The KIT ─ Knowledge & Information Technology
No. 208 - 16 Jan 2018
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In This Issue
The Programmer's Oath
A Book Non-Recommendation
Oil & Gas Invests in AI
Automated Technical Debt Measure
ICT in Asia/Pacific
Seen Recently
Claude Baudoin

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ACM Webinar: The Programmer's Oath
Robert C. Martin, co-founder of the online video training company cleancoders.com, says that programmers are "the modern-day scribes," that our society depends on them, but that "we are unorganized, undisciplined, and we have no unifying ethics or standards." That is surely an exaggeration (which helps sell his books) but it promises an interesting and provocative webinar, which will take place on Monday, January 29 at 12 noon Eastern US time (1700 GMT). Register here.
Deep Learning and Big Data
Put two buzzwords together, send a call for papers, and voilà... you are the editor of a book, which a prestigious organization like ACM will promote in its newsletter without having performed any sort of quality control. This just happened with "Deep Learning Innovations and Their Convergence with Big Data," a collection of research papers "edited" (that's what the cover says -- there is no evidence of editing) by S. Karthik, Anand Paul and N. Karthikeyan. Stay away.
AI in Oil & Gas
We recently mentioned that machine learning is part of the title of an upcoming Oil & Gas industry conference in Calgary. In related news, this ZDNet article reports on a related $20 million investment by BP Ventures in the artificial intelligence startup Beyond Limits.

That company originally developed its technology for space exploration in collaboration with NASA and Caltech. From the ultra-vague deal announcement of the BP deal, it is impossible to know what exactly is the projected use in O&G ("new levels of operational insight, business optimization, and process automation" -- oh my!) but the article, which lists other AI efforts including GE's Predix platform, makes it clear that these technologies are being taken very seriously in major industries.
A Standard to Measure Technical Debt
If you buy a car and don't have all the cash required, you take out a loan, which you have to reimburse with interest, so you will end up paying a lot more than the sticker price. If you develop a system and you don't spend the time to build quality into it (e.g., you release the system with known bugs and design weaknesses), you will also have to pay later, and spend more. That's the concept of technical debt.

Estimating that debt (in dollars, or your currency of choice) is very useful: it allows you to make rational decisions on fixing the system vs. throwing it away, and it helps prioritize various remedial actions. But while some tools exist to assess the technical debt, there was no recognized standard until now. The Consortium for IT Software Quality (CISQ) just produced an Automated Technical Debt Measure, approved by the Object Management Group (OMG), its parent organization, at its last meeting.
ICT in Asia/Pacific
Courtesy of the U.S. Commercial Service (part of the Department of Commerce), here are some statistics about the growth of Information and Communication Technologies (ICT) in the Asia/Pacific region:
  • Singapore has developed a ten-year plan aligned with a "smart nation" vision.
  • Malaysia's current 5-year plan wants to grow ICT from 13% of the nation's gross domestic product in 2016 to 17% by 2020.
  • Gartner predicts that Asia/Pacific and Japan combined will spend $13.6 billion in cloud services by 2019.

The Commercial Service is hosting an Asia Pacific Business Outlook conference in Los Angeles on April 16-17, 2018. 

Seen Recently...
"Complexity bias is a logical fallacy that leads us to give undue credence to complex concepts. Faced with two competing hypotheses, we are likely to choose the most complex one. That's usually the option with the most assumptions and regressions. As a result, when we need to solve a problem, we may ignore simple solutions - thinking 'that will never work' - and instead favor complex ones."
-- Complexity Bias: Why We Prefer Complicated to Simple
(there's much more to read that the above quote)
in Farnam Street, a blog by Shane Parrish