KMWorld 2024 Is Nov. 18-21 in Washington, DC. Register now for Super Early Bird Savings!

The rise of machine teaching

Article Featured Image

Machine teaching versus machine learning

Some jobs in information management can be adversely impacted by machine learning/AI—jobs that can indeed be automated and removed from the human payroll. We should never fall for the “but those people will be free to do more interesting work” line. In contrast, KM practitioners have the potential to see their skills in much higher demand and volume in the future. The new KM systems currently on and coming to the market are centered around the concept of machine teaching rather than machine learning. The basic concept of machine learning is that it is a system that automatically learns and improves from experience without being given explicit instructions. Machine teaching, on the other hand, relies on human expertise and skills to find solutions. AI often struggles to learn and find solutions since, again, it’s often not as smart as we think we think it is. By taking the machine teaching route, we accept its limitations from the get-go, apply our knowledge and skills to the problem at hand, and use AI/machine learning to help us speed up the task.

There is no doubt that some of these new systems will hit bumps in the road, and that expectations may not always be met. Many of those bumps may come from the fact that good KM practitioners are in short supply and will remain so for the foreseeable future. But, that also means there are tremendous opportunities ahead for some.

KMWorld Covers
for qualified subscribers
Subscribe Now Current Issue Past Issues