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Measuring Autonomy in Self-Driving Cars and People [Management
Posted on May 11, 2016 @ 07:25:00 AM by Paul Meagher

I was browsing a recent article by NVIDIA researchers called End to End Learning for Self-Driving Cars and was intrigued by the simple metric they were using to evaluate the performance of their self-driving algorithm. The metric is called "Autonomy" and is based upon measuring how much time the driver spends intervening to correct driving performance over a given amount of driving time. "Autonomy" is measured with the following simple formula:

Autonomy = ( 1 - Intervention Duration/Task Duration ) * 100

The inverse of the "Autonomy" score might be called the "Helping" score.

So perhaps in self-driving vehicles in the future they will be rated by their degree of autonomy or perhaps they will operate like an advanced form of cruise control where we have to potentially intervene every so often and, as such, we will want to keep track of our vehicles current autonomy score. Maybe on icy roads the autonomy score goes way down but driving through the prairies on a nice day it is at 100% like it is in this screenshot of the NVIDIA dashboard.

Autonomy in the workplace is measured by researchers in terms of a worker's freedom to schedule and choose their work. Not surprisingly, they have discovered that workers with more autonomy have more job satisfaction. Personally, I would be more interested in measuring worker autonomy in the way that they measure autonomy in self-driving cars so that we might have answers to questions about the variance in worker autonomy as a function of various factors (e.g., individual differences, time on job, type of work, autonomy scores in the past, etc...). Likewise, we might study child development using an autonomy metric like this. Take a task and ask your kids to do it and, depending on age or other factors, you might find yourself intervening to help with such frequency and duration that you wonder why you asked them to help you in the first place. Other kids might prefer to try it themselves and don't ask for much help. Are there individual differences in preferences for working autonomously? Does it correlate with measures of introversion/extroversion?

I think these self-driving car researchers are onto something with this autonomy score. It offers a nice simple formula we can use to reason about an important aspect of worker performance; namely, the amount of intervention that is required to help them carry out a work assignment.

Incidentally, you might wonder why graphics chip manufacturer NVIDIA is doing research on self-driving cars. The popular "deep learning" technique they are using for their algorithm relies critically on the parallel processing that Graphics Processing Units (GPU's) provide. The popularity of deep learning is good news for NVIDIA and it looks like they are not content to just manufacture more hardware for deep learning algorithms but also want to play a role designing some of the deep learning algorithms that will run on their chips. Deep learning algorithms harness the power of many GPUs which NVIDIA has no shortage of.

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