Deborah Kay, Tech, Code and Edu Twitter buff and Digital Futurist says it best:
A Machine Learning algorithm walked into a bar.
The bartender asked, “What would you like to drink?”
The algorithm replied, “What’s everyone else having?”
We are literally teaching machines what we like everyday through our smart devices and computers. As the name suggests, more data creates smarter algorithms.
In 2016, Google even initiated a ‘Machine Learning Ninja Program’ designed to pull coders from their teams to participate “in a regimen that teaches them the artificial intelligence techniques that will make their products smarter. It even makes the software they create harder to understand.”
This is a perfect example of a ‘Machine Learning’ pun if you will. Humans tricking the very machines they originally created. Clever!
Machine Learning operates like a new switchboard for Higher Education and a new infrastructure for all Enterprise businesses.
EdTech is quickly harnessing learning management tools, game-based platforms and flipped classrooms — including more technology with each coming school year. Basic factors build-out the differentiation on how Machine Learning will affect Education, directly.
Self- driving cars and robots were not part of daily life when the idea of ‘Machine Learning’ was born. A few years ago, predictions were made about how our culture would be taken over by computers. However, this fear has been replaced by the reality that technology is even smarter than anticipated. “…Machine Learning is now successfully applied in our daily life from speech recognition apps in smartphones to YouTube recommendations.”
Keep in mind, technology has subtly been influencing and shaping parts of our culture, behind the scenes, for decades. Take the hip hop music scene of the 90’s, for instance…
Hip hop producer literally humanized a machine, with legendary status.
Watch this amazing story Vlog on the MPC60, the sampling tool of choice for top hip-hop producers in 1990’s influenced music — including the pioneer of this style, J-Dilla. In fact, Dilla’s MPC machine is so famous, it’s featured in the Smithsonian Museum along with Basquiat’s Paintbrushes and Jimi Hendrix’s Guitars.
As technology expands, security and risk also breach the comfort zone affiliated with Machine Learning. Bitcoin, Blockchain, Net Neutrality, and countless other terms highlighting 2017, distinctly advocate the power of Machine Learning and the foundation it is paving for our future.
Perhaps classic opportunity lies in Machine Learning. With enough past data and computational resources, learning algorithms, often produces surprisingly effective predictors of future events.
So are we humanizing the machines, or are the machines simply imitating us?
Over at IEEE, “a growing awareness about the ways AI can discriminate against users if designers don’t take diversity into account” is being reviewed.
However you choose to apply Machine Learning in your life, one thing is certain. Machines and humans are learning to live in harmony and the test of time will show who is teaching who.
Written by: Chelsie Foster @chelsiefoster
Colab: Kati Mac