{"id":153470,"date":"2026-06-01T13:38:55","date_gmt":"2026-06-01T21:38:55","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/06\/01\/introducing-the-legal-tech-to-english-dictionary-version-2-0\/"},"modified":"2026-06-01T13:38:55","modified_gmt":"2026-06-01T21:38:55","slug":"introducing-the-legal-tech-to-english-dictionary-version-2-0","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/06\/01\/introducing-the-legal-tech-to-english-dictionary-version-2-0\/","title":{"rendered":"Introducing The Legal Tech-To-English Dictionary \u2014Version 2.0"},"content":{"rendered":"
\"\"
<\/figcaption><\/figure>\n

Auth. note:<\/span> <\/strong>Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0<\/em><\/p>\n

Welcome to the sequel to the Legal Tech-to-English Dictionary <\/em>(2022)<\/a>. This edition updates a vestige of the pre-AI world to share all of the AI and practice management terminology you need to be funner at parties.\u00a0<\/p>\n

Now, before you suggest that the sequel is never better than the original \u2014 hello, \u201cT2: Judgment Day\u201d \u2014 this iteration of the Legal Tech-to-English Dictionary <\/em>promises to be at least 7.2 times better. (Don\u2019t blame me, y\u2019all \u2014 that\u2019s just Moore\u2019s Law<\/a> in operation!)\u00a0\u00a0<\/p>\n

It\u2019s not just about being a better practicing lawyer, it\u2019s also about being a better practicing human. AI is all around us, and it makes no sense to avoid it, because your competitors \u2014 in the broadest sense of the term \u2014 are definitely<\/em> leveraging it.\u00a0\u00a0<\/p>\n

In this installment, we\u2019ll be starting with the essentials. Stay tuned for future posts covering the past, present, and future of AI in legal. <\/p>\n

So grab your 3D-printed knife and fork, and dive into a veritable cornucopia of artificial intelligence information. <\/p>\n

It\u2019s everything you wanted to know about AI, but were afraid to ask!<\/p>\n

(We will also be publishing a full eBook this summer, in partnership with our friends at CosmoLex. Use the form below to pre-register.) <\/em><\/p>\n

Table Stakes \u2013 Basic Terminology for Using AI Tools<\/strong><\/p>\n

Smart folks understand that it makes sense to read the instructions before attempting the build. You know: Measure nine times, cut one, and all that jazz.\u00a0\u00a0<\/em><\/p>\n

Plus, in most jurisdictions, technology competence is now an ethics requirement for lawyers. To effectively use AI in the modern environment, there is some terminology you\u2019re going to need to know.\u00a0<\/em><\/p>\n

prompt <\/strong>v. <\/em>1. <\/strong>to engage with an AI platform, via text or voice, to request an output, which request can be supplemented by additional, uploaded information.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

query, contextualize, initiate, trigger<\/p>\n

Related Words<\/em><\/strong><\/p>\n

open-ended prompting, zero-shot prompting, few-shot prompting, persona-based prompting, chain-of-thought prompting, system prompting, heat check<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Gary: OK, my prompt is complete.<\/p>\n

Gary: I\u2019ve spent a full seven hours working on it, but it was totally<\/em> worth it.<\/p>\n

Gary: I\u2019ve assigned ChatGPT a role, provided context, specifically outlined the task, included constraints on that task, even defined what I want as an output.<\/p>\n

Gary: I\u2019M ALL POWERFUL, GINA. ALL POWERFUL! ME AND MY AI! WE WILL RULE THE WORLD TOGETHER!\u00a0<\/p>\n

Gina: All right, take it easy, Gary.\u00a0\u00a0<\/p>\n

Gary: MWHAHAHAHAHAHAHAH!!!!<\/p>\n

iterative prompting <\/strong>n. <\/em>1. <\/strong>engaging with an AI chatbot past an initial prompt in order to revise an eventual final output.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

recapitulating, reprising, revising, revisiting, remaking, remodeling, editing<\/p>\n


<\/strong>Related Words<\/em><\/strong><\/p>\n

prompt chaining, contextualization, non-linear, adaptive, confidence scoring<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Gina: Why are you still<\/em> interacting with that AI?<\/p>\n

