Differential Skill Gain from AI

A Differential Skill Gain from AI is a performance phenomenon where AI has varying impacts on users of different skill levels.

Context:
- It can amplify the performance of lower-skilled users by providing structured guidance (performance equalization).
- It can enhance the efficiency of higher-skilled users by automating routine tasks (efficiency enhancement).
- It can help organizations design targeted AI support strategies (personalized augmentation).
- It can range from slight to significant effects depending on the skill distribution of users and the tasks involved.
- ...
Example(s):
- Below-average performers showed a 43% improvement with AI, compared to a 17% improvement for top performers.
- AI-augmented tools that level the playing field in knowledge-intensive tasks, enabling less-skilled users to achieve near-parity with experts.
- ...
Counter-Example(s):
- Skill-Neutral AI, which impacts all users equally, regardless of skill level.
- AI Biases, which may disproportionately favor or hinder specific user groups.
See: performance equalization, personalized augmentation.

References

(Dell'Acqua et al., 2023) ⇒ [[::Fabrizio Dell'Acqua]], [[::Edward McFowland III]], [[::Ethan Mollick]], [[::Hila Lifshitz-Assaf]], [[::Katherine C. Kellogg]], [[::Saran Rajendran]], [[::Lisa Krayer]], [[::François Candelon]], and [[::Karim R. Lakhani]]. ([[::2023]]). “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality.” In: Harvard Business School Working Paper Series.
- QUOTE: