Why I’ll Never Visit The Gym Without a Data Scientist

December 8, 2015 Kris Hammond

Data Scientist

As originally seen in Computerworld

A favorite New Yorker cartoon of mine shows a man sitting at his breakfast table while a toaster tells him:

“Tim, you’re not crazy, you’re special! You have a magical, talking-toaster, and that’s what makes you special.”

Aside from highlighting the fine line between magic, technology and madness, this cartoon was also a harbinger of things to come.  All the objects and devices that we use are becoming ‘smart,’ meaning we’re going to begin receiving much more feedback on status of our surroundings and activities. Not only is it a future that I want but it's also one that I am passionately committed to building.

Translating Data Into Language

Let me clarify further before you get nervous about the chaos that might ensue as everything from cars to refrigerators to tooth brushes start to chatter endlessly.   

We are entering a world in which everything is going to be metered and monitored. In fact, it is already happening.

The question is now, what will we do with all the data that is generated?

Will we be forced to have weekly dinner parties with data scientists so they can interpret the data that is being produced by our surroundings? Not that I wouldn’t enjoy the good food, wine and company but, in reality, what is the most efficient way to understand all of our data?

I would prefer a future world in which the metered devices are empowered to have insightful, easily understandable and timely communication with us.

For example, I recently was given a peek at a new fitness device from Atlas that tracks your workout activity at a whole new level of detail that I didn’t think was feasible.  Atlas tracks not only the expected metrics of calorie burn, pulse and overall activity but also very specific details such as when you are working with weights and you are loosing your stability (an indication that you are using too much weight).  While quite impressive, the device is gathering more data and advice than the average human being is able to interpret.

So if Atlas is building our exercise devices of the future, does this mean every gym visit will also require a data scientist gym buddy?

A Machine-Based Approach

Taking a step back, it seems that all this data needs to be explained and used to provide advice in a personalized, easy to understand explanations and advice. To attain that level of sophistication, we need a machine-based approach to the collection of the data and the analysis and interpretation.  Additionally, it isn’t enough to just integrate the data with goals and history but the system must also transform the resulting insights into language so we can immediately understand it.

As we experience the beginnings of a data deluge caused by the Internet of Things, we should consider a parallel approach to the large scale metering of devices.  While devices will continue to churn out increasingly complex levels of data regarding performance and status, these same devices should be integrated with automated systems to explain what all the data means and how it factors into our future decision making.

And, then I won’t need to subject a data scientist to my workouts.

Storytelling is the Last Mile in Big Data and Analytics

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