“This is not the familiar question of whether our machines will put us all out of work. In fact, the question is whether we will start doing more and more intellectual work for free or for barter, becoming more like our ancestors. Instead of producing food or housing for ourselves or for barter, we will be producing content and amusement for one another, without engaging in explicit (taxable) financial exchange. Yes, there is a so-called gift economy, but there is also an attention market that may not be fungible or priced – a distributed, many-to-many economy that harks back to the old days.”
“Indeed, the “art” of business has become more important as the “science” grows ubiquitous. As Big Data and sophisticated analytical tools allow us to make our processes more efficient, intuition and creativity are fast becoming the only differentiating factors among competitors. Like any “soft asset,” these qualities cannot be exploited, only explored. And like artists, innovators must cultivate creative habits to see the world afresh and create something new.
How do artists think and behave? Here are 12 traits”
Makes sense. How is STEM visualized/appreciated? Via design principles, graphics and such.
“Artists and designers bring STEM to life: As we all know, STEM is so important — but on its own, sadly it’s not working. Despite all of the resources being invested in it, the word is exactly what’s wrong with the concept. It doesn’t inspire, energize or engage the youth whom it is ultimately intended to benefit; hence our nation is falling desperately behind.”
Good article on 3-D printing and MakerBot’s quest to bring 3-D printing/printers to the masses.
“But nothing MakerBot has ever built looks like the new printer these workers are currently constructing. The Replicator 2 isn’t a kit; it doesn’t require a weekend of wrestling with software that makes Linux look easy. Instead, it’s driven by a simple desktop application, and it will allow you to turn CAD files into physical things as easily as printing a photo.”
Good to know: “Two major trends could open the door to robotic care givers that help senior citizens stay in their homes longer. First, robots are getting more people friendly. And second: people are getting more robot friendly.”
Michael shared this during a conversation we were having on zombie projects. We’ve all seen ’em…
“Walking-dead IT projects, also known as zombies, should be killed off — putting these suckers out of their misery is the right thing to do. Of course, various techniques exist to repair failing projects, such as restart methodologies and live-goat sacrifice, which was pioneered by Nepal Airlines. Nonetheless, there are times when the zombies must die.”
Good example of digital strategy, role of CTO, and technology-driven innovation.
“…The next thing King knew, Walmart arranged for him to join a videoconference with CEO Mike Duke. “It was the strangest thing,” King says. “Mike’s office in Bentonville is the original one that Sam Walton had, complete with 1970s wood paneling. I was looking at this video, thinking, Where is this place?”
Over the next 45 minutes, though, Duke made what King calls an irresistible pitch. After years of seeing his company lag online, Duke swore that digital was now a priority for Walmart. Duke had restructured the company, placing e-commerce on equal footing with Walmart’s other, much larger divisions. He had made serious investments in high-tech talent, acquiring several startups. One, a 65-person social media firm called Kosmix with expertise in search and analytics, was the impetus for Walmart rechristening its Valley operations “@WalmartLabs.” Duke was looking for people who would revive the company’s sites and services, and energize its entire culture. He hoped to turn a company famous for rigid, coldly effective business processes into one that’s flexible, experimental, and entrepreneurial. In other words, Duke wanted to inject a bit of Silicon Valley into Bentonville, Arkansas.”
“We rightfully add safety systems to things like planes and oil rigs, and hedge the bets of major banks, in an effort to encourage them to run safely yet ever-more efficiently. Each of these safety features, however, also increases the complexity of the whole. Add enough of them, and soon these otherwise beneficial features become potential sources of risk themselves, as the number of possible interactions — both anticipated and unanticipated — between various components becomes incomprehensibly large.
This, in turn, amplifies uncertainty when things go wrong, making crises harder to correct: Is that flashing alert signaling a genuine emergency? Is it a false alarm? Or is it the result of some complex interaction nobody has ever seen before? Imagine facing a dozen such alerts simultaneously, and having to decide what’s true and false about all of them at the same time. Imagine further that, if you choose incorrectly, you will push the system into an unrecoverable catastrophe. Now, give yourself just a few seconds to make the right choice. How much should you be blamed if you make the wrong one?
CalTech system scientist John Doyle has coined a term for such systems: he calls them Robust-Yet-Fragile — and one of their hallmark features is that they are good at dealing with anticipated threats, but terrible at dealing with unanticipated ones. As the complexity of these systems grow, both the sources and severity of possible disruptions increases, even as the size required for potential ‘triggering events’ decreases — it can take only a tiny event, at the wrong place or at the wrong time, to spark a calamity.”
Love this: “mean time to meddling”… “Instant access and cloud has compressed the “mean time to meddling” to milliseconds for micromanagers.”
“Every manager needs to review their last 100 network communications — text, email, SharePoint, LinkedIn, etc. — and ask themselves: What’s the mix between messages that might be interpreted as management, micromanagement and mentoring? Am I giving in to temptations that will corrode trust? Or am I using these technologies in a way that brings out my better managerial self?”
The world, and the data within, is messy. Good piece by Irving Wladawsky-Berger:
“In discipline after discipline, we are beginning to learn how to deal with the very messy world of big data and complex systems, and how to best apply our learning to make good decisions and good predictions. One of the hardest parts of that learning is the need to let go of our preconceived notions of scientific determinism and get used to living in a world of probabilities, uncertainties and subjective realities.”
No WSJ account? Cross-posted to his blog: http://blog.irvingwb.com/blog/2012/12/big-data-complex-systems-and-quantum-mechanics.html