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Beyond Machine Learning: Capturing Cause-and-Effect Relationships

Irving Wladawsky-Berger

Deep learning is a powerful statistical technique for classifying patterns using large training data sets and multi-layer AI neural networks. Each successive layer in a multi-layer network uses the output from the previous layer as input. Machine learning is a statistical modelling technique, like data mining and business analytics , which finds and correlates patterns between inputs and outputs without necessarily capturing their cause-and-effect relationships.

we are dependent on human connection

Harold Jarche

Our networks are great places for serendipitous connections. The difference between an open social network (e.g. To make sense of our complex world and its often-veiled media sources, we need both open social networks and more closed communities of practice/interest. Only collectively can we confront the post-truth machines of the network era. The more diverse our social networks, the more diverse our thinking can be. What we do not know.

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The Social Network Is the Computer

Irving Wladawsky-Berger

The Social Network Is the Computer. For years, The Network Is the Computer was used as a marketing tagline by Sun Microsystems , - now part of Oracle,- to emphasize that in the Internet age, networked systems and applications were far more powerful than any single computer.

Shaping (As Opposed to Stumbling Into It!) – The Future of Online Learning and Training

Stephen Downes: Half an Hour

Shaping (As Opposed to Stumbling Into It!) – The Future of Online Learning and Training Stephen Murgatroyd, PhD, Chief Innovation Officer Contact North | Contact Nord These are summary notes of the talk, taken by me, “I’m here because I’m old….

Artificial Intelligence for Good: A Few Good Articles To Read #AI4Good

Beth Kanter

Allison Fine, my co-author for the Networked Nonprofit , and I are actively researching the use of AI for Good, in particular to scale giving and spread generosity. It was almost ten years ago that we published the Networked Nonprofit during the early days of social media and networks. Now, we entering a new digital era which includes emerging technologies like AI. Artificial Intelligence presents a lot of benefits for the social good sector.

#AI4Good: What Your Nonprofit Needs To Know About AI

Beth Kanter

Allison Fine, my co-author for the Networked Nonprofit , and I are actively researching the use of AI for Good, in particular to scale giving and to spread generosity. Demystifying Machine Learning for Global Development, an article published in the Stanford Social Innovation Review, suggests that when it comes to global development, the key is to ask the right questions, and then see if and how it can help.

learning in complexity and chaos

Harold Jarche

Cooperation is a fundamental behaviour for effectively working in networks, and it’s in networks where most of us will be working in the digital age. People in knowledge networks cannot be told what to do, only influenced through other people due to their reputation. In a distributed network you have to be seen as having some value, though not the same value, by many others. Social networks and communities of practice usually cooperate. Innovation.

six ways to make sense

Harold Jarche

connecting the curious —2019. Continuous ambiguity exerts continuous pressures on organizations to modify their patterns of interaction, information flow and decision making. This creates a demand for innovative approaches in sensemaking.” diversity trumps ability — 2019.

Cynefin St David’s Day (5 of 5)

Dave Snowden

Speaking of regret, the best part of a decade ago I started to argue and present the idea of creating a human sensor network using schools, community centres, and sports clubs. But you need to build cognitively diverse networks before the situation if at all possible as that will allow a fast response. If you create one in a crisis keep it live, but best is networks for ordinary purposes that can be activated in times of extraordinary need.

Educational Research in Learning Technology

Stephen Downes: Half an Hour

Decades of technological innovation in education have shown precious little in the way of educational gains and, more than anything else, have taught us that we need to be sceptical from the outset. Unfortunately, ‘the vast array of literature involving learning technology evaluation makes it challenging to acquire an accurate sense of the different aspects of learning that are evaluated, and the possible approaches that can be used to evaluate them’ (Lai & Bower, 2019).

Ethical Codes and Learning Analytics

Stephen Downes: Half an Hour

2019) Ethical Codes As Standards of Conduct While ethics commonly applies to people in general, there is a specific class of ethics that applies to people by virtue of their membership in a professional group. Modern analytics is based mostly in machine learning and neural networks, and these in turn provide algorithms for pattern recognition, regression, and clustering. 2019) Similar functionality is also provided by IMS Global’s Caliper learning analytics (Oakleaf, et.al.,