Building a More Resilient, Data-Driven Economy

Irving Wladawsky-Berger

Today we face two simultaneous disruptions: one is the COVID-19 pandemic and resulting economic shock, and the second is the rise of pervasive digital data, crypto systems, and artificial intelligence (AI).” T he two disruptions are highly interrelated. Data and AI: A new ecology.

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The Emerging Data Economy

Irving Wladawsky-Berger

The Economist’ s May 6 issue referred to data in its cover as the world’s most valuable resource. Similarly, data centers “power all kinds of online services and, increasingly, the real world as devices become more and more connected.”.

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Data Science and the Changing Nature of Research and Innovation

Irving Wladawsky-Berger

Last month, the American Academy of Arts and Sciences (AAAS) released the results of a new study, ARISE II: Unleashing America’s Research & Innovation Enterprise. The emergence of data science is closely intertwined with the explosive growth of big data over the past several years.

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What is innovation?

Harold Jarche

In writing almost 100 posts on innovation since 2007, it’s time to put the core observations together into a cohesive narrative. Innovation is fifteen different things to fifteen different people. Innovation today is people making connections. An Innovation Process?

Big, thick and rich (the data)

Dave Snowden

One of the main points I have made is the need to focus on learning and innovation in parallel with crisis management processes. Now when you talk to people about mass distributed sense-making you often hit the Big Data argument. Great insights inspire design, strategy, and innovation.

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Innovation and National Security in the 21st Century

Irving Wladawsky-Berger

The Task Force noted that leadership in innovation, research and technology since World War II has made the US the most secure and economically prosperous nation on earth. A major new wave of innovation is characterized by speed, disruption, and scale.

Towards a Trusted Framework for Identity and Data Sharing

Irving Wladawsky-Berger

As the economy and society move toward a world where interactions are primarily governed by digital data and transactions, our existing methods of managing identity and data security are proving inadequate. Few institutions will let their critical data out of their premises.

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Big Data Takes Center Stage

Irving Wladawsky-Berger

A few recent articles have expressed concerns that big data may be at the peak of inflated expectations in the so-called hype cycle for emerging technologies, and will soon start falling into the trough of disillusionment. So is big data. .

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Are Innovation and R&D Yielding Decreasing Returns?

Irving Wladawsky-Berger

Given the pace of technological change, we tend to think of our age as the most innovative ever. These innovations, first developed in the late 19th and early 20th century, have long been transforming the lives of billions. Innovation may be hitting a wall of diminishing returns.

Big Data, Science and the Humanities

Irving Wladawsky-Berger

In my opening statement I said that I strongly believe that digital technologies and the many data services they are enabling will make cities smarter and help transform them over time. And then there is the advent of big data.

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Open Innovation 2.0

Irving Wladawsky-Berger

I recently read Twelve Principles for Open Innovation 2.0 , an article published last year in Nature by Martin Curley. Let me discuss each of these phases of innovation. Closed Innovation. Innovation was increasingly occurring in the marketplace, no just in their labs.

The Science of Innovation

Irving Wladawsky-Berger

Innovation - identified by MIT economist and Nobel laureate Robert Solow as the driver of long-term, sustainable economic growth and prosperity - has been a hallmark of the Massachusetts Institute of Technology since its inception.” The innovation paradigm has changed.

The Big Data Era Is Here

Irving Wladawsky-Berger

During the meeting, the TRB Executive Committee held a policy session on the impact of big data on transportation systems. Big data and related information-based disciplines, - e.g., data science , artificial intelligence , - are everywhere. Insight vs Data Volume.

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The Impact of AI on R&D and Innovation

Irving Wladawsky-Berger

Beyond innovations in existing sectors, the rapidly improving price/performance of GPTs have led over time to the creation of whole new applications and industries. Big data and AI learning algorithms are now ushering such a scientific revolution.

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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Data-Driven Decision Making: Promises and Limits

Irving Wladawsky-Berger

Given the explosive growth of big data over the past decade, it’s not surprising that data-driven decision making is one of the most promising applications in the emerging discipline of data science. . Neither is good data-driven decision making.

