Talent Pool

But at the end of the day, it was very meritocratic because the hackathon, the reason for why you were doing this was also very related to some of the things that are very important for you at the time of making a decision of who to hire, right? For them to demonstrate that they had the skills, but you were not so distracted or affected by the resume, right? where you start really seeing some of these credentials and some of these kind of signals that lure you away from really the goal that you have, which is giving an opportunity to someone that could be amazing.

But if I hadn't taken that step, of broadening and being experimental and try to really find talent in a way that maybe others are not doing it, this will have never happened, right? So that's, I think, one of the things that many organizations could do is go back to your organization, look at all these processes that you have in place, and do you see opportunities for improving the way you're going to be expanding the talent pool that you're going to be considering? that look as the relevant criteria, right? As opposed to, again, you know, like proxies.

You know, and I think that, Stuart, I think it's just really very relevant also now when we think about AI, right? Think about, as you can imagine, I've been paying a lot of attention to what AI can do or cannot do when it comes to really thinking about managing the workplace, right? So when there is like, you know, companies, organizations that are telling you we use AI in order to help you improve recruitment, right? and improve hiring, just think about that twice, right? I mean, what kind of data are these algorithms using when they're trying to really give you recommendations on who to interview from this kind of amazing pool of candidates, right? You should be, I mean, and one of the things that I say in my book, and I say when I present my book, You as leaders of organizations, as managers, as employees we're going to be hiring, you need to be almost like social scientists, investigators that say, to what extent this information that is being given to me is actually going to be relevant for the success of my organization? Should I trust this AI platform? Where is the data coming from? What kind of criteria is it using to make that decision, right? So it's very relevant that we, as social scientists, as practitioners, as managers, we kind of really go back to the workplace and diagnose where we think we may have problems.

Where are we not giving enough opportunity? Where are we being too narrow or too elitist or paying attention to the wrong variables when we're making decisions and how like some of this like a small interventions, right? Because I think of what you just did in this particular Harry situation was like a little intervention of some sort that was experimental at the end of the day, provided you with amazing outcomes.