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.
Instead of asking the tech industry for a six-month pause on AI research … why not instead ask lawmakers for an intense six-month effort of exploring AI-related policy and regulation?
What would solid, airtight data privacy laws look like? (Limiting the wholesale collection and redistribution of personal information could curtail a fair amount of AI misuse.)
What if companies that claim to provide “AI-driven” services were required to demonstrate more transparency? (What features went into this model? When was the data collected, and how?)
**How do we design laws that hold AI providers responsible for their products’ outcomes? ** (See: consumer lending laws that require companies to disclose why someone was rejected for a loan. These laws don’t outright forbid black box models, but a lender will think twice before using them.)
And so on. This could do wonders for helping to integrate AI-based solutions into society while protecting people from the downsides.
I thought this field was over “move fast and break things,” but … I guess not?
“In A.I. Race, Microsoft and Google Choose Speed Over Caution” (New York Times)
I have to admit, this one did not make it to my risk bingo card for EVs:
“Heavy EVs Could Collapse Old Parking Garages: Report” (The Drive)
This is a reminder that every new device or technology bundles a mix of benefits and drawbacks. No matter what the hype crews and naysayers try to tell you, it’s exceedingly rare that the New Thing is 100% one or the other.
And as that New Thing interacts with the rest of the world, it’s going to encounter Existing Things that simply weren’t designed with it in mind.
All of which comes back to risk management. When the New Thing is meant to replace some Old Thing, it helps to compare them across all attributes – not just the ones you want to promote – and assess impact.
Yesterday I dropped the phrase “risk bingo cards” without explaining it – here’s a quick writeup from last year:
AI meets fashion.
“What to expect at the first AI Fashion Week” (Vogue Business)
While excitement about the potential of AI is rising fast, there’s also a degree of hesitancy. LCF’s Drinkwater argues for a more balanced perspective. “The discourse around AI has for too long been ‘utopia or dystopia’,” he says. “There are immediate use cases for the technology to improve efficiency across design, marketing, logistics, supply chain and store operations. Fashion must improve its knowledge, skill sets, understanding and application of these technologies to deliver more sustainable business models.”
This applies to quite a few domains that are embracing AI … not just fashion.
Note one key aspect of how this team uses generative AI: there’s always a human in the loop.
(Also, note the time savings: from “months” to arrange a photo shoot, down to “three weeks.”)
“Inside the creation of Revolve’s first-ever AI-generated billboards” (Business Insider)