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A Data Science Approach to Organizational Health

Irving Wladawsky-Berger

Organizational health encompasses relatively soft measures, such as leadership, skills, coordination and innovation capabilities, which have often been based on opinion and conjecture rather than on hard numbers. A 2013 Deloitte report, Success or Struggle?

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The Competitive Value of Data: From Analytics to Machine Learning

Irving Wladawsky-Berger

A recent article by NY Times reporter Steve Lohr discussed the rising importance of data as a major competitive differentiator. In his NY Times article , Lohr cautions that standard antitrust arguments may not be so easy to make in this new era of data competition.

Data Science: from Half-Baked Ideas to Data-Driven Insights

Irving Wladawsky-Berger

In a Big Data presentation last year, MIT professor Erik Brynjolfsson pointed out that throughout history new tools beget revolutions. Big data is leading to such a measurement-driven revolution, brought about by the new digital tools all around us, including our mobile phones; searches and web links; social media interactions; payments and transactions; and the myriads of smart sensors keeping track of the physical world. Data science is a mashup of several different fields.

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Learning to Apply Data Science to Business Problems

Irving Wladawsky-Berger

A-Lab’s objective is to teach students how to use data sets and analytics to address real-world business problems. Companies submit project proposals prior to the start of the class, including the business problem to be addressed and the data on which the project will be based.

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bias thwarts innovation

Harold Jarche

Our data implies that gender differences may lie not in how women act but in how people perceive their actions. Innovation requires diversity. Innovation is not so much about having ideas as it is about making connections. Innovation is in a state of perpetual beta.

The 2018 MIT Inclusive Innovation Challenge

Irving Wladawsky-Berger

In 2016, MIT’s Initiative on the Digital Economy launched its first annual Inclusive Innovation Challenge (IIC). iMerit hires and trains economically challenged people so they can provide data services to customers around the world.

A Framework for the Safe Management of Digital Identities and Data

Irving Wladawsky-Berger

In a world that’s increasingly governed by digital transactions and data, our existing methods for managing security and privacy are proving inadequate. Data breaches, large-scale fraud, and identity theft are becoming more common. Decentralized data architecture.

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Data Science - the Emergence of a New Discipline

Irving Wladawsky-Berger

Data Science is emerging as a hot new profession and academic discipline. Data Scientist: the Sexiest Job of the 21st Century is the title of a recent Harvard Business Review article. They note that demand for data scientists is racing ahead of supply. What is data science? ,

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Reflections on Big Data, Data Science and Related Subjects

Irving Wladawsky-Berger

CUSP’s research and educational programs are centered on urban informatics , - “the acquisition, integration, and analysis of data to understand and improve urban systems and quality of life.” Big Cities + Big Data and Bringing Urban Data to Life are prominently displayed in its website.

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Why Do We Need Data Science when We’ve Had Statistics for Centuries?

Irving Wladawsky-Berger

Data Science is emerging as as one of the hottest new professions and academic disciplines in these early years of the 21st century. A number of articles have noted that the demand for data scientists is racing ahead of supply. So, what is data science all about?

As Big Data and AI Take Hold, What Will It Take to Be an Effective Executive?

Irving Wladawsky-Berger

Big data , powerful analytics and AI are everywhere. First, much still needs to be done to create the proper data sets that would enable intelligent computers to assist in decision-making. Analysis is essentially rational, quantitative, data-driven decision making and problem solving.

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The Blockchain and Open Innovation

Irving Wladawsky-Berger

Transformational innovations don’t always play out as originally envisioned. It’s too early to know if the blockchain will become another major transformational innovation. Once in the marketplace, they seem to acquire a life of their own.

Serverless Computing - An Innovative Approach to Software Development

Irving Wladawsky-Berger

It is becoming more centralised again as some of the activity moves into data centres. Any information that needs to be persistent across invocations must be explicitly stored in a separate file or data base. Cloud Computing Innovation Services Innovation Technology and Strategy

Reflections on the Education of Applied Data Scientists

Irving Wladawsky-Berger

About a year ago, an article in the Harvard Business Review called data scientists the sexiest job of the 21st century. Patil , succinctly defined data scientist as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data.”.

