complexity rules

Harold Jarche

We live and work in a complex system. Simple, traditional linear models do not work in complex systems. Complexity is not complicated, nor linear — “In complex systems, the last thing that happened is almost never informative about what’s coming next.”

Understanding complexity

Harold Jarche

Thinking of complex adaptive systems as merely complicated entities that can be regulated like machines can lead to disaster, as Niall Ferguson shows in his recent book. Human systems are complex. Today’s large, complicated organizations are now facing complex business environments that require agility in simultaneously learning and working. A schematic history of human civilization reflects a growing complexity of the collective behavior of human organizations.

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Transforming learning through analytics

George Siemens

Data, big data, analytics, and visualization are significant trends in education. There is much to be alarmed about with analytics, including the mechanization of teaching, learning, and assessment. Additionally, the data and analytics that are easy to collect and conduct risk becoming a simple veneer over the complexities of learning and cognition. Or, as Gardner Campbell states : “Current NGLC/NCLB paradigms create great risk of analytics-generated edu-hell.”

Social Physics - Reinventing Analytics to Better Predict Human Behaviors

Irving Wladawsky-Berger

They’ve enabled the construction of AI algorithms that can be trained with lots and lots of sample inputs, which are subsequently applied to complex problems like language translation, natural language processing, and playing championship-level Go. Machine learning has been most successful when used for complex computational problems like image and voice recognition, where a huge body of data is available and the data is fairly static.

Open Learning Analytics: A proposal

George Siemens

Learning analytics are increasingly relevant, and prominent, in education. Startups and established software vendors are targeting learning analytics in their product offerings for the education and training and development sector. Many of the companies that serve the higher education market– including Sungard, Blackboard, and Pearson – are already heavily committed to analytics. In education, everything is becoming “data” and “analytics”).

The Promise and Challenges of Health Analytics

Irving Wladawsky-Berger

On February 24 I attended a workshop in MIT on the Future of Health Analytics. In a recent paper , Ausiello notes that health analytics has the potential to become the next frontier in medicine, driven by the confluence of three key revolutions: . Complex Systems Data Science and Big Data Education and Talent Healthcare Systems Innovation Management and Leadership Political Issues Services Innovation Smart Systems Society and Culture Technology and Strategy

Notes On "Global Guidelines: Ethics in Learning Analytics"

Stephen Downes: Half an Hour

In my post referencing the ICDE's Global Guidelines: Ethics in Learning Analytics yesterday I said: This document summarizes the considerations of an ICDE working group on learning analytics. The presumption throughout is that a global ethic in learning analytics is needed, can be known, and comprehends the issues in this document. Definition and purpose of the use of Learning Analytics Where is data drawn from? What data must be included in learning analytics?

Organize for Complexity

Harold Jarche

” Well I think Niels has answered much of that question himself, in his recent book Organize for Complexity. We call this “disciplined practice” Fads like business analytics, knowledge management, and big data will never make organizations fit for complexity. So what does Organize for Complexity cover? Complex markets require decentralization, combined with market-like coordination. Books complexity ConnectedEnterprise Wirearchy

Reflecting on Learning Analytics and SoLAR

George Siemens

The Learning Analytics and Knowledge conference (LAK16) is happening this week in Edinburgh. I have great hope for the learning analytics field as one that will provide significant research for learning and help us move past naive quantitative and qualitative assessments of research and knowledge. Would you be interested in participating in a discussion on educational analytics (process, methods, technologies)? Not everyone was a fan of the idea of learning analytics.

The Competitive Value of Data: From Analytics to Machine Learning

Irving Wladawsky-Berger

Business analytics predates the big data era. Beyond business analytics, new data science methods could now be used to extract actionable knowledge from all that data, that is, knowledge to help make better decisions and predictions. AI-based tools are enhancing our own cognitive powers, helping us process vast amounts of information and make ever more complex decisions.

