I’ve noted elsewhere some exciting developments in online education (most interestingly, this year, the opening of MITx, which is worth checking out). This recent article about educational badges available online helps me to formulate, a bit more, a thought that has been gelling in my mind: If lower information-sharing costs help to make distributed systems more realizable in finance, scientific research (see here, too), hardware design and development, etc., etc., then why not in education?
A key quotation:
Employers might prefer a world of badges to the current system. After all, traditional college diplomas look elegant when hung on the wall, but they contain very little detail about what the recipient learned. Students using Mozilla’s proposed badge system might display dozens or even hundreds of merit badges on their online résumés detailing what they studied. And students could start showing off the badges as they earn them, rather than waiting four years to earn a diploma.
The current university system’s great asset is that it concentrates people in a learning environment. But it also, as the quotation above implies, limits visibility to the student’s actual learning, limits student flexibility with regard to learning goals, defers recognition of achievement for several years, and does not lend itself easily to synchronous immersion in the professional world. I’m interested to hear other’s thoughts on the viability of the model suggested in the article.
I really enjoyed this piece, by Barb Darrow, about the development of healthcare-related data management at the University Pittsburgh Medical Center (UPMC) for a number of reasons. First of all, as the article explains, UPMC is a leader in the area and is doing some really interesting things! Secondly, I always enjoy a good story about the economy of Pittsburgh, since it represents one of the best cases (the best case?) of transforming a US rust belt city into a 21st century City (Health care and robotics are among the key fields relevant to that success.). Finally, and most significantly, the issues raised in the article demonstrate that mastering new levels of data management do not lead to ease and simplicity but rather, to even greater opportunities and challenges.
In the case, of UPMC, getting a head start on developing Electronic Medical Records has led, first of all, to the challenge of coordinating independent systems across specialties. Being able to manage enormous amounts of granular data, and to understand how to deploy that data, is one of the frontiers beyond the systems coordination step:
Doctors now try to take a more holistic view of their patients, and that requires the ability to pull together data from different sources. Imaging data is separate from surgery notes, which is separate from pharmacy data.
“If we look at big data, the idea is how to interconnect multiple points of data across the broad, biological continuum,” Shrestha said. “If the patient is diabetic, you don’t just see an endocrinologist looking at the liver in terms of liver function tests or any scans but across the biological spectrum of organs and then down to a cellular level. We look at pathology slides, reports on molecular imaging and down to the genomic levels.”
Darrow explains that data can be broken down into three buckets: imaging data, which accounts for close to 50% of UPMC’s digital information; databases, which account for about 10%; and unstructured information, such as “postoperative notes, radiology reports, discharge summaries,” which accounts for the remaining 40%. The piece goes on to describe some of the specific technologies that are being used to address these various categories and concludes by pointing to another, even further frontier: the integrated management of pathology reports.
Big data, as the article in which I found the above reference would argue, is here to stay. The more we know, the more we that will become knowable. Personally, I find the challenge daunting
A great series of case studies about how data is changing the world:
“Huawei people, especially the leaders, are destined to work hard for a lifetime and to devote more and suffer more than others.” – Ren Zhengfei, President and Founder, Huawei.
Huawei, based in Shenzhen, is one of the largest telecom companies in the world (with 2010 Revenues of $28bn) and the single largest such company in China. In this Harvard Business Review post (hat tip: Brian Pan) by China-based consultant, Ruxiang Jiang, the author questions whether the work ethic at Huawei, and in China in general, will be enough to propel that country into 21st century economic leadership.
A key quotation:
A collective culture is great for rapidly building an organization from scratch. But too often, companies with collective approaches continue to disempower individual employees and devalue their intellectual contributions.
As would many in the West, I tend to agree with Mr. Jiang’s conclusions. The enormous size of China’s labor force, which Mr. Jiang does consider, could push off China’s day of reckoning for some decades, however. One important question is how deeply business culture in other parts of the world would be influenced by such Chinese success, in the meantime.
High-speed transactions that leveraged large amounts of information were vital to banks and financial institutions supporting the real estate bubble that preceded the 2008 crisis. Today, banks are still viewed with suspicion and, at the same time, themselves lack visibility to the quality of debt that they have issued. Trust is hard to come by from all quarters.
