Plain-language definitions of the AI terms that come up in product and design work, from tokens and context windows to agents, evals, and prompt injection.
Handoff willingness, flexibility, proactivity, emotional responsiveness, and transparency help you build trustworthy AI chatbots that guide users well.
Unsure where to start? Use this collection of links to our articles and videos to learn about how artificial intelligence works, and how users think about it.
The ELIZA effect describes users' tendency to quickly attribute human characteristics to artificial systems when the interaction feels human-like. This is why people fall in love with AI.
Users quickly attribute human-like characteristics to artificial systems, which reflect their personality back to them. This phenomenon is called the ELIZA effect.
Far from being ‘intelligent’, today’s chatbots guide users through simple linear flows, and our user research shows that they have a hard time whenever users deviate from such flows.
Frequent users of Siri, Alexa, and Google Assistant report attempting low-complexity tasks such as simple fact retrievals, weather forecast, navigation, playing music, setting timers.
User research finds that tightly integrated services with simple and unified design make people use WeChat; mainly through traditional GUI interactions, not a “conversational UI.”