Open Symposium: Policy and Strategy for Learning Analytics Deployment

George Siemens

We ( SoLAR ) are organizing an online symposium on Policy and Strategy for Learning Analytics Deployment. A short intro video to the goal of the symposium: From the symposium description: While research in learning analytics has advanced, limited attention has been paid to the larger policy and strategy considerations that influence the adoption and deployment of analytics in educational settings. Educational data is complex.

Big Data, Complex Systems and Quantum Mechanics

Irving Wladawsky-Berger

Big data is a foundational element in IT’s quartet of Next Big Things : Social, Mobile, Analytics and Cloud. In thinking about this question over the last few years, I started to notice that a number of subtle, non-intuitive concepts that I learned many years ago as a physics student seem to apply to the world of big data and information-based predictions in highly complex systems. Big Data is one of the hottest topics out there.

Gird for complexity

Jay Cross

Complexity has been on my mind a lot lately. In the future, the descendants of IBM’s Watson and analytics will do the complicated jobs. What’s left is complexity: the unpredictable, volatile, surprise-time, non-linear, quantum, interconnected challenges of WTF. Will complex work become the norm by 2020? Yet learning to navigate complex environments is totally different than learning to follow procedures and solve bounded problems. The U.S.

The Science of Complex Systems

Irving Wladawsky-Berger

When I look back over my long, relatively eclectic career, complex systems have been a common theme in all the activities I’ve been involved in. It started in the 1960s, when I was an undergraduate and graduate student at the University of Chicago majoring in physics, - the study of complex natural systems. The research for my thesis was focused on the highly complex world of atoms and molecules.

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Preparing Students for an Increasingly Complex Business World

Irving Wladawsky-Berger

Are engineering and management schools adequately preparing students for our fast-changing, highly complex business world? Universities generally do a pretty good job when it comes to teaching hard skills, - engineering methods, technology, analytical tools, finance, marketing, and so on. Not quite, say a number of recent studies. A good education should include soft as well as hard competencies.

Future of work is complex, implicit and intangible

Harold Jarche

With the increasing complexity that networks bring, implicit knowledge-sharing becomes more important as well, but this is often ignored by both training and knowledge management programs. The new workplace of intangible assets is a complex environment , and one where traditional analytical methods no longer work. The future of work is complex, implicit, and intangible. complexity Work

Complexity and Design in Warfare

Irving Wladawsky-Berger

The workshop explored how design-oriented approaches can help us better understand and deal with the very complex problems we are increasingly encountering in all aspects of business, economies, government, public policy, military operations and society in general. Over the past few meetings the Forum has focused on various topics related to complex systems, - how to best understand and manage them in the present, as well as predict and shape their future directions.

In a complex society

Harold Jarche

In complexity, we have to think about emergent practices, which means jumping in and immersing ourselves in the environment in order to start making sense of it. An external, analytical approach will tell us little. Networks and complexity are the defining characteristics of our “work&# places today. Tweet As you may have noticed, this has been a busy week. I flew to Maastricht, NL last weekend, via London and Brussels; a 24 hour trip.

The Complex Transition to the Age of the Cloud

Irving Wladawsky-Berger

We can use real time information and powerful analytics to help us understand and optimize the very way everything works in an attempt to make the world more efficient and smarter. Cloud computing is a highly complex initiative - at the technical, business and organizational levels. And, one of the key lessons we all hopefully learned from the dot-com era is that complex, global initiatives take time. In June of 2008 I participated in a conference on cloud computing.

Growing Up in a Complex World

Irving Wladawsky-Berger

The primary challenge emerging out of the CEO conversations was complexity - the fact that CEOs now operate in a world that is substantially more volatile, uncertain and complex. Inheriting a Complex World: Future Leaders Envision Sharing the Planet invited graduate and undergraduate students to participate in a Web-based survey between October 2009 and January 2010. They grew up in a complex world. Several weeks ago IBM released its 2010 Global CEO Study.

Ten IT Predictions for the Post-Pandemic New Normal

Irving Wladawsky-Berger

T hrough 2023, half of enterprises’ hybrid workforce, business automation, and other transformation efforts will be delayed or will fail due to a shortage of IT and analytics talent with the right skills.

