The KIT ─ Knowledge & Information Technology
No. 256 - 20 January 2020
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In This Issue
Forum on AI Advances and Standards
Interoperability Across Blockchain Systems
Cloud Transaction Costs
Data Enrichment or Data Endangerment?
UK Data Science and AI Predictions
Seen Recently
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Call for Presentations -- AI Advances & Standards
The Artificial Intelligence Platform Task Force of the Object Management Group, formed in September 2019, is organizing a one-day forum in Reston, Va., near Washington D.C., on March 26. We are soliciting presentations from government, industry, and academia that outline advances in AI and areas where the development of standards can accelerate progress.

You can learn about the AI Task Force's work on the OMG wiki. Then, please look at the Call for Papers and follow the instructions to propose a paper or presentation.
Interoperability Across Blockchain Systems
Blockchain users are starting to express concerns about the challenges of managing complex information flows that span multiple distributed ledger technologies (DLTs), for example in supply chain management. Some of these issues may be mitigated by the development of one or more standards in this area. OMG has put out a Request for Information (RFI) on Blockchain Ecosystem Interoperability to gather more information on the challenges, concerns and potential solutions to interoperability questions.

To hear more and better understand the scope and the opportunity to contribute, you are invited to attend a free webinar led by Mike Bennett, co-chair of OMG's Finance Domain Task Force, on Wednesday 22 January, 8:00 Pacific / 11:00 Eastern/ 1600 UK time.
Cloud Transaction Costs
Rasha Makhlouf, a researcher at the Technical University of Brandenburg in Cottbus, Germany, has published a well-regarded paper in the Journal of Cloud Computing, entitled "Cloudy transaction costs: a dive into cloud computing economics."

Here is an excerpt from the outline: "This paper applies transaction cost theory to cloud computing through a 360-degree industry analysis. Expert interviews with vendor, customer and consultancy sides were conducted to understand costs associated with cloud computing. Findings were validated through a case study."
Data Enrichment or Data Endangerment?
First, some background: Elastic N.V. is a Dutch company that released in 2010 an open source search and data analytics engine, ElasticSearch, built on the Apache Lucene library and programmed in Java. Companies use ElasticSearch to mine data from public sources, such as directories and LinkedIn or Facebook profiles, and make that data available through APIs.

The problem is that some ElasticSearch servers, which store terabytes of data in the cloud, are poorly protected. If you can discover them on the Internet, you may be able to access the data without a password. Often, the data about people is just a handy compilation of millions of already public records; but sometimes there is more sensitive data (passwords or password reset links, e-mail addresses, dates of birth, loan information, and more). You can read here about 8 data breaches that occurred between just November 2018 and November 2019. CISO Magazine reported on November 25 that security experts discovered a server containing data records collected by People Data Labs and OxyData, so-called "data enrichment companies," about 1.2 billion users.
Computerworld: UK Data Science and AI Predictions
Computerworld published on December 30 an article about AI forecasts, focused on the UK, which makes some interesting points in a somewhat disorderly manner (and what's unique about the UK anyway with respect to those forecasts?). Here are some key takeaways:
  • AI funding more than doubled from 2018 to 2019.
  • Many companies are looking to hire their first data scientist (or data science consultant).
  • The new rules about data protection (GDPR) and the issuance of the first multi-million dollar fines are causing companies to think twice about collecting and exploiting personal information, and to look for "white hat" security people who can find vulnerabilities before breaches occur.
  • "Understanding fairness, bias, explainability and robustness of AI models will become as important as understanding their performance and effectiveness" -- one interviewee sees the rise of a "digital ethics officer" function.
  • The emergence of "AI as a Service" packaged solutions, enabling non-AI experts to exploit the technology.
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