Wiki Way Machine Learning
I’d like to understand Wiki Way Machine Learning
Most people understand what a wiki is: an editable, collaborative document that allows contributors to come together on the same page and progressively update and add content. What sometimes gets missed is how this develops a cultural attitude to collaboration and sharing that can really make a difference to businesses.
The Wiki Way Culture
For those born into a world of Microsoft desktop apps, we’re used to creating documents on our own, to then publish and share files using mechanisms like document repositories, file shares and email. This approach to content creation results in lots of people working in isolation, to then contribute their work for others to scrutinize as "finished articles". In truth, there aren’t many content authoring tasks in business that are best served by people working in isolation. And creating lots of files can result in version control issues, fat volumes of content that never gets used, and gigabytes of content that nobody curates.
So Is There a Better Way?
We would argue there is. The humble wiki creates a collaborative way of working with content that suits many teams and businesses better. It’s about encouraging people to invest time in activity threads that matter most to the team or community, to encourage individuals to apply their skills and capabilities for the betterment of the project. The wiki culture brings people together to work in near-real-time on a collection of activities, maximizing their skills, know-how and efforts. Once you have that culture in your team or business, people get accustomed to a better (and more productive way) of getting jobs done.
These cultural attitudes about how best to work together and work as a team to get the best outcomes ultimately transcend any wiki tool. You can apply these cultural norms of behavior and operating principles to lots of areas, including the creation of solutions using machine learning.
Framing Actions and Effort
Without some level of governance over how actions are managed, projects can quickly spiral out of control. For example, if contributors don’t know what the most important jobs to be done are, and team members keep adding activities without some basic checks and balances, taxonomy structures, etc. then you can imagine how diluted efforts become. For this reason, EvoluData and WikiSuite project teams have evolved working practices over the past decade framed around Tiki Trackers that install a light-touch level of governance that’s sufficient to frame activities without constraining individual contributions or innovation. This light-weight action framework, we would argue, is an essential ingredient in the effective operation of the Wiki Way.