This challenge, in part, is why my job title is now related to Information Governance and Compliance. It’s recognizing that data is a valuable asset and a significant risk. Grounding your AI in low-quality data is a massive risk
In the age of AI, though, this might be the high-priority risk. That old, untrustworthy, and outdated information that no one ever bothered to clean up is actively messing up your AI implementation. Your attempt to be a data-driven business depends on having accurate data. That becomes difficult to do when you’re not actively cleaning up after yourself.
We should always be thoughtful about what we say in meetings and how we say it. It’s just being professional, and now that we can also assume there will be a record of it, we have yet another reason!
Employees want to know they are being treated fairly and are trusted to find the best way to accomplish the required work. That doesn’t seem so difficult. Both of these things reduce the risk of burnout, a phenomenon that is becoming a workplace hazard everywhere. You would think they were asking for the impossible from the way some companies act, though.
So when they tell you that the risks and dangers are overstated, and not to worry about it, because the benefits will surely outweigh everything else, come back and remember that the wealthy said the same thing about slavery. For them, the benefits did outweigh everything else. That wasn’t the case for people who were different from them.
Perhaps we should include a bullet point or two in our business continuity plans for addressing AI outages. Of course, we might also consider the continuity plan for AI tools, or any SAAS solution, going under as well. It’s just good risk management.
How much of your AI work would be negatively impacted by even a few hours of downtime?