Irving Wladawsky-Berger: Reflections on Complex Systems

Irving Wladawsky-Berger

Home Archives Subscribe « The Web and the Long, "Soft" War | Main | The Life Cycle of a Business » April 16, 2007 Reflections on Complex Systems Last week I attended the Almaden Institute , a meeting held annually at IBMs Almaden Research Center , located in Silicon Valley. The theme of this years Institute was Navigating Complexity: Doing More with Less , and featured a number of talks and panels on a variety of themes relating to complex systems.

Ethical Codes and Learning Analytics

Stephen Downes: Half an Hour

Abstract The growth and development of learning analytics has placed a range of new capacities into the hands of educational institutions. The ethics of learning analytics will therefore need to be developed on criteria specific to education. It may be argued that the relation between ethics and law is such that in a treatment of the ethics of learning analytics we ought also to be concerned with the law in relation to learning analytics.

AI Is Mostly About Business Value, Not Technology

Irving Wladawsky-Berger

A few months ago, Babson College professor Tom Davenport convened a virtual meeting of chief data and analytic officers (CDAO) from a variety of industries to discuss how to best achieve a return on investments (ROI) in AI. “We

Design Principles for Complex, Unpredictable, People Oriented Systems

Irving Wladawsky-Berger

An IBM Global CEO Study conducted in 2010 concluded that complexity was the primary challenge emerging out of its conversations with 1,500 CEOs and senior government officials. CEOs told us they operate in a world that is substantially more volatile, uncertain and complex. Over the past several years, we have seen a rising emphasis on design, creativity and holistic thinking in business to help us deal with an increasingly volatile, unpredictable complex world.

How to Emerge Stronger in the Post-Pandemic New Normal

Irving Wladawsky-Berger

Such a digital recovery will include “technology-enabled next-generation operations, analytics-enabled engineering productivity, and automation of service-related processes.”. “What now?,”

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The State of AI Adoption - High Performers Show the Way

Irving Wladawsky-Berger

A common theme throughout the report was that the same players who were leaders in the earlier waves of digitization and analytics were the early leaders in the AI wave. Revenue growth is highest in marketing and sales, - pricing, prediction of likelihood to buy, and customer-service analytics; in product and service development, - creating new AI-based products and enhancements; and in supply-chain management, - sales and demand forecasting, and spend analytics.

After Years of Promise and Hype, Is AI Once More Failing to Deliver?

Irving Wladawsky-Berger

One of deep learning’s key features is that, unlike classic analytic methods, there’s no asymptotic data size limit beyond which it stops improving.

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The AI Factory: A New Kind of Digital Operating Model

Irving Wladawsky-Berger

Operating models are often quite complex, encompassing the activities of thousands of people, lots of processes, advanced technologies and millions of lines of code.

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Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. For the vast majority of the use cases, 69%, the key value of machine learning is to improve performance beyond that provided by traditional analytic techniques. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

Online Community Purpose Checklist | Full Circle Associates

Nancy White

11/26/2009 HANH Le # uberVU - social comments on 14 Jan 2010 at 7:02 am Social comments and analytics for this post… This post was mentioned on Twitter by lordorica: Community builders can get a jumpstart using Nancy White’s Online Community Purpose Checklist.

Reconnecting Society and Reopening the Economy

Irving Wladawsky-Berger

Their recent paper and accompanying supplementary material explains their models and analytical methods in great detail. A few months ago, MIT Connection Science held it’s annual Sponsors’ Meeting online. The virtual meeting included a number of very interesting presentations.

Blockchain and Public Health Solutions

Irving Wladawsky-Berger

Using next generation data analytics and AI they could understand the possible trajectories of a virus and take steps to crush it.”. Artificial Intelligence Blockchain and Identity Complex Systems Data Science and Big Data Economic Issues Healthcare Systems Innovation Management and Leadership Political Issues Society and Culture Technology and Strategy

Getting on the AI Learning Curve: A Pragmatic, Incremental Approach

Irving Wladawsky-Berger

Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” is the paper’s overriding finding. For the vast majority of the use cases, 69%, the key value of machine learning is to improve performance beyond that provided by traditional analytic techniques. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

Can Democracy and Free Markets Survive in the Coming Age of AI?

