iPads, MakerEd and More in Education

As many teachers make the transition back into classes after the holidays, quite a few have plans to update lessons to include segments that introduce data science concepts. Why, you ask?

According to a LinkedIn report published last week, the most promising job in the US in 2019 is data scientist. And if you search for the top “hard skills” needed for 2019, data science is often in the top 10.

Data science, applied computation, predictive analytics… no matter what you call it, in a nutshell it’s gathering insight from data through analysis and knowing what questions to ask to get the right answers. As technology continues to advance, the career landscape also continues to evolve with a greater emphasis on data—so data science has quickly become an essential skill that’s popping up in all sorts of careers, including engineering, business, astronomy, athletics, marketing, economics, farming, meteorology, urban planning, sociology and nursing.

Everyone loves data. Everyone loves talking like they understand data. Everyone loves using ML and AI buzzwords — but many times they are just talking, hoping they are using them in the correct context, but still usually just throwing them out there into the open. Which of course is also important. That’s how you sell your product. That’s how one shows that their company is the top in their field, that they have high-end abilities, and of course, that they are the best at what they do.

What I have learned along the way, is that really learning to share and explain a “data story” is hard work.

It’s the bottom of the ninth with two outs and it’s all tied up. You’ve got a runner on first base and you need to decide who you’re sending to the plate. You have a player with a stellar batting average, a player reliable for drawing walks and one who promises they can win it all for you—who do you play?

In the fall of 2002, the Oakland Athletics shattered a 55-year-old record with twenty consecutive games won. The A’s accomplished this on a shoestring budget and despite losing three of their best players at the start of the season. How, you ask? By applying rich data analysis to the sport, a practice known as sabermetrics. When we set out to design an engaging kickball unit for our middle school students, we asked ourselves how we could learn from the 2002 A’s.

In short, we wondered how we could combine data analysis, computational thinking and kickball to make the P.E. experience more personal, more academically rigorous and more inclusive to students of all athletic abilities.

Bias is a fundamental human characteristic. We are all biased, by our very nature, and every day we make countless decisions based on our gut feelings. We all have preconceived ideas, prejudices, and opinions. And that is fine, as long as we recognize it and take responsibility for it.

The fundamental promise of AI, besides the dramatic increase of data processing power and business efficiency, is to help reduce the conscious or unconscious bias of human decisions. At the end of the day, this is what we expect from algorithms, isn’t it? Objectivity, mathematical detachment rather than fuzzy emotions, fact-based rather than instinctive decisions. Algorithms are supposed to alert people to their cognitive blind spots, so they can make more accurate, unbiased decisions.

At least that’s the theory…

"Just as many other technological advancements, Artificial Intelligence came to our lives from the pages of fairy tales and fiction books (think of the Tinman from The Wizard of Oz or Maria from Metropolis). People dreamt about machines able to solve problems and release some of the fast-compounding pressure of the 21st century.

Less than 70 years from the day when the very term Artificial Intelligence came into existence, it’s become an integral part of the most demanding and fast-paced industries. Forward-thinking executive managers and business owners actively explore new AI use in finance and other areas to get a competitive edge on the market.

More often than not, we don’t realize how much Artificial Intelligence is involved in our day-to-day life."