Before revision:  In this paper, we show that  in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides major improvements to certain users .
After revision:  In this paper, we show that in some cases it is possible to improve this compatibility-accuracy trade-off relative to a specific user by employing new error functions for the AI updates that personalize the weight updates to be compatible with the user's history of interaction with the system and present experimental results indicating that this approach provides moderate improvements on average (around 20\%) but large improvements for certain users (up to 300\%) .