The solution, oftentimes (if not always), harnesses the same energies that created the problem: Namely, the explosion of information and transaction speed in finance suggests that new institutions, capable of processing this information in a manner that garners greater trust, are not only necessary, but possible.
This Business Insider article details some of the changes in finance that could be harbingers of more dramatic changes in the years ahead. One tidbit (in the context of start-ups):
Crowdfunding startups has long been a dream deferred. But it’s finally happening. Direct crowdfunding via equity financing is still a big no-no, because SEC rules make it difficult for non-accredited investors to invest in startups. But exciting things are going on.
One of the most exciting such examples is AngelList, a “Match.com for investors and startups” that lets startups vie for capital from angels and (increasingly) VC firms. AngelList has seen torrid growth on the back of rising early-stage valuations in Silicon Valley. And it has also been expanding horizontally and geographically.
There are non-tech companies listed on AngelList, along with companies from around the world. AngelList is not technically crowdfunding–it just makes it easier for startups to get accredited investors’ attention and get funding–but it is certainly an early step in that direction.
Start-ups, by their improvisational nature and limited funding options, are likely to continue to be innovators in this space. But look for changes in finance to be an instrumental part of our economic recovery across multiple sectors. I am not promising that this will happen soon but I am promising that major structural changes, such as the ones described in the Business Insider article, will be necessary for economic recovery in a global informational environment that has dramatically changed in the past decade.
Perhaps you’ve already this exciting news:
Over a three-week period, gamers playing Foldit, an online protein-folding game, helped to map out the structure of an enzyme that could be used to help fight HIV and AIDS.
What the gamers were able to accomplish in unlocking the structure of a protein called M-PMV was something that scientists, engineers and automated computer programs haven’t been to pull off in about a decade’s worth of attempts, according to a study published in the journal Nature Structural & Molecular Biology.
This online game, which I’ve referenced several times before, provides a prime example of the open source phenomenon spreading beyond software programming. It’s interesting to consider why scientific discovery might provide a ripe field for such collaboration. I’ve yet to see examples as successful in areas such as government, supply chain planning, or other areas of personal interest. Here’s to hoping that we do see such examples, and in short order.
I couldn’t resist sharing this article about how technology is affecting the way baseball is played.
Here’s a key passage:
“I think this is truly the second great renaissance in baseball,” says Joe Maddon, a visionary kind of guy whose embrace of technology, info and outside-the-box thinking has made him, for all intents and purposes, the Steve Jobs of managers.
The first great renaissance, Maddon says, arrived with Branch Rickey in the 1920s, ’30s and ’40s, back when Rickey was pioneering the use of (gasp) farm systems and (shudder) statistics.
And the second great renaissance? That’s been taking place, almost imperceptibly, over the last decade — but to a greater degree, just over the last year or two or three. . . . Think about it:
. . .
• All of a sudden, while you were busy doing your laundry or drafting your fantasy team or something, the world was quietly being invaded by an army of sabermetric wizards, capable of computing Justin Verlander‘s road FIP against sub-.500 teams in games in which he throws more than 20 percent curveballs — and actually understanding the significance of that.
Lest anyone think that the tagline for this blog (“How to Stay Afloat in a Sea of Data”) applies only to business/government analytics, I’d like to share a recent sports article by Matt Mitchell (KVUE reporter – Austin) that addresses how sports-related information is created, digested, and broadcasted by ESPN today. A certain nautical feeling can overcome any observer ingesting a series of (often misleading) ESPN statistics but Mitchell makes a more general point about the influence the organization’s influence, in light of the its recent investment in the Longhorn Network, which will be dedicated to University of Texas sports:
The problem with all of this is the very real threat of sports hegemony when ESPN wields enough influence to alter the very sports it broadcasts by driving the national conversation.
ESPN’s distorting influence on sports stories came into sharp focus for me when the network raised LeBron James’ “Decision” about where to play basketball to unprecedented prominence before preceding to pillory him on a regular basis.
In Guy LeBord’s The Society of the Spectacle, the author observes that “modern industrial society . . . is based on the spectacle in the most fundamental way.” The trajectory in ESPN’s development validates that hypothesis in one particular sphere of society.