Irving Wladawsky-Berger

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. This is clearly the case when attempting to apply machine learning to highly complex and open-ended problems like markets and human behavior. Can technology plan economies and destroy democracy?

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Becoming a Data-Driven Business: Challenges and Opportunities

Irving Wladawsky-Berger

A few weeks ago, McKinsey published The age of analytics: Competing in a data-driven world , a comprehensive report on the state of big data, and in particular, on the challenges and opportunities a company faces as it strives to become a data-driven business. Big data ,- including analytics , data science , artificial intelligence and related information-based technologies - are now everywhere. “Is

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The Emergence of Industry 4.0

Irving Wladawsky-Berger

In its scale, scope and complexity, what I consider to be the fourth industrial revolution is unlike anything humankind has experienced before…”. The digitization of product and service offerings by adding smart sensors, communication devices, and data analytics tools to create smart digital products and smart services. Data analytics and digital trust are the foundations. “Data fuels Industry 4.0 Robust, enterprise-wide analytics requires significant change.

Is Design Thinking the “New Liberal Arts”?

Irving Wladawsky-Berger

Design thinking is now being applied to abstract entities, - e.g. systems, services, information and organizations, - as well as to devise strategies, manage change and solve complex problems. Recent studies have shown that, given our complex business world , companies are increasingly searching for talented individuals that are strong in quantitative, analytical, technical and similar hard skills, as well as in strategic thinking, teamwork, communications and related soft competencies.

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My Old Online Facilitation Workshop Materials | Full Circle Associates

Nancy White

Online Facilitation Course Curriculum Rev Aug 2002 Share and Enjoy: 13 responses so far 13 Responses to “My Old Online Facilitation Workshop Materials&# # uberVU - social comments on 30 Dec 2009 at 10:24 am Social comments and analytics for this post… This post was mentioned on Twitter by NancyWhite: Setting my old online facilitation curriculum into the wild [link]. #

Deep Learning: Is it Approaching a Wall?

Irving Wladawsky-Berger

The data requirements for deep learning are substantially different from those of other analytic methods in a number of dimensions. The performance of traditional analytics tends to plateau as the data set size increases. Deep learning methods are particularly valuable in extracting patterns from complex, unstructured data, including audio, speech, images and video. It’s quite difficult to explain in human terms the results of complex deep learning applications.

Can AI Help Develop and Execute a Competitive Business Strategy?

Irving Wladawsky-Berger

In today’s data-rich markets, top business leaders rely heavily on analytics and quantitive measures to define, communicate and drive strategy. As ‘accountable optimization’ becomes an AI-enabled business norm, there is no escaping analytically enhanced oversight. Artificial Intelligence Complex Systems Data Science and Big Data Economic Issues Innovation Management and Leadership Services Innovation Smart Systems Technology and Strategy

Blockchain Can Reshape Financial Services… But it Will Take Significant Time and Investment

Irving Wladawsky-Berger

Others include biometrics, cloud computing, cognitive computing, machine learning and predictive analytics. Not surprisingly given their complexity, change comes much slower to global financial infrastructures. Transforming this highly complex global ecosystem is very difficult. Overcoming these challenges will add complexity and delay large-scale, multi-party DLT implementations.

Learning to Apply Data Science to Business Problems

Irving Wladawsky-Berger

This past semester I was involved in an interesting course at MIT’s Sloan School of Management , - Analytics Labs (A-Lab). A-Lab’s objective is to teach students how to use data sets and analytics to address real-world business problems. Furthermore, data science is a highly complex discipline, a veritable mashup of several different fields. Businesses across the world are wrestling with challenges and opportunities that call for the application of analytics.

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