It may be sad news for the data science cowgirls and cowboys: But the Wild West days of AI development are clearly over. And that may actually be a good thing as companies and individuals are realizing an old truth: With great power comes great responsibility.
The motivation to use AI in more responsible, more controlled ways is based on multiple sources: Ethical and societal responsibility as a good -corporate- citizen is a base. But in many countries there are now legislations -active and upcoming ones- that will legally mandate a level of scrutiny and responsibility. And many companies also realize that using ungoverned AI is just a bad business decision: Evaluating AI development processes and monitoring for metrics like quality, fairness and bias allows to manage risk and ensures long term success.
But doing the right thing is neither easy nor cheap: Establishing AI governance processes and tools can bloat bureaucracy and inhibit innovation. This is where tooling can help to balance oversight and control with productivity and innovation.
In this session we will discuss the drivers for AI Governance, the challenges that companies face in “doing the right thing” and we will show some of the tools and processes we have come up within IBM to meet these challenges.
Presenter: Thomas Hampp-Bahnmüller
For presenter bio, webex registration, and more details, go to https://www.meetup.com/ibm-canada-technical-meetup-group/events/287268932/#GlobalDataScience