Category: AI

https://www.wired.com/story/artificial-intelligence-labor/

Here is our next AI challenge, as our jobs undergo gradual transformation. How will we as knowledge workers in informatics accommodate the growing sophistication of narrow AI assistants? Scheduling appointments, helping with spelling and grammar, now writing fluid manuscripts based on the library we point them to?

Teachers are starting to change “take home” assignments to in-class writing with no internet connection, to ensure students don’t outsource their thinking/writing to an AI chatbot.

What will we do? Can an AI replace us in writing the “one-pager” that summarizes thinking and succinctly and convincingly makes the case for change? Is Machiavelli vulnerable to being toppled? Do we no longer have need for governance and leadership if we can outsource thinking and fluency to an AI? Will my AI go up against your AI in the battle for mindshare?

Yes.

CMIO’s take? Yet again, time to re-imagine our jobs with the tools we have at hand.

https://www.technologyreview.com/2022/09/29/1060472/meta-text-to-video-ai/

Well, you thought AI-generated static images were both cool and concerning. Now, META (formerly Facebook) introduces AI-generated VIDEO based on simple user inputs. If distinguishing fake from real was hard before, where is this going?

https://www.wired.com/story/spotify-wrapped-user-data

https://www.wired.com/story/dalle-ai-meme-machine/

How can this be real? Read the story above at Wired.com.

I typed “Elephants breakdancing at midnight” into the prompt, and seriously, about a minute later I get this on my screen.

Let’s not go into why that sentence came out of my head thru my fingers, and instead focus on the technology. There is an AI, with the internet as infinite visual resource, that can now take brief text prompts and then render them for your viewing pleasure.

This is mind-blowing. Here’s “Frolicking Flying Cars”

Here’s “A family of dolphins using iPhones in the style of Picasso”

Here’s “Speed skating in the style of a Chinese landscape painting”

What is real? What is imaginary? Who drew this? Try it yourself at http://www.craiyon.com !

I’m always on the looking for developments in computing outside of healthcare. This is a longer read, but so thought provoking:

• What is a Large Language Model and why is it only recently important?
• What is GPT-3 and what are all these magical things it supposedly does?
• Can GPT-3 digest 1000 progress notes of a patient chart, say, and write a cogent 1-page summary for a clinician to digest rapidly? I’d pay for THAT.

‘‘The underlying idea of GPT-3 is a way of linking an intuitive notion of understanding to something that can be measured and understood mechanistically,’’ he finally said, ‘‘and that is the task of predicting the next word in text.’’ 

Prompt the algorithm with a sentence like ‘‘The writer has omitted the very last word of the first . . . ’’ and the guesses will be a kind of stream of nonsense: ‘‘satellite,’’ ‘‘puppy,’’ ‘‘Seattle,’’ ‘‘therefore.’’ But somewhere down the list — perhaps thousands of words down the list — the correct missing word appears: ‘‘paragraph.’’ The software then strengthens whatever random neural connections generated that particular suggestion and weakens all the connections that generated incorrect guesses. And then it moves on to the next prompt. Over time, with enough iterations, the software learns.

Ilya Sutskever

There is all this discussion of “is this a sophisticated parrot” or “truly an artificial intelligence capable of generating new ideas.” Well, in our Electronic Health Record world, just the first item would be transformative, if we can get an AI to digest a hyperobject large set of data into an executive brief. Just that.

CMIO’s take? This is an important article by Steven Johnson in the New York Times Magazine. Watch this space; the development of GPT-3 heralds a qualitative improvement in AI language models; so much so that we feel compelled to teach it values and culture lest it start spewing hatred it learns on the internet. This is a worthwhile long read.

https://www.wired.com/story/opinion-bill-of-rights-artificial-intelligence/

Read the Wired.com article. In brief, it outlines the emerging risks of relying on AI (artificial intelligence) tools that can unintentionally create bias and other consequences.

This is a nascent class of technology that, at its root, is often a black box: what is inside, is opaque to us, the users, and often to us as the designers.

I feel this critique personally. Having participated in the design of several AI tools in healthcare, I worry that, although we do our best, we don’t know what we don’t know.

CMIO’s take? I have no “best practice” lessons to impart here, on bias and the unknown. Do you? Please share. This is a big mountain we are about to climb, and we need to help each other.