What you see here is the last week’s worth of links and quips I have shared on LinkedIn, from Monday through Sunday.
For now I’ll post the notes as they appeared on LinkedIn, including hashtags and sentence fragments. Over time I might expand on these thoughts as they land here on my blog.
One of my favorite ways to describe a risk is “a question mark on your balance sheet: you don’t know what the date will be, nor how large the amount will be. But it’s in there.”
Generative AI/LLM tools represent a special kind of question mark because they operate in an unclear legal zone. Will the lawsuits against OpenAI and other providers lead to significant changes in their offerings? Will downstream clients be sued for using those tools? It’s up in the air, which makes some companies hesitant to use or build on those tools.
Some LLM providers have promised legal assistance to reassure their end-users. This week OpenAI joined that list, saying they’ll step in if someone faces a lawsuit for using tools like ChatGPT:
“AI Legal Protections May Not Save You From Getting Sued” (Bloomberg)
So much for those question marks on your balance sheet, right?
Well, sort of:
The predictable truth, of course, is that if you read the fine print, the protections offered are narrower than what’s suggested by the PR — and by Altman’s curt answer at the press conference. For starters, the policies apply only to commercial customers that are paying to use services like ChatGPT Enterprise and Firefly for Enterprise. These premium options can include an extra set of guardrails that preclude them from inadvertently using copyrighted material in the first place.
The article is a worthwhile read. From what I can tell: if you’re building on OpenAI or other LLM providers, you may still be on the hook. The question marks on your balance sheet may not have gone away after all.
Not every AI project will lead to earth-shattering changes in your business. And that’s OK!
I thought of that while reading a recent Money Stuff, “Some Startups Need a Second Chance.” The column explored investments in startups that didn’t meet their mission of changing the world, but can still generate respectable cash:
“Some Startups Need a Second Chance” (Bloomberg)
Sound familiar? If you’ve worked in this space long enough, you can think of several companies that were dead-set on data science/ML/AI driving dramatic change (with hockey-stick revenue/growth to match). While that result is more the exception than the rule, remember that even “halfway to hockey-stick growth” amounts to “very healthy business value.” And that is something to celebrate.
What if your AI plans didn’t take off at all? Is it time to close up shop?
Maybe. Maybe not.
This would be a great time to review your business model and your challenges through the lens of present-day AI capabilities.
In other words: it’s time to update your AI strategy.
There’s a good chance you’ll uncover new opportunities to apply AI (and BI, and ML) to your business. Those ideas may not revolutionize your product, but they could still lead to meaningful business efficiencies or product enhancements. The kind that translate to revenue.
Let’s say you’re interested in writing a fresh AI strategy. Where do you begin?
- Here’s a blog post I wrote about this in 2016. (Yes, seven years ago! That’s ancient history in internet-time, but the idea still stands.)
- For personalized assistance, please reach out – you can contact me here on LinkedIn, or through my website.
I write a lot about how companies can use AI. Here’s an example of how to not use AI.
Seriously. Don’t do this.