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How to Survive and Thrive in a World of Disruption

Irving Wladawsky-Berger

Why have so many companies been done in by disruptive technological and market changes? Evolutionary fitness of organizations is determined by their ability to effectively respond to environmental changes,” write Leo Tilman and Charles Jacoby in their recently published book Agility : How to Navigate the Unknown and Seize Opportunity in a World of Disruption. “Extinctions generally follow a familiar pattern. How can you turn survival into the driving force of innovation?

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Beyond Machine Learning: Capturing Cause-and-Effect Relationships

Irving Wladawsky-Berger

Artificial intelligence is rapidly becoming one of the most important technologies of our era. AI technologies are approaching or surpassing human levels of performance in vision, speech recognition, language translation, and other human domains. Deep learning is a powerful statistical technique for classifying patterns using large training data sets and multi-layer AI neural networks. Why are there such universal human activity patterns?


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The Current State of AI Adoption

Irving Wladawsky-Berger

In the past few years, the necessary ingredients have finally come together to propel AI beyond early adopters to a broader marketplace: powerful, inexpensive computer technologies; advanced algorithms; and huge amounts of data on almost any subject. Newspapers and magazines are full of articles about the latest advances in machine learning and related AI technologies. Business and technology leaders must work quickly to establish key AI enablers.

The Puzzling Personal Productivity Paradox

Irving Wladawsky-Berger

The past 10-15 years have seen a number of technology advances, from smartphones to machine learning. A few contend that there’s been a fundamental decline in innovation and productivity over the past few decades, compared to the period between 1870 and 1970. Yet others argue that there have always been time lags between technology advances and their impact on economic growth. While technologies may advance rapidly, humans and institutions change slowly.

How We Learned to Prosper Using Fewer Resources

Irving Wladawsky-Berger

In recent years we’ve seen a different pattern emerge: the pattern of more from less.”. What led to the emergence of a more-from-less pattern? The most important forces responsible for the change are technological progress and capitalism. In particular, we got better at combining technological progress with capitalism to satisfy human wants and needs.”. Similar patterns are seen in other rich countries.”.

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….

Educational Research in Learning Technology

Stephen Downes: Half an Hour

Kerr in this recent post , about how research in educational technology could be improved, but I have disagreements around the edges, enough that I think more discussion is warranted. Also, while Kerr is more focused on artificial intelligence in education (AIEd) research, I will address my remarks to learning technology more generally. Here are just a few: - access - it is demonstrably true that educational technology has increased access. 2019) which caught my eye.

Will Artificial Intelligence Augment Nonprofit Staff or Replace?

Beth Kanter

Artificial intelligence, machine learning, bots, and other automation technologies offer many benefits to nonprofit professionals because it can perform basic and mundane tasks. AI technologies will enable time shifting to more human-centered tasks through using a combined machine/human approach. If AI can do the boring grunt work for a nonprofit human, use that free time on building relationships,identifying innovation solutions, and scaling services.

#AI4Good: What Your Nonprofit Needs To Know About AI

Beth Kanter

Are you trying to get up to speed on AI and other emerging technologies and how they might impact your work? 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.

The Social Network Is the Computer

Irving Wladawsky-Berger

The Technology Trifecta. Three technologies make the Hype Machine possible by transforming how information is produced and consumed: digital social networks, machine intelligence, and smartphones.

Is Work-from-Anywhere Here to Stay?

Irving Wladawsky-Berger

There were predictions that the Internet would lead to the decline of cities , because technology was making location less relevant to our work and personal lives. Remote work has been around for a few decades, but took off in the mid-late 1990s with the explosive growth of the Internet.

learning in complexity and chaos

Harold Jarche

While all levels of complexity exist in our world, more and more of our work deals with real complex problems — in which the relationship between cause and effect can only be perceived in retrospect — whether they be social, technological, or economic. Innovation. Innovation comes from people, not technology. The challenge for the Fourth Industrial Revolution becomes interpretation, reflection, and innovation. Innovation does not happen inside a petri dish.

Trends That Will Likely Shape a Highly Uncertain Year

Irving Wladawsky-Berger

In all these cases, and in many others, the pandemic has accelerated existing trends of technological adoption,” adds The Economist. “Now people in many countries have been abruptly propelled into a future where all of these behaviours are far more widespread.”.

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Are We Becoming a Decadent, Stagnating Society?

Irving Wladawsky-Berger

This long essay covers a lot of ground, from technology and innovation to politics and religion. Most everyone will agree that the Internet, smartphones, and related digital technologies have had a far bigger impact in people’s daily lives than the moon landing.

What History Tells Us About the Accelerating AI Revolution

Irving Wladawsky-Berger

A few weeks before our lives were turned upside down by Covid-19, I read Technology at Work v4.0 , the fourth report in the Technology at Work Series developed by Citigroup in collaboration with Oxford University. The report includes an excellent chapter on What History Tells Us About the Coming AI Revolution by Oxford professor Carl Benedikt Frey based on his 2019 book The Technology Trap. Computers followed a similar pattern.

Why Some AI Efforts Succeed While Many Fail

Irving Wladawsky-Berger

Winning with AI , - a 2019 report based on a survey jointly conducted by the MIT Sloan Management Review and the Boston Consulting Group , - found that 90% of respondents agree that AI represents a business opportunity for their company. To help answer these questions, the study looked for patterns in the survey data and in the executive interviews to uncover what the companies that are succeeding with AI are doing.

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Philgorithms: Two Examples of Data Mapping to Guide Donor Decisions

Beth Kanter

As COVID accelerates innovative uses of AI in many areas, we are also seeing more development of AI-powered data mapping tools for philanthropic advising and to support donor investment decisions. The technology helps donors make investments that yield the highest impact or strategic system change. Davies coined the term “ philgorithm ” to describe the use of algorithms to detect basic patterns or gaps in a donor’s strategy. AI4Giving Innovation Philanthropy

Ethical Codes and Learning Analytics

Stephen Downes: Half an Hour

Keywords: Learning analytics, ethical codes, learning technology, education, research ethics Introduction What distinguishes ethical codes from other forms of ethics generally is that while they may assign duties and responsibilities, these are assumed voluntarily by virtue of being a member of the profession. Modern analytics is based mostly in machine learning and neural networks, and these in turn provide algorithms for pattern recognition, regression, and clustering. 2019).