The Tipping Point
We’ve become accustomed to data-driven, rapid scaling up: climbing likes, unfurling comments, increasing dollars. It’s much the same as the way a cell phone feels like part of our hands. This is the tipping point from hyper-aware to part of our mindset: We don’t need to think about where the phone ends and we begin. We don’t need to question that green bar filling its frame on gofundme.com or that rising dollar amount. We know the program is reacting to data that, in turn, is reacting to us. At this point, we accept that we’re learning from each other.
The boundaries are tumbling down between people and tech. The implications for HR make this year’s conference a must. Whether you’re going or not, here are four strategies to ride the wave:
- Don’t Think Big Data
Reality check: For most organizations, HR is not going to be working with Big Data. You’re going to be working with smaller data. The challenge is not gleaning massive amounts of recruiting, hiring, engagement, performance and retention data from millions of employees. The challenge is making the data unified so you can utilize it and create metrics that mean something. Look for powerful tools that do just that, using the principles behind Big Data but on a far smaller scale, shrinking down tools so the same effectiveness applies to smaller enterprise. As we become far more used to working digitally that means being able to scale down as well as up — the same camera, with a different lens.
- We Need Chatbots
Yes, there was hoopla surrounding the unfortunate blunders of Microsoft’s chatbot, Tay. But Tay has been rehabilitated and there are far more instances where chatbots are working and will benefit HR. Chatbots on company websites and social media channels will be a boon for attracting far more talent and then helping turn that talent from passive into active candidates. In terms of talent management, the possibilities are endless, from onboarding to management. If you don’t have it, you’re going to get left behind. The IBM Institute for Business Value found that a full 65% of CEOs are expecting cognitive computing to drive significant value in HR. I don’t think AI and cognitive computing are options anymore, they’re a must: If the U.S. Army has a chatbot, SGT STAR, to answer potential enlistees’ queries, and we are making all sorts of noise about how candidates are consumers of employer brand, do we really have to wonder anymore?
- The End Of Machines?
Tipping point or not, we aren’t done: AI may not always be bound by the constraints of a machine and its power. There’s a kind of nature versus nurture debate happening not over people, but over deep learning. This may feel like the equivalent to a star glimmering from a far away galaxy, but think again: things happen fast in tech. It’s possible that just as we’re comfortable installing the latest software, we’re going to learn that we don’t even really need it: the chip itself is enough. I’ll leave cognitive scientists to debate this. But it shows that there is no such thing as complacency anymore. That’s another side to this transformation.
- Get Over Bias
I’ve argued before that tech is going to help us be better human beings. To me, this is the whole point and why I continue to champion innovation as well as keeping the human in HR. Tech can help, so long as we agree to agree on the criteria. A more diverse workforce is a more productive workforce, but it’s also time to catch up on this in terms of humans before the next wave overtakes us. We can learn to overcome bias, unconscious or otherwise, by using technology and analytics to teach us what we’re doing right and what we can do better. And then we can apply those lessons to the next generation of employees, which may well be partly generation Bot. (Wink, wink.) Once that happens, the very definition of HR is going to take on a whole new meaning. We’d best be ready. I know I for one am very excited about it.
A version of this post was first published on Forbes.