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What Comes Before Automation?
In the beginning there was augmentation...
Bobby Brazen
November 01, 2022
Here's your daily briefing:
Is it just us or is this ridiculously cool?
1/6
How I transferred a physical toy to the digital world in one hour with AI-> LumaAI (3D scan)
-> Cinema4D (editing)
-> Mixamo (rigging and animation)
-> MetaSparkStudio (AR)— Sergei Galkin (@sergeyglkn)
1:05 PM • Nov 1, 2022
We really liked this interview Sar Haribhakti did with Cristóbal Valenzuela, co-founder and CEO of Runway AI:
Some of the ideas discussed:
Being in the limelight
Early sentiment around AI content creation
Runway's evolution
Web browsers as tool-making platforms
Ethical dilemmas around generative AI
The rise of Generative AI, among other techniques, will enable a new class of filmmaking and video-making possibilities. It will be comparable to what happened with the rise of CGI in the early 90s. If you pair this generative content with the automation tools we’re already seeing, the next generation of creators will be equipped with a unique toolbox of expressive tools that were previously unavailable. It will revolutionize industries forever.
Speaking of Runway, they just dropped this demo video of their cool new "infinite image" tool:
Learn to use Infinite Image, our newest AI Magic Tool 🪄
— Runway (@runwayml)
4:31 PM • Nov 1, 2022
Very cool thread from artist Trey Ratcliffe about how generative AI is "like having a very creative assistant around you all the time, making wild suggestions that you may never think of":
34 Crazy Photos From Burning Man That Don’t Exist - AKA How Artists Can Embrace AI - Part 1 - The First 4
I have an interesting theory on AI – I believe a very interesting future for all artists is to “team up” with AIs to form an UberArtist...
1/— Trey Ratcliff (@TreyRatcliff)
5:04 PM • Nov 1, 2022
We just read this piece by Brian Eastwood from MIT Management about Tom Davenport's (co-authored by Singapore Management University professor Steven Miller) new book...
...and we thought we'd share some of the main takeaways we got from it.
Davenport makes the claim that full automation works best in familiar and well-defined situations where "the nature of the unexpected is somewhat familiar." This makes intuitive sense. It's clearly far easier for an AI to do something once we know how and why it should be done than it is to ask AI to figure out what we should be doing and how to do it.
Davenport's co-author Miller reiterates this point, saying that "the human mind is particularly suited for creativity, wisdom, and context — not just realizing that something can be done, but whether it should be done. In other words, don’t underestimate what humans can do."
Because of this, they assert that for the time being, the name of the game is augmentation as opposed to full automation. It's not (currently) a matter of AI versus humans but AI plus humans. That's the intersection where the most potential currently lies.
That being said, Davenport and Miller argue that most people/companies these days nevertheless underestimate the opportunities of augmentation.
Eastwood quotes Miller as mentioning, "There are more opportunities than people assume."
The article goes on to highlight 4 key (and overlapping) scenarios for which Davenport and Miller believe AI augmentation is best suited:
When companies want to experiment. Product development is especially expensive in the pharmaceutical industry, where the median R&D cost for new drugs is now north of $1 billion. Instead of spending up to a year working on a drug only to realize that it’s not going to work, pharma manufacturers are creating AI infrastructure to assess their data and evaluate potential use cases for a new drug in as little as two weeks, Davenport said. Not only does this support frontline workers, it also leads to new “data product” roles to manage these AI use cases.
This reminds us of a heuristic by Jim Collins, author of Good to Great, best summarized as "fire bullets before cannonballs." The idea is that it's best to try small experiments or place small bets to calibrate one's aim before going all-in.
When there’s a lot of pencil-pushing. “Every businessperson we meet, and any company we talk to, almost always has the same lament: ‘We have so much to do, and we don't have the headcount to do it.’ At the same time, they complain about how much grunt work they have to do,” Miller said. In these situations, he added, automation will free up employees to do more of the experimental work augmented by AI, from product development to predictive analytics.
Isn't this the ideal for AI? The more and more "grunt work" we can outsource to machines, the more we humans can focus on what we're best at: creative and emotional intelligence.
When things are happening quickly. Cybersecurity monitoring software can assess threats from millions of sources in real time. Some tools can also prioritize threats and even automatically respond to them — by shutting down a compromised device, for example. But in “complicated and nuanced cases,” Miller said it takes an experienced security analyst to assess all the data collected and determine whether something is a one-off incident or an indication of a pattern of attacks that may require mitigation on a larger scale.
And, if you haven't noticed, things are happening increasingly quickly as the world becomes ever more technologically complex and interconnected.
When workers want a recommendation. When consumers put their trust in health care professionals, augmentation acts as form of decision support. For example, AI looks at the available information and makes a recommendation, but the final decision is up to the doctor in front of the computer. In countries such as China and Indonesia, where hundreds of millions of patients have access to AI-powered diagnostic tools such as Ping An Good Doctor, “A physician actually has to produce the diagnosis and the treatment, or else it’s not valid,” Davenport said. “But the AI system does save the doctor a lot of time and effort.”
A second (or third or fourth) opinion is always better than one, isn't it?
—
For more insight about how AI can be used to your or your company's advantage now and in the near future, be sure to check out the book:
"a human mcdonalds employee flipping burgers next to a robot serving french fries"
