Three trends in ’23

The combined human and computing clouds will drive our core KM processes of search, collaboration, and discovery to new heights.

Writing as empathy

Communication is about revealing something about the world that the other person hasn't noticed—and often hasn't been able to notice because their ideas get in the way.

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.

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.

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?

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.

How robotic is your process ?

To break out of the structured process world, RPA will need to address the full range of cognitive computing capabilities.

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.

Ethical issues in AI and cognitive computing

Many innovations from the past needed the insight of entrepreneurs as well as technologists to change the world. That's also the case with machine learning and AI.

Data and our future: too much of a good thing? Not enough? How will we know?

In today's AI-exploded world, analysts and business people loudly call for more data, complaining that cognitive computing and other AI applications need more raw material to build better models and more accurate predictions.

Usability testing for effective interactivity

Connecting the seeker to the information she seeks is not a new problem. Interaction design has been a stumbling block since the age of the card catalog.

Coming soon to your newsfeed —Ethics and AI

People need to be sensitive to the many ways ethical judgments are being baked into the fabric of their AI projects.

Tools, senses, and machine learning

Machine learning sometimes extends our cognitive abilities in ways that are alien to our minds.

Rebooting the information refinery

In the field of knowledge management, of course, the idea of turning data into information into knowledge has been a foundation concept for knowledge managers. But frankly, the ability to achieve this alchemy of data to knowledge has not been broadly demonstrated in practice. A next generation information refinery is required to make something meaningful and valuable out of the raw data flying around the firm and throughout the internet economy.

AI: The issue is execution

By demonstrating on Jeopardy! that a machine could understand and analyze many fields of human knowledge and answer questions faster and more accurately than the reigning human experts, Watson's victory created an instant global brand.

Cognitive Computing: Another look at cognitive tasks

To build a practical framework for understanding what kinds of capabilities will be the key success factors for the intelligence economy, we need first to look hard at what kinds of cognitive tasks or capabilities are going to come into play to enable the innovations we will need as we partner more closely with machines. Can we delegate cognitive processes to silicon colleagues? How will we make judgments about what we need to retain as human responsibilities versus what we can partially or fully automate?

Cognitive Computing: Balancing the risks with the rewards from AI

The fact is that the effects of AI and cognitive computing will be even broader than current traditional computing systems. As we incorporate more and more data sources for better results, we also increase the likelihood of affecting more lives and more organizations.

Automating cognitive tasks: fact or fiction?

There is a long-standing debate in philosophical, psychological and educational circles about how to understand and measure intelligence. Is intelligence actually a singular thing that can be pointed to and measured, for example, by an IQ test? Or are there multiple kinds of intelligence whose existence and behaviors only come to light when individuals confront specific kinds of context in life?

My teammate the bot—really?

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.