OLDaily

Feature Article
Knowledge, Education, and the Role of Teachers.
Stephen Downes, Aug 11, 2017.

Responses to questions ahead of my upcoming presentation in Warsaw.

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Blackboard Trend Report
Blackboard Blog, 2017/08/11

Starting today, Blackboard is offering a weekly 'Trend Report' to be posted every Friday offering a list "of the recent industry articles that the Blackboard team has been reading and found most interesting.". While I'm delighted to welcome another entry into the field, I think the first pass needs reworking. The selection of sources is limited (do people at Blackboard read only Inside Higher Ed, the Chronicle, NPR, Hechinger and EdSurge?) and the summary is nought but a word-for-word reproduction of the first paragraph of the selected article. Blackboard staff should beep in mind that when I survey my own readership what they appreciate is the wide range of sources consulted and - even more! - the personal commentary written for each article. You can't fake authentic. :)

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Sony wants to digitize education records using the blockchain
Jon Russell, TechCrunch, 2017/08/11

TechCrunch reports that "Sony said today that it has finished developing a digital system for storing and managing educational records on the blockchain." It's now looking to commercialize the technology. The idea has been around for a while, but this is the first concrete development. "The system is managed by Sony Global Education, and is built on top of IBM Blockchain using IBM’s Cloud and The Linux Foundation’s Hyperledger Fabric 1.0 framework."

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xAPI Conformance Research & Future Requirements
Advanced Distributed Learning, 2017/08/11

Advanced Distributed Learning (ADL) is gathering community feedback on the xAPI specification and associated Learning Record Stores (LRS) requirements. To this end, they've posted the relevant documents on GitHib. There are three documents: the xAPI LRS Conformance Requirements, the xAPI LRS Certification Requirements and Recommendations, and the xAPI Profiles specification (subdivided into three parts). As thewy say, "Please take a few minutes to help influence the future direction of xAPI. Your input and feedback are extremely valuable and will help inform future direction of xAPI and where future research efforts should be focused."

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Artificial Intelligence: The Road Ahead in Low and Middle-Income Countries
World Wide Web Foundation, 2017/08/11

According to this article, "Research by McKinsey has gone as far as describing AI as contributing to a transformation of society 'happening ten times faster and at 300 times the scale' of the Industrial Revolution." So how does that impact low and middle income countries? The report looks at employment and growth, the redistribition of wealth, the delivery of public goods and services, and the impact on democracy. As we can imagine, things could go very well or very poorly. So what makes the difference? Data and infrastructure are key, of course, and people will need access to both. But the report also highlights skills and ethics, which to a certain degree fall within the domain of education and learning technology. According to the report, we need to create bridges to lower-income countries, to ensure that their perspectives are represented in the coming debates on ethics and policy, and to maximize the use of AI to promote the public good. I agree.

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Algorithmic Accountability: Applying the concept to different country contexts
World Wide Web Foundation, 2017/08/11

I've been thinking recently about how we validate AI algorithms, this in light of over-enthusiastic press reports and questionable outcomes. This article addresses this question directly. If we think about the four major functions of algorithms - priortization, classification, association and filtering - we can see how misleading data inputs can create undesired outcomes. This is what Microsoft discovered with Tay, the racist chatbot (the Chinese fared no better) The report looks at the causes and types of discrimination that can result and examines the possibility of algorithmic accountability, elucidating five principles for accounbtable algorithms: fairness, explanability, auditability, responsibility, and accuracy. Given the way these algorithms work, adherence to some of these principles may be a challenge.

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Personal Data: An overview of low and middle-income countries
World Wide Web Foundation, 2017/08/11

I just mentioned the EDUCAUSE article comparing different student data protection schemas. That article should be compared with this one, and especially the chart on page 11 looking at different mechanisms, including trade agreements, Commonwealth provisions, OECD, APEC and European directives. "There are generally weaker data protections in low and middle-income countries, leaving their citizens at risk." This includes the U.S. (see the chart on page 12). In a regime of increased surveillance and growth in government (and corporate) data collection we are seeing growing public mistrust. The report proposes three key elementsd to achieving data justioce (quoted):

• Everyone should be free from greater government infringement on their (data) privacy;
• Everyone should be free to create and use a “digital identity”;
• Everyone should have the right to identify and challenge when their personal data is used to discriminate against them.

That would be a start.

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