Augmentation over automation

The augmentation approach to AI creates human-AI partnerships instead of replacing people entirely. This view recognizes that humans and machines are good at different things. While automation tries to substitute AI for human tasks, augmentation aims to enhance what humans can do with AI help. This requires understanding different strengths:

• Humans are great at creativity, understanding context, ethical judgment, and empathy.
• AI excels at spotting patterns, staying consistent, working quickly, and remembering information.

Good augmentation builds teamwork systems where AI might suggest options for humans to choose from, highlight important patterns for people to investigate, or handle simple cases while sending complex ones to humans. This approach keeps human judgment in the loop while reducing mental workload. Designing for augmentation means carefully planning how humans and AI hand off tasks to each other without losing important context. It also avoids the "automation cliff" problem, where systems that handle most cases automatically leave humans unprepared for the difficult exceptions they still need to manage.