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The MIT 2017 Inclusive Innovation Challenge

Irving Wladawsky-Berger

How can we accelerate the transformation of institutions, organizations, and human skills to keep up with the quickening pace of digital innovation? I was really impressed with their innovative ideas, courage and determination as they addressed some of society’s toughest problems.

Fostering an Innovation Culture: Talent, Discipline and Leadership

Irving Wladawsky-Berger

Innovation has been a hot topic for the past few decades. Companies all over the world have integrated innovation into their overall strategies and marketing campaigns. True innovation is, in fact, not all that much fun. In the end, necessity is the mother of true innovation.

Once Lumbering, Now Innovative Incumbents Hit Their Stride

Irving Wladawsky-Berger

Last year, IBM’s Institute for Business Value published Incumbents Strike Back , a global C-suite study based on survey data from over 12,800 executives from 112 countries, including CEOs, CFOs, CMOs, COOs, CIOs, and CHROs.

Innovation at Google: the physics of data

George Siemens

An interesting talk by Marissa Mayer on Innovation at Google: the physics of data. She argues that three key changes exist around data: speed, scale, and sensors (new means of collecting data). Around the 30 minute mark she nicely sums up Google philosophy: find innovation weak points (areas where technology has advanced, but hasn’t been applied to “real world&# problems) and exploit opportunities to improve the end-users experience

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The Impact of AI on R&D and Innovation

Irving Wladawsky-Berger

For the past couple of centuries, general-purpose technologies (GPTs) have been the key drivers of productivity and economic growth, - thanks to their rapid improvements in price and performance, pervasive applications, and ability to spur complementary innovations across a wide variety of industries. Beyond innovations in existing sectors, the rapidly improving price/performance of GPTs have led over time to the creation of whole new applications and industries.

The “Recombinant” Nature of Digital Innovations

Irving Wladawsky-Berger

Customer self-service is an excellent example of recombinant innovations , which UC Davis professor Andrew Hargadon defines as innovations that “rather than chasing whole new ideas, [are] focused on recombining old ideas in new ways.” Is innovation accelerating or slowing down?

Innovation on the cusp: symbiosis

Dave Snowden

Over the last year I’ve been starting sessions with my use of Apex Predator theory to combine Moore’s Crossing the Chasm with Clayton Christensen’s ideas of disruptive innovation and various uses of S-Curves. The post Innovation on the cusp: symbiosis appeared first on Cognitive Edge.

Embracing Disruptive Innovations: Organizational Challenges

Irving Wladawsky-Berger

I was there in my role as a board member of the Institute for Data Driven Design (ID3) , a research and educational nonprofit established to help define the principles, contracts and rules needed to empower individuals to assert greater control over their personal data and digital identities.

Organizing Big Data Initiatives: Lessons from the Internet

Irving Wladawsky-Berger

In a recent CIO Journal article, Is There a Leadership Vacuum for Big Data? , About 80 percent of the participating companies said that they were already using big data and analytics to a greater or lesser extent.

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The need for innovation across boundaries and the power of big data analytics

Ross Dawson

The primary themes of the report were around spotting opportunities, innovation, transparency and trust, personalization, and 24/7 availability, and the implications for business.

innovation means learning at work

Harold Jarche

“So it is important to understand that there is no one-size-fits-all philosophy in terms of successful innovation. Innovation is continuous. Successful innovators and entrepreneurs all embrace change and the risks that they pose. Innovation and Learning. Innovation

Blockchain and Public Health Solutions

Irving Wladawsky-Berger

The roundtable’s findings and recommendations were released in early April in Blockchain Solutions in Pandemics : A Call for Innovation and Transformation in Public Health. But countries with more limited data capabilities, - e.g., Italy, Spain and the US, - have fared significantly worse.

The Complex Nature of Cloud-based Innovation

Irving Wladawsky-Berger

I find it helpful to look at cloud along two key dimensions: as a technology to improve IT productivity, and as a platform for enabling business innovation. Only one company in six viewed cloud as a way of fostering business innovation.