Gina: You need to be zero<\/em>-shot prompting, my guy!<\/p>\n

Gary: I tried<\/em>.<\/p>\n

Gary: I tried so hard<\/em>.<\/p>\n

Gary: [weeping]<\/p>\n

hallucination <\/strong>n. <\/em>1.<\/strong> false or misleading information, presented by AI as if it were true.\u00a0<\/p>\n

Etymology<\/em><\/strong><\/p>\n

Taken from the traditional notion of a hallucination (perceiving something that is not actually there), the idea, as applied to technology, originally had a positive connotation. Hallucination first arose as a term related to AI, when computer engineers used it as a way to describe how programs could \u201cimagine\u201d segments of low-resolution images, by filling them in, from whole cloth. The negative usage that now predominates was coined by OpenAI cofounder, Andrej Karpathy, in a blog post in 2015.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

shenanigans, whopper, fibs, spun yarn, malarkey load, fed line, cap<\/p>\n

Cf. The philosophical question is whether an AI is actually \u201clying\u201d when it hallucinates.\u00a0Well, not in the traditional sense. AI does not lie with intent, like a human would \u2014 it simply makes an incorrect guess, based on pattern recognition. And, that\u2019s the truth.<\/em><\/p>\n

human in the loop <\/strong>n. <\/em>1. <\/strong>a human being entrenched in the chain of command, who makes the ultimate decision whether to advance an AI process and\/or verify a final output.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The term is almost as old as AI itself. It was coined by Norbert Wiener as a method for adding human failsafes into government intelligence programs. Post-Cold War, the term was adopted for machine learning.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

degenerate, cockroach, brute (actually, that\u2019s probably how the AI would describe it \u2014 that, or I\u2019m simply hallucinating).<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Barry: You know how I know Carl is a complete dork?<\/p>\n

Sandra: How?<\/p>\n

Barry: He\u2019s wearing a T-shirt that says \u2018Human in the Loop\u2019?<\/p>\n

Sandra: Oh, my God. That\u2019s so <\/em>embarrassing.<\/p>\n

Barry: I know.<\/p>\n

Sandra: Probably why his wife left him.<\/p>\n

Barry: For sure.<\/p>\n

synthetic media <\/strong>n. <\/em>1. <\/strong>text, images, audio, and\/or video generated \u2014 in whole, or in part \u2014 by artificial intelligence\u00a0<\/p>\n

Related Words<\/em><\/strong><\/p>\n

deepfake, general adversarial networks, voice cloning, natural language generation, autoencoding, anti-spoofers, artifacts, cheapfakes, uncanny valley\u00a0<\/a><\/p>\n

Antonyms<\/em><\/strong><\/p>\n

Like, anything real. Just go outside.<\/p>\n

\n

CosmoLex is proud to sponsor this edition of the Legal Tech-to-English Dictionary. As an end-to-end practice management platform built specifically for small to midsize law firms, CosmoLex integrates AI directly into the workflows attorneys rely on every day \u2014 summarizing documents, filtering matters and invoices in plain language, automating intake, and streamlining firm workflows. No separate tool to learn, no AI layer dropped onto a legacy system. Practical functionality built into the platform where the work already happens, with the compliance guardrails law firms actually need.<\/em><\/p>\n

Pre-Register for the Legal Tech-to-English Dictionary \u2014 Version 2.0<\/strong><\/p>\n

Registrants will receive the eBook via email this summer. <\/em><\/p>\n

<\/div>\n
\n

Jared Correia<\/a>, a consultant and legal technology expert, is the host of \u201cAdventures in Legal Tech,\u201d the featured podcast of Above the Law\u2019s Legal Tech Center<\/em><\/strong>.<\/p>\n

The post Introducing The Legal Tech-To-English Dictionary \u2014Version 2.0<\/a> appeared first on Above the Law<\/a>.<\/p>\n

\"\"
<\/figcaption><\/figure>\n

Auth. note:<\/span> <\/strong>Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0<\/em><\/p>\n

Welcome to the sequel to the Legal Tech-to-English Dictionary <\/em>(2022)<\/a>. This edition updates a vestige of the pre-AI world to share all of the AI and practice management terminology you need to be funner at parties.\u00a0<\/p>\n

