Emerging legal technology dynamics brings along issues of managing risk, technology prioritization, and in-line evolutionary needs associated with these new technologies, all of which can greatly impact the pace and delivery of legal services today.
This theme dominated the recent 2021 Emerging Legal Technology Forum, presented by Thomson Reuters Institute last week in Boston.
Many panels explored common themes and imperatives essential to staying competitive in a dynamic legal technology industry, such as the use of AI in functions like contract development, automating workflows, and blockchain.
Sessions also discussed legal tech service delivery, how project finances and priorities are evaluated, remote working, and client-facing technologies, with risk management and security hovering as ever-present topics as well.
Set in the historic Boston Park Plaza Hotel, the forum was very much a boutique event, a setting favorable to striking up conversations (and hopefully longer-term relationships as well) with an impressive collection of legal technology thought leaders.
With no supplier parties or staffed vendor booths, the intimate nature of the forum lent itself to deep discussion of forward-thinking ideas, both in panel and networking interchanges. It was not unlike the environment within a boutique law firm or smaller legal tech shop, where the high quality of professionals generally leads to fast-moving, elite-level exchanges or ideas.
This panel explored the topic of artificial intelligence, starting with a very interesting example of Tesla’s driver safety ratings and how currently, there is no formalized process for appealing any safety rating decisions made by AI. Panelist Stas Gayshan, General Counsel of CIC Health, led a discussion around who has the right to know about the decisions a machine-learning system makes and the need to respect the protection of intellectual property, which sparked an interesting exchange of governance issues and concerns.
Of particular interest was a presentation identifying five key points of theory relating to AI governance offered by Boston-based Thomson Reuters Labs data scientist Sally Gao. These points of consideration include:
- human-user interaction;
- transparency and explainability;
- algorithmic fairness;
- robustness and reliability; and
- data privacy.
The main premise here is that on-going broad-based improvements in these areas will help to continue the quality of AI applications across society. Overall, this panel conveyed that AI is a field very much still maturing, with ethical AI, transparency, fairness, reliability, resistance to threats, data privacy, and differential privacy all topics that still need addressing until we achieve favorable long-term frameworks.
Blockchain’s broad horizons
Highlighted by subject matter expert Dazza Greenwood, founder & CEO of CIVICS.com Consultancy Services, this panel covered governance and regulation for blockchain and, interestingly, how blockchain itself can help in these areas. Greenwood also detailed the need for a legal definition of blockchain, highlighting his efforts to crowdsource the same within his MIT Media Labssite.
Also on the panel, Co-Founder & Chief Technology Officer of Chrysalis Digital Asset Exchange, Doug McCalmont, used a sports wager as an example of a very simplistic (in the positive sense) example of a smart contract, demonstrating how a sports wager could rely on an oracle — a fact-determining authority, such as ESPN.com in our sports wager analogy — to finalize contract results, or in this case, game winners. McCalmont also noted that there are already-available templates and technologies that can provide common implementation tools for smart contracts.
