Paper, logos and cognac: Sweet Spot Dec 12 2017

It’s the Christmas edition of the Sweet Spot! That wraps up 12 months of, what I hope, have been inspiring and entertaining things to read/watch/listen to, all somehow related to helping people see and understand data. For the final issue of the year, some fun stuff. Still relevant. But fun. See you in 2018!

Secrets to measuring a piece of paper (5 min video, Numberphile)

Numberphile is one of my favourite YouTube channels. This video, by the wonderful Cliff Stoll, provides a brilliant gotcha to teach you a lesson about data collection. It’s a simple lesson but one with big implications: how do people learn to trust their data? Should they trust it blindly? Are they measuring things correctly?

A New Master Blend: Giorgia Lupi and Kaki King (3 min video, Hennessy)

Dataviz, music and cognac: a Christmas gift seemingly designed for the data geek in your life. This is a great project from three inspiring people.

Branded in Memory (15 min read, Signs.com)

Our visual system is the most powerful of our senses, but our brain’s a little lazy and doesn’t remember everything with complete accuracy. This campaign from Signs.com asked people to draw logos. The results are really interesting, and they did some great data analysis and storytelling with the results. (shared by Louis Archer in Product Marketing)

Sweet Spot Dec 1: Visicalc, Excel, and Planet-Sized Data

A Spreadsheet Way of Knowledge (20 min read, Backchannel)

“A virtual cult of the spreadsheet has formed, complete with gurus and initiates, detailed lore, arcane rituals – and an unshakable belief that the way the world works can be embodied in rows and columns of numbers and formulas.” That’s my favourite quote from this piece celebrating October 17’s Spreadsheet day (marking the 35th anniversary of Visicalc. When Tableau is 35yrs old, will people look back and reflect in the same way? (That’s 2038, by the way!)

Meet the Spreadsheet That Can Solve NYC Transit (10 min read, Vice Motherboard)

Clearly there’s life in the old spreadsheet! This article strikes an almost romantic tone as it describes the depth and complexity of a spreadsheet that models NYC’s transport system. Read it and marvel at how far we’ve come with Tableau. I’m amazed at how this is so anachronistic and yet, somehow, appropriate? Go download the spreadsheet itself and marvel at the charts, and the maintenance nightmare this must be. Surley we could model this with a good database and Tableau?

Mission One Complete! (5 min read/watch)

Shall we map the entire world, every day? Why yes, why not? We’ll need a bunch of our own satellites to create 1.4 million images daily (that’s 6 petabytes of data, each day!). That’s what Planet did. Now they’ve built it, think of the possibilities of this dataset. Their promo video is crazy: imagine measuring a country’s economy by measuring the number of ships in a port each day? Or tracking natural disasters more accurately than ever before? Sure beats the Excel datasets described above! Their promo video really sets the scene.

Sweet Spot: popping the hype balloon of Artificial Intelligence

Welcome to the Sweet Spot. What’s the Sweet Spot? As Tableau’s Evangelist, I need 3 things to do my job well:

  • I need to know Tableau inside out
  • I need to know my day-to-day job
  • But I also need to know how data impacts and is impacted by the world around us.

Keeping on top of all of these gets me in my Sweet Spot. To stay there, I read a lot of stuff. And now: It’s time to share it, fortnightly, with you all.

This week – 3 things to challenge assumptions about AI (hint: robots ain’t coming to kills us. It’s much more boring, in a good way, than that). Thanks to everyone for feedback on switching up the format of this, and for links you’ve been sending me. I’ll include some of those in future mails.

We need to shift the conversation around AI before Elon Musk dooms us all (3min, Quartz)

Reuters/Bryan Snyder

AI is being hyped more than Big Data was. That is deceptive and misleading; it’s time to refocus.

Why read and share? AI is really exciting. But the media swoons over Musk, Zuckerberg and others and their sci-fi prophecies. This brilliant article by Chad Steelberg urges us to dismiss the hype and focus on the reality. Think about our own roadmap: the Data Interpreter and Recommendations are machine learning, in our products now. That’s not killer robots: it’s just a branch of AI doing mundane (but still amazing) stuff to make our jobs go quicker. Ignore the attention-seeking tech titans, and instead get on with augmenting your own intelligence.

Myths and Facts about Superintelligent AI (4min video, minutephysics)

minutephysics, YouTube

Superintelligence: it’s going to destroy us and take over the galaxy. Or is it? Watch this and decide.

Why you should read and share this? Personally, I think talk of Superintelligence is an interesting philosophical game, but closer to science-fiction than reality. The Future of Life Institute do think about this stuff, though. Watch their overview. Then decide: when talking about AI to customers/colleagues, should you focus on mundane machine learning applications of killer robots? [Hint: it’s not robots.]

The AI revolution (30min podcast from BBC’s The Briefing Room)

Want an overview of the current opportunities and risks of AI? This podcast has them all.

Why you should read and share this? AI is coming, and it’s part of Tableau’s roadmap. It’s up to all of us to educate ourselves about the pros/cons and realities. We all need to get on top of it. This podcast is a superb overview of the benefits and risks from the BBC. It’s balanced and doesn’t succumb to the usual hype. It features lots of diverse opinions, including a great interview with Cathy O’Neil, author of Weapons of Math Destruction.

Happy reading! More to come in a couple of weeks. I’ve been toying with ways to do this (LinkedIn, here, YouTube). What do you think? Do you like the content? How would you best like it delivered?