Here’s a quick breakdown of Microsoft’s work trend research. You can download your copy here. These are my personal takeaways.
A couple of years into the generative AI explosion is revealing the impact of these tools on employee productivity.
Here’s what you need to know from studies by:
- Nielsen Norman Group
- Boston Consulting Group
I’ve spent the last year trying to navigate the Matrix of generative AI.
About 7 months back, I decided to delve deeper into the poster boy for the Gen AI scene in ChatGPT from OpenAI. These are the 5 lessons learnt so far in this journey of self experimentation and guidance from smarter people than I.
1/ It’s Narrow AI
✍️ ChatGPT is a ‘Narrow AI’. That basically means it focuses on one task/s only. It’s limited and needs supervised learning from you (the human).
🤖 Artificial General Intelligence (AGI) is what you see in the movies like Terminator and Ex-Machina. This is a self-aware form of technology. One that thinks and learns independently. It does not need human input.
Generative AI tools such as ChatGPT will change the way we work and even search for information. They won’t be taking over our world anytime soon (at least I hope so).
2/ Never Prompt and Ghost
ChatGPT is not a mind reader.
I’m sorry to break that to you. Nor is it some kind of magic where it just ‘gets it’. If it helps, imagine CGPT like an intern.
They don’t know what they don’t know but you can help them unlock their capabilities with the right instructions. You wouldn’t talk to them once and then give up if they didn’t get it the first time, right?
The secret sauce is in building an ongoing dialogue between you and the tool.
3/ It Needs Clear Input
Better input = better output.
If you were tasked to complete a big project you had never done before and were only given one sentence of information, how would you feel? Lost? Exactly. Now you know how CGPT feels.
Prompts need 3 things to do well:
4/ It Needs A Human Touch
60% = CGPT, 40% = Human.
ChatGPT is not a silver bullet. It’s not going to create high-quality content as good as a human. It doesn’t think critically and has no clue about real emotions.
But you do.
You must co-create not delegate. More on that in our fifth and final lesson.
5/ Review, Edit and Challenge
Never use any output from ChatGPT without:
- Reviewing content
- Editing for your audience and style
- Identifying and challenging bias
- Fact-checking research and data
Large language models like chatGPT are only as good as the data they’re trained on. So, if that’s rubbish then you must be cautious.
Generative AI can and will hallucinate. It’s up to you (the human) to always review, edit and challenge outputs.
Before you go… 👋
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In Josh Bersin’s latest focus on generative AI in business, his team spoke with over 200 clients about their current relationship with this technology.
Josh shared that the excitement is overwhelming but the actual understanding of this technology is very low.
“First, about a third of the HR leaders and professionals we talked with are still figuring out what this is. They’re not sure how these things work, they’re confused about the proliferation of LLMs, and they haven’t come to grips with the complexities of “prompt engineering” yet.”
This matches data from my own report in the L&D world.
130 L&D teams took part in the State of Generative AI in L&D report.
Generative AI is happening whether you like it or not.
So why ignore it?
Here’s 3 ways to get ahead of this in your work 👇