At long last, the conference of the future

In past epochs, usually when a civilization is at or near its peak, the architecture of prominent structures masterfully blends the physical and the cognitive.… we need to be thinking along the same lines as we build platforms for interacting in an increasingly virtual world, including virtual conferences.

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.

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.

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.

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.

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.

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.

Flipping data science

No matter how much "intelligence" is programmed into a computer, it will very likely never understand the results it produces. Doing so takes human cognition, intuition, judgment, and other ways we humans make sense out of data.

The convergence of convergence

The more systems and subsystems we attempt to stitch together, the greater the unpredictability.

The future of food: a fresh look

There's a growing demand for the ability to facilitate the integration of knowledge generated by widely diverse communities from multiple disciplines.

The future of education

Today, we find ourselves in a highly networked knowledge-based economy. This new world demands radically different learning approaches in alignment with complex behaviors of natural systems.

Trends for the ’20s

Providing the right information to the right people at the right time can only be accomplished through greater openness.

Crossing the epistemic divide

As the world races ahead, purely data-driven approaches will become less attractive. Instead, we need to start gaining a deeper understanding of how to bridge the great divide which separates the artificial and the natural.

From just-in-time to just-ahead-of-time

Through our many decades of research into the knowledge sciences, we've determined that if AI is ever going to live up to its promises, it needs an architecture that integrates three levels of functionality: memory, awareness and anticipation.

A deep future approach to KM

We're familiar with the near-term portion of the time spectrum—from femtosecond lasers used in eye surgery to high-frequency trading in milliseconds on the major securities exchanges. Unfortunately, the extreme opposite end of the time spectrum, the "deep future" receives little if any attention. Decisions in fields such as genetic engineering, nuclear energy, geopolitics and the like can have serious implications for human civilization. But the impact of those decisions might not become apparent for many thousands of years and hundreds of generations.

Critical capacities for navigating in turbulent times

To navigate better in severe turbulence, three critical capacities are needed: foresight, agility and resilience. Those capacities have always been fundamental to sustaining high performance in knowledge-based organizations. But during times of turbulence, they need to be operating at peak levels.

No one left behind

It's inexcusable for anyone with a serious disability to have to wait for technology to catch up. It's here already. It's the user community that needs to catch up. And we KM'ers need to be right out in front.

Getting back to basics

From outright survival to the innate human desire for peace and prosperity, there's no shortage of needs.

The high cost of not sharing

Assembling and exchanging the necessary situational knowledge in a way that protects civil rights and privacy remains an enormous challenge.

What not to worry about

There's still plenty of thinking, innovating and discovery that needs to be done. Use machines as your tools, not as your master.