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.

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?

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. He also elaborates on 16 attributes of effective ways to address complex problems.

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. My interest in learning analytics, however, doesn’t blind me to potential risks.

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.

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: .

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.

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. Educational data is complex. The problem of data, at a systems level, seems too large and too complex to tackle.

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.

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.

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.

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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.

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.

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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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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 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. Tweet As you may have noticed, this has been a busy week.

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.

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.

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.

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.

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. And, in the remaining 15% of cases, machine learning provided limited additional performance over existing analytical methods. .

The Business Value of Resilience

Irving Wladawsky-Berger

Biological systems have long been an inspiration in the study of complex systems. Teach for resilience : “Management education focuses on the single-minded pursuit of efficiency - and trains students in analytic techniques that deploy short-term proxies for measuring that quality.

Beyond Machine Learning: Capturing Cause-and-Effect Relationships

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.

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My Old Online Facilitation Workshop Materials | Full Circle Associates

Nancy White

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.

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. .

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.

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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…”. Data analytics and digital trust are the foundations. “Data fuels Industry 4.0

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. Design thinking has become an increasingly popular topic of discussion over the past decade.

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A Framework for Building AI Capabilities

Irving Wladawsky-Berger

It’s led to the development of AI algorithms that are first trained with lots and lots of sample inputs, and then subsequently applied to complex problems like language translation, natural language processing, real time fraud detection, personalized marketing and advertising, and so on.

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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.

Gender Diversity, Empathy and Technology

Irving Wladawsky-Berger

The human brain may well be one of the most complex structures in the universe. To help us address increasingly complex problems, the bulk of modern work , - in technology as well as most other fields, - is more and more team-based.

The Challenges of Executing a Transformational Strategy

Irving Wladawsky-Berger

Strategy is inherently complex,” said Turning Strategy into Results , a recent MIT Sloan Management Review article by Sull and collaborators. Complex Systems Economic Issues Innovation Management and Leadership Technology and StrategyThe 2018 MIT CIO Symposium will take place on May 23.

What Machine Learning Can and Cannot Do

Irving Wladawsky-Berger

One of the key features of deep learning algorithms is that, unlike classic analytic methods, there’s no asymptotic data size limit beyond which they stop improving. Artificial intelligence is rapidly becoming one of the most important technologies of our era.

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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.

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Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

Irving Wladawsky-Berger

A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture.”. AI is now seemingly everywhere.

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Solow Paradox 2.0: The Lagging Impact of Technology Advances on Productivity Growth

Irving Wladawsky-Berger

Complex Systems Economic Issues Education and Talent Future of Work Innovation Management and Leadership Political Issues Society and Culture Technology and StrategyFewer workers is one of the key reasons for our stagnant economic growth.

Serious AI Challenges that Require Our Attention

Irving Wladawsky-Berger

Police agencies hope to do more with less by outsourcing their evaluations of crime data to analytics and technology companies that produce predictive policing systems.

How Will AI Likely Impact How We Work, Live and Play?

Irving Wladawsky-Berger

Public safety and security. “One of the more successful uses of AI analytics is in detecting white collar crime, such as credit card fraud.

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What Will Life Be Like in an AI Future?

Irving Wladawsky-Berger

Interest in AI declined until the field was reborn in the 1990s by embracing an engineering-based data-intensive, analytics paradigm. I believe that in the end, it comes down to which of two major forces will prevail over time - exponential growth or complexity brake. .

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A Framework for Building AI Capabilities

Irving Wladawsky-Berger

It’s led to the development of AI algorithms that are first trained with lots and lots of sample inputs, and then subsequently applied to complex problems like language translation, natural language processing, real time fraud detection, personalized marketing and advertising, and so on.

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AI - the Creation of a Human-Centric Engineering Discipline

Irving Wladawsky-Berger

Machine and deep learning are the latest examples of tools like the World Wide Web, search and analytics that are helping us cope with and take advantage of the huge amounts of information all around us. AI is rapidly becoming one of the most important technologies of our era.

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