI can route based on traffic, time of day, user behavior, and favorite routes. In productivity tools, generative AI can suggest document templates or specific functions based on the user’s recent tasks or work patterns.

For example, maps default to the “fastest route,” which in many cases is exactly the same as the slow option (by 5 minutes often). Yet, the busy road is the forced default. By tapping “Scenic Route,” it could default to that. Or if you ask it to find good coffee shops, places for kids, or museums- the map could suggest a more “curated” route instead of assuming you are in a hurry to cross Silicon Valley through traffic every day– as it does currently.

6. Emotion or Mood Sensing & Adapting

By analyzing tone, language, and other contextual factors, generative AI can provide emotionally aware responses. This is especially useful in customer service or mental health apps, where understanding user emotions and adjusting the conversation tone can significantly improve the user experience. AI can potentially sense frustration, confusion, or satisfaction and adapt its approach, leading to more sensitive and appropriate interactions.

Big idea: AI as context-shaping agent

Generative AI can significantly enhance context sensitivity by making experiences more adaptive, personalized, and desirable. With context awareness, UX can become more meaningful and relevant for users. This includes adapting content, predicting needs, and improving the quality of an experience.

Hint: Discovering your context-sensing potential for AI starts by exploring contextual usage scenarios. Join me, Frank Spillers, for a 6 hour, 3 part workshop starting Sept 11th, 2024 on Doing UX Research alongside AI