Let’s face it, you’ve all heard the term “artificial intelligence” or “AI”. I read a couple of years ago that it’s the single most overused term in technology. And we’re seeing AI everywhere in our daily lives and more and more in legal technology. But are you familiar with the term “augmented intelligence”? You’re seeing that too, you just don’t realize it.
As stated by IEEE: Augmented intelligence is a subsection of AI machine learning developed to enhance human intelligence rather than operate independently of or outright replace it. It’s designed to do so by improving human decision-making and, by extension, actions taken in response to improved decisions. Another term for it is “intelligence amplification”, so the typical acronym for augmented intelligence is “IA”. AI was already taken. 😉
Unlike the traditional view of AI as an autonomous system, operating without the need for human involvement (which is scary and intimidating to a lot of people), IA uses machine learning and deep learning to provide humans with actionable data. If you’ve used Alexa, Siri, or another virtual assistant, you’ve used IA. Virtual assistants don’t make decisions for you. Instead, they provide the data you need when you need it. When it comes to big data, think of IA as virtual assistants for data scientists, who would otherwise be faced with a big, big problem.
So, a lot of the AI and machine learning processes you know may technically be IA processes if they enhance rather than replace human intelligence. Make sense?
Of course, just as many of us use the term Technology Assisted Review (TAR) interchangeably with the term predictive coding (even though predictive coding is considered just one form of TAR by many), people will use the superset term AI interchangeably with the term IA, even though IA is a subset. Just remember that if someone uses the term AI to reference some form of machine learning technology, the term IA may be more technically correct.
Why do I bring this up? Today at Corporate Counsel Business Journal (CCBJ)’s ELITE LegalTech virtual event, I will be moderating the session From Complexity to Clarity: Harnessing the Right AI for Your Legal Processes Now and Tomorrow on Thursday, May 6 from 12:40pm – 1:25pm ET, with a 15-minute breakout session afterward for further Q&A on trends, and an AI (or IA) case study from H5, the sponsor of the session. A description of the session is available here. I’m delighted to be presenting with:
- TracyAnn Eggen, Manager of eDiscovery Solutions for Investigation and Litigation, Dignity Health
- Jake Harrell, Division Counsel, Enterprise Data & Digital Health, AbbVie; and
- Eric Pender, Engagement Manager, H5
It should be a great discussion regarding use cases for AI and the significant competitive advantage enabled by AI adoption. Come join us!
Tickets for CCBJ’s ELITE LegalTech event are still available here and they’re FREE (at least if you’re an in-house legal professional, law firm professional or individual or institutional investor). It should be enlightening and educational!
So, what do you think? Were you familiar with the term augmented intelligence before reading this post? Please share any comments you might have or if you’d like to know more about a particular topic.
Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer, my partners or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.
“So, what do you think? Were you familiar with the term augmented intelligence before reading this post? Please share any comments you might have or if you’d like to know more about a particular topic.”
The term and ideas behind IA go back to 1968, at least:
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.729.3287&rep=rep1&type=pdf
I do think that there is nuance to this statement, though: “IA uses machine learning and deep learning to provide humans with actionable data.” IA can use a lot of things, not just machine learning. And currently, deep learning is not a very suitable technique for IA, because it is not very explainable or transparent. And it also requires massive amounts of training data for it to work properly. IA is more human scale.
Otherwise, if you’re further interested in the interplay between AI and IA, you may be interested in this workshop that is being organized as part of this year’s International Conference on AI and Law (ICAIL). The workshop includes organizers from Thomson Reuters, OpenText, H5, TextIQ, Brainspace, Disco, and Legal Robot, as well as academia.
https://sites.google.com/view/legalaiia-2021/home
I had a feeling you’d have something to say about this topic, Dr. J! Thanks for the additional info, great stuff as always! And, yes, the term and ideas behind IA have been around a long time, though I’ve found many people don’t know the term and how it differs — hence, my reason for the post today! 🙂
I agree.. still a lot of confusion around the term for sure. And in practice, most systems are a mixture of both AI components and IA components. Some have more of one or the other, but most things are a mix. Now, in terms of what is better, that’s where I wish we did a better job at vetting. In being able to ask questions that aren’t about what something is, but about what it does. In the being vs doing debate, I’ll take the doing, every time 🙂