Nah, who am I kidding. I'll be harping on this topic again before 2024 is over. If you've followed my AI posts the past week, and thank you even if you read just one, then you saw I raised many concerns we should all be talking about before we jump into the AI pool.
Government regulations, employment laws, union/trade groups, corporate ethics/policies, DEI, disinformation, and misinformation to name a few of things we should be looking into first.
Besides all those, let's be real for a minute. We're still talking about AI in learning; LEARNING!!?
There's plenty of research and opinion out there about formal learning's lack of effectiveness in on-the-job practical application for performance improvement, no need to rehash that here, and as new technologies have come along, the results really haven't changed. Actual learning outcomes are better for certain, on-the-job practical application for performance outcomes, well..., that's a tougher question to answer.
There's no reason at this time to assume that AI will be any different than all the other technology we've thrown at formal learning over the past 20 years; remember all the hype about eLearning, LMS, LXP? The question isn't AI's impact on formal learning, the AI questions are:
- Is AI on the organization's radar? 90% of all businesses are small businesses and typically not the businesses that these hyperbole headlines are referencing. These businesses manage their workforce, budget and resources strictly as they typically don't have a lot of any to spare, so AI may be a ways off. If AI is on your organization's radar, "who what, when, where, why and how" will guide you to the learning and practice you need to support/use it. If it's not on your organization's radar, then you have time to play and learn.
- Will AI be in the workflow? How will it be used?? Who will be using it?? At what point(s) in the workflow will it be present?? What is the impact of the output from AI in and on the workflow?
- Where's the information coming from that feeds AI? Outside the organization's firewall? Depends on the policy. From inside the organization? Well, if your experience is anything like mine the internal information is often inconsistent, in silos and not tagged properly. Not even AI can solve this challenge. This problem is on us to create one true source of information from which AI can pull.
- Can it pass the test(s)? No, not functionality. Corporate tests to determine if the information received is correct, bias free and compliant.
- Will it be in your future role? If you follow job titles and descriptions on LinkedIn, chances are you have or will see changes to the typical L&D jobs. Responsibilities like employee engagement, retention, recruitment, OD, etc., are being blended into L&D jobs and vice versa. If your job is more than just L&D or a job function within L&D, will AI be in these spaces as well?
To summarize, all this hype about AI is often generated by those who stand the most to benefit from its use, or in some cases want to be see at the front of the transformation. Your source of truth is from your organization's leaders who will decide the "who, what, when, where, why and how" of AI; let that be your guide to your AI improvement roadmap.
Thanks for reading, until next time...
5 years building talent at SpaceX | 15 years building leaders in aerospace & technology | ex-Air Force Pilot & recovering Ironman
1 年Really great points to consider Joe. Though it is important to watch out for the next big thing or industry trends, if your organization doesn't think it is important, you can only take it so far.