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Columns

Thinking about KM differently

Moving to a push rather than a pull mentality simply means that we now have the technology to tag, manage, and interpret information automatically and near instantly—automatically pushing the right information to the right person (or application) at the right time.

The twisted case of facial recognition

Machine translation continues to make strides forward. Facial recognition, on the other hand, has entered the twilight zone.

Perspective on knowledge: Data is never just data

As with all tools, data has uses because of complex contexts that include other objects, physics, social norms, social institutions, and human intentions.

Disruptive innovation: No better time

With the push to move more functions online, disruptive technologies such as robotic process automation are rendering old skill sets obsolete, while at the same time creating the need for new ones.

The eureka moment

AI is beginning to develop some support for the thought process. As the technology improves, it's possible that AI will eventually be able to offer relationships and connections that still seem far-fetched.

Perspective on knowledge: Links then and now

Broken links used to be like potholes. Now there are entire neighborhoods that are gone.

Building the enterprise of the future: If not now, when ?

It should be plainly clear that we need knowledge management now more than ever. You can be sure that the COVID-19 crisis won't be the last crisis to come our way. And the next one might be even more severe because our supporting systems have taken some serious hits.

Thinking beyond the status quo

The technologies exist today to achieve almost any corporate or departmental goal. What is lacking is the nerve to think big and think beyond the status quo—to break barriers, to collaborate, and to share.

What happens when AI meets a pandemic?

This is what we can see clearly after some months of reading, watching, and listening to the pronouncements on the novel coronavirus crisis from around the globe: Content challenges continue to dog AI.

Enterprise of the future update: More disruption ahead

The concept of a phyle has experienced a resurgence, driven in part by the frustration people are feeling about being forced into making binary choices regarding the groups with which they want to be identified: public versus private, capitalist versus socialist, and liberal versus conservative.

Perspective on knowledge: Approximately causal

Science will not give up on hypotheses. But it already is becoming more willing to accept results based on the sorts of statistical analyses performed by machine learning. And it may be thatwhen science does rely on theories and laws, we will recognize that no matter how ironclad they are as generalizations, their application to a world of confetti will always and necessarily render them approximate and probabilistic.

The right time for knowledge management

A new generation is coming in—one that sees order in the chaos, spots previously invisible patterns, and not only embraces technology but grew up with it.

Cognitive computing and AI begin to grow together

How do we manage the hype and promise for new inventions while making sure that they represent a realistic opportunity? Can we invent self-driving cars or a Boeing 737 MAX without exposure to the risks these innovations can pose to our lives?

Perspective on Knowledge: 250 Columns later

Knowledge management has indeed become a multi-threaded discipline, embracing just about everything related to knowledge.

Deep project management

Given the increased negative media exposure that comes from project failure, organizations need more tightly integrated, intelligent project management systems, in addition to people who have the requisite skills. This need will grow as systems continue to become more complex and timelines more tightly compressed.

Perspective on Knowledge: The challenge of emergence

Traditionally, we humans have succeeded at building complex structures by breaking plans down into a multitude of simple, predictable, knowable causes and effects.

Boosting knowledge worker engagement through mentoring

If your employees aren't engaged, knowledge simply can't flow to the extent that's needed in order to compete in the global economy.

Talk a little, type a lot - Will conversational interfaces survive Siri and Alexa?

For the next generation of conversational computing, it is hard to avoid the conclusion that the only companies that have enough researchers, enough processing resources, enough motivation, and, above all, enough data to deliver the much- needed improvements are the consumer giants.

Perspective on Knowledge: Journalism’s new landscape

What's happening to news is a microcosm of what's happening to knowledge overall.

Bringing adult supervision to machine learning and AI

Human and machine knowledge governance has many moving parts. No governance means leaving things to chance. Too much governance means clogging up the system and slowing things down to a crawl. The trick is achieving the right balance based on your organization's size, goals, strategy, and risk profile.