Goal Setting, Nudges and Machine Learning

Interesting study-based results.   Now should the same approach be used for training and goal setting of machine learning?   Not just the ML of current systems, but  machine 'learning' in general.   It would seem that the 'nudge' theory would seem to say its better to set many, easier goals, than big jumps.  Why not here?   Is it because human feedback is different?  A fundamental question, I think.  Especially if the feedback can be more conversational that one-step.

Why You Should Stop Setting Easy Goals
Amitava Chattopadhyay, Antonios Stamatogiannakis, Dipankar Chakravarti in the HBR

When setting team goals, many managers feel that they must maintain a tricky balance between setting targets high enough to achieve impressive results and setting them low enough to keep the troops happy. But the assumption that employees are more likely to welcome lower goals doesn’t stand up to scrutiny. In fact, our research indicates that in some situations people perceive higher goals as easier to attain than lower ones — and even when that’s not the case, they still can find those more challenging goals more appealing.

In a series of studies we describe in our latest paper, we tested how people perceive goals by asking participants on Amazon’s crowdsourcing marketplace, known as Mechanical Turk, to rate the difficulty and appeal of targets set at various levels and across spheres from sports performance and GPA to weight loss and personal savings. We asked about both “status quo” goals, in which the target remained set at a baseline level similar to recent performance, and “improvement goals” in which the target was set higher than the baseline by varying degrees. .... "