By Stephen Downes - Stephen's Web. The Road to Sharing is Not Paved With Licenses
Alan Levine, CogDogBlog, 2018/10/23
"Share for gratitude," writes Alan Levine, "not for rules and license terms." I agree (and I have my own stories about home someone just uses some of my content for a project or whatever). What the whole copyright and licensing debate has done is to move the ethos of the crass commercial from the corporate sphere into the personal sphere. More...

By Stephen Downes - Stephen's Web. Meet the modern learner: Engaging the Overwhelmed, Distracted, and Impatient Employee
Todd Tauber, Wendy Wang-Audia, Bersin by Deloitte, 2018/10/23
This is a scraped blog post (may or may not be framed) containing a framed version of a Bersin by Deloitte PDF-based report uploaded and shared through Slideshare. I can think of easier ways to offer this content (but I follow e-learning, conocimiento en red for the content, not the convenience). More...

By Stephen Downes - Stephen's Web. With what do you want to light the torch? Say things in full, bedlamite!
Wordshore, Metafilter, 2018/10/23
This year marks, more or less, the 40th anniversary of the Multi-User Dungeon, or MUD. This post on Metafilter focuses on the first MUD, ultimately called MUD2, licensed to CompuServe, and later killed by that company. MUDs really began to proliferate with the LPMud, created by Lars Pensjö, which, first, was extensible, and second, spawned numerous free and public domain versions of the code (many of which predate the 'official' invention of free software at Stanford in 1989). More...

By Stephen Downes - Stephen's Web. Learner Model's Utilization in the e-Learning Environments
Vija Vigale, Laila Niedrite, University of Latvia, 2018/10/29
This is quite a good paper describing the need for, creation of, and use of a learner model in support of adaptive learning. In current systems, the learner model is at the core of such systems. In conjunction with a domain mode, which maps the learning required in a field, the adaptive system employs an adaptive model to generate the activity, resource or intervention required. More...

By Stephen Downes - Stephen's Web. Towards Better Frameworks for Social Media Data Archiving
Axel Bruns, Snurblog, 2018/10/29
Snurblog summarizes a number of presentations from the recent iCS Symposium on Challenges to Studying Disinformation, including this keynote from Katrin Weller. It addresses some of the challenges in collectiong and sharing data from social media platforms. More...

By Stephen Downes - Stephen's Web. Here's What I Covered In My 4 DevLearn Presentations
Mel Milloway, Blog, 2018/10/29
Mel Milloway had a pretty busy conference. In his first session he has "the audience go through my Is It Edible? activity and guess what JavaScript was used." Thast's a nice way to do a "how do do it with Javacript" session. More...

By Stephen Downes - Stephen's Web. Call for Proposals: Skills, education & skills development
Mowat Centre, 2018/10/24
This call from the Mowat Centre might attract some interest from readers. They're looking for research  regarding the state of skills and skills development in Canada addressing specifically questions of equity, the future of work, and what skills matter. The deadline is October 31. More...

By Stephen Downes - Stephen's Web. How to build a learning city?
UNESCO Institute for Lifelong Learning, 2018/10/24
It's not called a MOOC, of course, but this series of videos from UNESCO is closer to a MOOC than any other form of learning. " The tutorials are based on the 2015 Guidelines for Building Learning Cities and consist of seven infographic animation videos addressing cities around the world to support them in the process of building learning cities." There's a hashtag - #Buildlearningcities. More...

By Stephen Downes - Stephen's Web. This robot co-taught a course at West Point
Khorri Atkinson, Axios, 2018/10/24
"Bina48 co-taught two sessions of an introduction to ethics philosophy course — which covers ethical reasoning, just-war theory and the use of artificial intelligence in society. In the classroom were almost 100 students, along with Barry and Maj. Scott Parsons, an assistant professor at West Point." I think "taught" is a very generous statement of what probably actually happened. More...

By Stephen Downes - Stephen's Web. 4 human-caused biases we need to fix for machine learning
Glen Ford, TheNextWeb, 2018/10/28
The response to three of the four biases reported in this post is diversity. And I would add that just as machines need diversity in order to avoid bias, so do humans. That's why diversity is valuable. Anyhow here's the breakdown of the three (all quoted from the text):

• Sample bias is a problem with training data... (we need a sample) both large enough and representative enough to mitigate sample bias.
• Measurement bias happens when there’s an issue with the device used to observe or measure... best avoided by having multiple measuring devices (and I would add, multiple types of measuring devices)
• Algorithm bias is a mathematical property of an algorithm. The counterpart to bias in this context is variance.

The fourth type of bias is prejudice bias, and "is a result of training data that is influenced by cultural or other stereotypes." More...