ILTACON Video Killed the Radio Star

Video Killed the Radio Star

In 1978, Trevor Horn, Geoff Downes, and Bruce Woolley wrote a catchy earworm…ahem…jingle that focused on “promotion of technology while worrying about its effects” and “concerns about mixed attitudes towards 20th-century inventions and machines for the media arts.” (Wikipedia)

Doesn’t this sound remarkably contemporary?

The song’s video went on to become “the first music video shown on MTV in the United States at 12:01am on 1 August 1981, and the first video shown on MTV Classic in the United Kingdom on 1 March 2010.” (Wikipedia)

ILTACON Video

I really did intend to provide a recap of some ILTACON highlights as soon as I returned from Vegas. However, life intervened and I found myself on the road again. Therefore, I’ve decided to focus on some highlights that happened outside the formal ILTACON sessions but were captured by ILTACON TV. Thanks to the wonderful folks at ILTACON TV, I was able to have extended conversations with the conference’s keynote speakers: Pablos Holman, Brian Kuhn, and Shawnna Hoffman. All of the conversation ran overtime. However, we do have a bit of video to share with you now.

Below you’ll find my interviews of Pablos, Shawnna, and Brian. In addition, I’ve linked all the rest of my ILTACON blog posts so you have them in one place. Finally, I’m including a video of the infamous song that started this post. Unfortunately, it doesn’t appear to be the original video but it certainly is enough to induce a bit of nostalgia among my more seasoned readers and, perhaps, introduce millennial readers to a classic.

Pablos Holman

 

 

IBM Watson Legal with Shawnna Hoffman and Brian Kuhn

 

A Roundup of my ILTACON 2017 blog posts

 

Video Killed the Radio Star (1979)

There you have it. And I bet you won’t be able to stop humming the song. <Sorry!>

While these ILTACON videos may not kill a radio star, they certainly have lots of interesting information for you to chew on over the long weekend. Hopefully, their lessons will endure nearly as well as the one cheesy song that started this post.

Have a great long weekend!

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Keynote: Transforming the Business of Law with Cognitive Computing – Watson Legal #ILTAKEY2 #ILTACON

Session Description: “Artificial intelligence” (AI) is arguably an overused label for a vast array of technologies that vary in features, complexity and benefits. What is AI, and how do you know if you have a problem it can solve? Brian Kuhn (founder of IBM Watson Legal) and Shawnna Hoffman ( IBM Global Co-Leader, Global CoC) will address key misconceptions around artificial intelligence and cognitive computing and share insights from business-of-law use case workshops IBM conducted with corporate legal departments and law firms over the last two years. Brian and Shawnna will identify patterns of customer interest and success related to the application of artificial intelligence and cognitive computing to the legal domain, and he’ll discuss the top facts everyone needs to know about what AI can — and can’t — do.

Speakers:

  • Brian Kuhn, Esq., Global Leader and Co-Creator of IBM Watson Legal
  • Shawnna Hoffman, Global Cognitive Co-Leader, Global CoC

[These are my notes from the International Legal Technology Association’s 2017 Conference. I’m publishing them as soon as possible after the end of a session, so they may contain the occasional typographical or grammatical error. Please excuse those. To the extent I’ve made any editorial comments, I’ve shown those in brackets.]

NOTES:

  • What is AI.  A type of tool to extend our cognitive abilities. While computers have extended our cognitive abilities, 88% of the data we have created is “invisible” to us. It is rendered invisible because it is unstructured — narrative creative for consumption by humans rather than computers. The language is context heavy and may be rife with ambiguity. Historically, computers have been unable to parse unstructured data because they did not understand human language.
  • AI is an umbrella term. There is no single agreed definition. It is a constellation of capabilities (e.g., machine learning, neural networks, etc.)
  • Cognitive Legal. All cognitive systems understand human language, they can reason to extact ideas, they can learn from past results, and then they can interact in a natural way. They can read 800 million pages per second and, in the background, derive meaning and form hypotheses based on this work.
  • Cognitive systems democratize knowledge. They have the capacity to read and understand more content than humans could do in a lifetime. And the cognitive systems can do this in a matter of days or weeks. Better still, while human intelligence is focused on discrete bodies of knowledge that leads to deep expertise, cognitive systems can consume and comprehend multiple domains of knowledge and derive new insights that humans could never reach by themselves. This ability to synthesize information from across domains of knowledge will profoundly alter professions.
  • How do you know you have a problem AI can solve? IBM’s Cognitive Legal practice focuses on the business of law rather than the practice of law. This was the choice of their clients. They have been identifying use cases that:
    • provide tangible business value
    • identifiable key performance indicators
  • Identifying good use cases.
    • Wha are the painpoints?
    • What is hte business value of this use case?
    • Has the content that will fuel the solution been identified?
    • The best use cases provide
      • organizational beef
      • end-user benefit
      • strategic alignment
      • speed to implemention
  • Examples of Use Cases.
    • Outside Counsel Insight — designed to reduce spend on outside counsel by
      • automating manual invoice review processe to detect billing anomalies,
      • producing insights into trends and patterns that demonstrate the quality of outside attorney performance, resulting in outcome and price consistency,
      • producing brenchmarking insights at the case and line-item level that establish a reasonable level of effort for repeatable legal tasks, which then helps justify fixed-fee pricing arrangements versus hourly billing.
    • Early Case Insights
      • Consuming historical work product by outside counsel to provide appropriate advice for repeatable work and new insights to address current needs — without reinventing the wheel or pay again for the work to be done
    • Expertise Finder
      • using internal and external data
      • it could be used across a network of organizations or law firms. The underlying data would reside in public filings or even in a private blockchain.
  • Cognitive Legal “Cartridge”. We will be training “cartridges” in what and how the people of your firm think. Others could then purchase these cartridges and point them at their own data sources so that they can derive new insights by using what and how the people who trained the cartridges think. IBM Watson has done already by having three oncologists at Sloan-Kettering train a cartridge, and then applying that cartridge to the medical data collected by the largest hospital in Thailand.
  • Closing Insights
    • “Cognitive is a mirror you hold up to yourself.”
    • Use AI internally first. The power of AI lies in turning it onto your proprietary data. The richest data source is not located on the internet. In fact, 80% of data resides inside organizations and behind firewalls.
    • “We think about Watson in the context of AI — not artificial intelligence but augmented intelligence.”
    • Access to justice — 80% of people involved in domestic violence disputes represent themselves pro se in court. If there were a cartridge trained by domestic violence legal experts, that cartridge could help make sense of the data for each of those cases.
    • Legal Blockchain +AI:
      • blockchain contains enormous stores of data
      • AI can parse that data and make sense of it
      • blockchain and AI could be combined to create trusted and transparent self-executing contracts
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