The Imperative of Open Source in Leveraging AI in HR
We've never seen a technology as disruptive as AI in business - and the stakes for HR have never been higher.
This post is for my subscribers in the HR and people space.
I have a request: wherever possible, please build in public with your AI HR and talent initiatives.
We’re navigating a technology that’s disrupting our function like nothing before. The speed of AI adoption, its capabilities, possibilities, and risks are significant.
The stakes have never been higher. It’s crucial we learn from each other as publicly as possible.
There are real risks associated with AI—bias, homogenous development, over-reliance, lack of policies, compliance, and legal exposure. These are not just hypotheticals; they are real challenges we must address collectively.
The Power and Pitfalls of AI in HR
How and Where You’re Using AI:
AI’s application in HR is vast. From recruitment processes, where algorithms sift through resumes to identify the best fit, to employee engagement tools that analyze sentiment and productivity, the possibilities are endless.
Are you using AI for predictive analytics in workforce planning?
Perhaps you’re leveraging it for personalized learning and development programs?
Share your strategies and successes so we can learn from your experience.
Where and Why You’re Not:
Equally important is understanding where and why you’re not using AI.
Is it due to budget constraints, lack of expertise, or concerns about data privacy and ethics?
Being transparent about these barriers can help us collectively find solutions and mitigate risks.
What You’re Learning and Where:
The learning curve with AI is steep, but the rewards are massive.
Are you learning through pilot programs, partnerships with tech companies, or by investing in upskilling your team?
Your knowledge sources—whether academic, professional networks, or trial and error—are valuable insights for everyone.
Specific Use Cases: Hits and Misses
Use Cases That Work:
Let’s highlight the use cases where AI is making a real impact. For instance, chatbots that streamline the onboarding process, AI-driven analytics, and revamping organizational design leveraging AI for particular tasks.
These successes are the stories we need to understand and amplify to gauge what might work elsewhere.
Use Cases That Don’t (Yet):
Conversely, there are use cases that haven’t hit the mark.
Maybe an AI tool failed to improve recruitment efficiency, or a predictive analytics model didn’t accurately forecast workforce needs.
These “failures” are just as important to discuss because they offer lessons that can save others time and resources.
Embracing the Future: Beyond Legacy HR
We can’t afford to think like legacy HR anymore.
The zero-sum war for talent is outdated. Now is the time to open our collective playbooks and learn from each other.
By building in public, we create a knowledge-sharing ecosystem that benefits everyone.
Addressing the Risks
The risks of AI are real and need our attention. Bias in AI can reinforce existing inequalities if not carefully understood and managed.
Over-reliance on AI without “humans in the loop” can lead to a lack of human oversight and ethical considerations.
Policies often lag behind technological advancements, leading to unclear future compliance and legal challenges. This is particularly true with AI.
We need to have open discussions about these risks and work towards mitigating them.
Learning and Sharing Resources
I highly recommend Ethan Mollick’s book, Co-Intelligence, as a foundational understanding of this new AI era. It’s a fantastic resource that explores how humans and AI can collaborate effectively.
I’ll continue to curate and share articles, podcasts, research, and whatever else I’m learning.
If you have any helpful resources or practices you’re willing to share, please add them in the comments. I’ll compile them into an open-source resource to publish.
Now, let’s build together. Let’s learn and navigate this together as a community.
The future of HR depends on our collective intelligence and willingness to share.