• From Information AgeArtificial intelligence in the legal industry: Adoption and strategy – Part 1, an insightful discussion with Geoffrey Vance, the chair of Perkins Coie’s E-Discovery Services and Strategy Practice, and Alvin Lindsay, partner at Hogan Lovells. The discussion of the future role of associates is especially interesting, and several useful links are included.

 

  • Investment money pouring into legal AI. “Legal tech blogger Bob (“God”) Ambrogi just posted that $200 million in new investment capital has found its way to legal tech companies in just May and June of this year. The money went into companies that are either based in machine learning (sometimes called “artificial intelligence”), an increasingly important sector of legal technology.” The post from the Akron Legal News lists some of the specific investments.

 

  • According to Bloomberg’s Big Law BusinessAnalytics Give Law Firms the Competitive Edge. “Bob Ambrogi’s Law Sites Blog lists more than 690 legal tech start-ups that are either currently active or have closed or been acquired. He only began keeping count in 2016.” The article goes on to report to report the results of a 2017 survey of 1117 respondents, including findings such as, “(b)y providing structure and visualization to information, technology is enabling attorneys to understand past results and forecast costs, time to resolution and outcomes — and thereby better serve their clients and operate their organizations more successfully.” The article includes a lot of interesting data, showing the success to-date of AI. Here’s a link to the full report by Above the Law. The survey was conducted back in October 2017, and results are reported with some care regarding statistical integrity. All that’s missing to have high confidence in the findings is an idea of the response rate; that is, how many were asked to participate in order to achieve the 1117 responses.

 

  • This post by Ron Friedmann (Legal Transformation or Disruption? A New Rule for Talking About It) is a suggestion for mitigating the extreme hype now plaguing discussions of legal AI and tech in general. It’s a step in the right direction, but is still subject to personal judgement (and hyperbole). I do not have a better idea.

 

  • This post (Baker McKenzie’s Growth Shows Value of One-Stop Legal Shopping from Bloomberg Big Law Business) includes: “(t)he firm also recently adopted artificial intelligence tools in 11 offices in three continents as the first step in a worldwide rollout. This will allow faster, more comprehensive review of merger and acquisition work, and other work involving contracts, the firm said.”

 

  • As I visit law firms, I am asked more and more about the Big 4 accounting firms’ encroachment into the legal space. This threat has been popping up since the days of the Big 8, but has more substance today than ever before. For instance:

Breaking: Big Four firm buys services ‘disruptor’ Riverview. “Global accountancy giant EY today laid down a significant marker in its expansion into legal services with the capture of forward-thinking firm Riverview Law.” … “The deal marks another step in what has long been predicted would be the rise of the ‘Big Four’ accountancy firms to rival – and possibly overtake – the biggest existing law firms. Each of those four, EY, KMPG, PwC and Deloitte, now provide reserved legal services.” Coverage here and here. “EY said the acquisition underlines its position “as a leading disruptor of legal services” and will “help clients to increase efficiency, manage risk, improve service transparency and reduce costs of routine legal activities.”

And the same day, KMPG published, “In the legal sector, this disruption presents vast challenges as firms struggle to move from traditional hierarchies, manual research requirements, time-based billing models, and other traditional ways of operating, into tech-empowered models fit for the future.” “Adapt or fall behind. Now is the perfect time to reimagine every layer of the workplace to future proof the legal profession.”

 

  • Here’s an interesting application of AI from Seyfarth Shaw: Australia: New Transparency: Using Collaboration And Technology To Address Modern Slavery. “Mining data (for example, from mobile phones, media reports and surveillance cameras) which can be analysed using artificial intelligence and machine learning to extract meaningful information and identify risks in the supply chain.”

 

  • From The Atlantic, this interesting application of sentiment analysis. The AI That Reads All a Company’s Emails to Gauge Morale. The very interesting article discusses text analysis generally and is definitely worth reading.

 

  • Canada’s Miller Thomson postedArtificial Intelligence Revolution and the Insurance Industry. “AI may soon be heavily used in all aspects of the insurance industry, including sales, customer service, underwriting, claims assessment and fraud detection and prevention. AI has and will continue to be used in the area of insurance marketing.”

 

Blockchain

  • From ForbesTrust, Security And Efficiency – How Blockchain Really Intersects With Artificial Intelligence. “Blockchain, though powerful on it’s own, becomes enhanced to a whole new level when coupled with AI technology. New features and capabilities become unlocked, enhanced, and more secure through the convergence.” Several instances of this synergy are discussed, but there’s no real insight as to how they will actually work together.

 

  • Get smart: blockchain will liberate lawyers. Sounds good, no? This post from the UK’s Law Society Gazette, focuses on smart contracts and details several concerns and limitations thereof, including use of imprecise terms such as “reasonable.”

 

  • This piece from ComputerWorld (By 2020, 1-in-5 healthcare orgs will adopt blockchain; here’s why) reviews several applications of blockchain in healthcare. It’s a deep dive into the pros and cons, and describes several applications, including smart contracts. “Blockchain lets the healthcare industry exchange data in a standard format, automate complex processes and apply AI against large silos of medical data. It might even allow patients to sell their data for rewards.”