The flip side of generative AI: Extractive AI

Extractive AI takes a more comprehensive and transparent approach to machine intelligence.

The trust problem with GenAI

2023 has been the year of ultra-hyping GenAI, and who is paying for this deluge of marketing? Technology vendors that want us to buy it. Again, it's impressive stuff, but when we shift from selling to buying and ultimately using it, many tough questions need to be asked.

When is good enough enough?

Our goal should be to improve the quality of knowledge assets and their accuracy and relevance in use. Much of this will come from human expertise and effort, increasingly combined with the power of AI.

Look to the skies for KM opportunities

Then there's the inevitable demand for more automation, from the flight planning and clearance process to the operation of the air vehicles themselves. No human or group of humans could possibly keep track of so many constantly changing variables

Finding the weakest link

Though traditional and often reluctant to change, the supply chain sector is now reassessing its lack of embrace of technology and, significantly, rethinking long-established processes.

The way of the scenario

The Delphi technique has become less effective in recent years, especially in crisis situations in which conditions, assumptions, and other variables are changing faster than the group is able to respond.

The convergence of convergence

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

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.