In the case of synthetic intelligence, I’ve heard multiple lawyer say, “I don’t must know the way it works, I simply must know whether it is authorized.” That is sort of a pilot saying, “I don’t must know the way the engines work, I simply must know if we will take off.” You would possibly get airborne, however I’d not ebook a ticket.
AI merchandise don’t exist in a vacuum. They’re the product of numerous technical choices, every with potential authorized penalties. For in-house counsel, understanding the mechanics of AI is not optionally available. It’s the basis for giving recommendation that really works in the actual world.
A New Skillset For A New Period
The previous mannequin, the place engineers construct and attorneys approve, is breaking down. AI techniques usually are not static merchandise. They study, adapt, and make choices in ways in which blur the road between design and deployment. Reviewing them solely on the finish of improvement is just too late to catch most of the most critical dangers.
Immediately’s in-house product counsel wants a twin fluency. You need to have the ability to grasp how an AI mannequin operates whereas mapping these particulars onto quickly evolving authorized frameworks. This mix permits you to enter product discussions not solely as a danger supervisor however as a companion in shaping design selections.
Understanding The Technical Aspect
You don’t want to be an engineer, however it is best to have the ability to observe a dialog about coaching datasets, mannequin structure, and efficiency testing. This implies participating together with your product groups early and asking for explanations which are clear and concise. Understanding whether or not a mannequin is generative or predictive, the way it was educated, and the way will probably be examined for equity and accuracy will inform you much more about potential authorized publicity than a product launch deck ever might.
Seeing The Authorized Dangers Early
We’ve already seen examples of what occurs when authorized and technical groups work in isolation. An AI hiring device that discovered to desire one gender over one other. An artwork generator educated on copyrighted pictures with out permission. These weren’t inevitable outcomes. They had been the results of missed alternatives to ask the precise questions earlier than the product was locked in.
When counsel understands the technical structure, potential issues could be noticed whereas they’re nonetheless cheap and possible to repair. By the point the product is stay, those self same points could be expensive, public, and much harder to resolve.
The Price Of Staying In One Lane
For those who keep solely within the authorized lane, you could miss the refined methods an AI’s design can introduce bias, create explainability gaps, or run afoul of privateness legal guidelines. For those who focus solely on the technical aspect, you would possibly underestimate how a single compliance failure can escalate right into a regulatory investigation or a reputational disaster. Both strategy leaves vital dangers unaddressed and potential worth untapped.
Constructing Your AI Fluency
For in-house counsel, constructing fluency begins with curiosity. Attend engineering demos, sit in on technical critiques, and ask your product groups to stroll you thru how their techniques make choices. Maintain monitor of developments in AI regulation, not solely in your house jurisdiction however in each market the place your product would possibly function. Create methods to translate authorized necessities into technical design selections and vice versa, so each groups are talking the identical language.
This isn’t about changing into a programmer. It’s about understanding sufficient to attach the dots between technical realities and authorized outcomes.
The Payoff
When in-house counsel can communicate each AI and regulation, they transfer from being the ultimate checkpoint earlier than launch to being a trusted companion in innovation. They assist design merchandise which are extra compliant, extra clear, and extra resilient to each market and regulatory stress.
In an AI-driven world, translation between code and case regulation is just not a peripheral talent. It’s a core management functionality that separates the groups who merely launch merchandise from those that launch merchandise constructed to final.
Olga V. Mack is the CEO of TermScout, an AI-powered contract certification platform that accelerates income and eliminates friction by certifying contracts as truthful, balanced, and market-ready. A serial CEO and authorized tech government, she beforehand led an organization by way of a profitable acquisition by LexisNexis. Olga can be a Fellow at CodeX, The Stanford Center for Legal Informatics, and the Generative AI Editor at regulation.MIT. She is a visionary government reshaping how we regulation—how authorized techniques are constructed, skilled, and trusted. Olga teaches at Berkeley Law, lectures broadly, and advises firms of all sizes, in addition to boards and establishments. An award-winning common counsel turned builder, she additionally leads early-stage ventures together with Virtual Gabby (Better Parenting Plan), Product Law Hub, ESI Flow, and Notes to My (Legal) Self, every rethinking the apply and enterprise of regulation by way of expertise, knowledge, and human-centered design. She has authored The Rise of Product Lawyers, Legal Operations in the Age of AI and Data, Blockchain Value, and Get on Board, with Visible IQ for Attorneys (ABA) forthcoming. Olga is a 6x TEDx speaker and has been acknowledged as a Silicon Valley Girl of Affect and an ABA Girl in Authorized Tech. Her work reimagines folks’s relationship with regulation—making it extra accessible, inclusive, data-driven, and aligned with how the world really works. She can be the host of the Notes to My (Authorized) Self podcast (streaming on Spotify, Apple Podcasts, and YouTube), and her insights frequently seem in Forbes, Bloomberg Regulation, Newsweek, VentureBeat, ACC Docket, and Above the Regulation. She earned her B.A. and J.D. from UC Berkeley. Comply with her on LinkedIn and X @olgavmack.