Now, before you suggest that the sequel is never better than the original \u2014 hello, \u201cT2: Judgment Day\u201d \u2014 this iteration of the Legal Tech-to-English Dictionary <\/em>promises to be at least 7.2 times better. (Don\u2019t blame me, y\u2019all \u2014 that\u2019s just Moore\u2019s Law<\/a> in operation!)\u00a0\u00a0<\/p>\n

It\u2019s not just about being a better practicing lawyer, it\u2019s also about being a better practicing human. AI is all around us, and it makes no sense to avoid it, because your competitors \u2014 in the broadest sense of the term \u2014 are definitely<\/em> leveraging it.\u00a0\u00a0<\/p>\n

In this installment, we\u2019ll be starting with the essentials. Stay tuned for future posts covering the past, present, and future of AI in legal. <\/p>\n

So grab your 3D-printed knife and fork, and dive into a veritable cornucopia of artificial intelligence information. <\/p>\n

It\u2019s everything you wanted to know about AI, but were afraid to ask!<\/p>\n

(We will also be publishing a full eBook this summer, in partnership with our friends at CosmoLex. Use the form below to pre-register.) <\/em><\/p>\n

Table Stakes \u2013 Basic Terminology for Using AI Tools<\/strong><\/p>\n

Smart folks understand that it makes sense to read the instructions before attempting the build. You know: Measure nine times, cut one, and all that jazz.\u00a0\u00a0<\/em><\/p>\n

Plus, in most jurisdictions, technology competence is now an ethics requirement for lawyers. To effectively use AI in the modern environment, there is some terminology you\u2019re going to need to know.\u00a0<\/em><\/p>\n

prompt <\/strong>v. <\/em>1. <\/strong>to engage with an AI platform, via text or voice, to request an output, which request can be supplemented by additional, uploaded information.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

query, contextualize, initiate, trigger<\/p>\n

Related Words<\/em><\/strong><\/p>\n

open-ended prompting, zero-shot prompting, few-shot prompting, persona-based prompting, chain-of-thought prompting, system prompting, heat check<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Gary: OK, my prompt is complete.<\/p>\n

Gary: I\u2019ve spent a full seven hours working on it, but it was totally<\/em> worth it.<\/p>\n

Gary: I\u2019ve assigned ChatGPT a role, provided context, specifically outlined the task, included constraints on that task, even defined what I want as an output.<\/p>\n

Gary: I\u2019M ALL POWERFUL, GINA. ALL POWERFUL! ME AND MY AI! WE WILL RULE THE WORLD TOGETHER!\u00a0<\/p>\n

Gina: All right, take it easy, Gary.\u00a0\u00a0<\/p>\n

Gary: MWHAHAHAHAHAHAHAH!!!!<\/p>\n

iterative prompting <\/strong>n. <\/em>1. <\/strong>engaging with an AI chatbot past an initial prompt in order to revise an eventual final output.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

recapitulating, reprising, revising, revisiting, remaking, remodeling, editing<\/p>\n


<\/strong>Related Words<\/em><\/strong><\/p>\n

prompt chaining, contextualization, non-linear, adaptive, confidence scoring<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Gina: Why are you still<\/em> interacting with that AI?<\/p>\n

Gina: You need to be zero<\/em>-shot prompting, my guy!<\/p>\n

Gary: I tried<\/em>.<\/p>\n

Gary: I tried so hard<\/em>.<\/p>\n

Gary: [weeping]<\/p>\n

hallucination <\/strong>n. <\/em>1.<\/strong> false or misleading information, presented by AI as if it were true.\u00a0<\/p>\n

Etymology<\/em><\/strong><\/p>\n

Taken from the traditional notion of a hallucination (perceiving something that is not actually there), the idea, as applied to technology, originally had a positive connotation. Hallucination first arose as a term related to AI, when computer engineers used it as a way to describe how programs could \u201cimagine\u201d segments of low-resolution images, by filling them in, from whole cloth. The negative usage that now predominates was coined by OpenAI cofounder, Andrej Karpathy, in a blog post in 2015.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

shenanigans, whopper, fibs, spun yarn, malarkey load, fed line, cap<\/p>\n

Cf. The philosophical question is whether an AI is actually \u201clying\u201d when it hallucinates.\u00a0Well, not in the traditional sense. AI does not lie with intent, like a human would \u2014 it simply makes an incorrect guess, based on pattern recognition. And, that\u2019s the truth.<\/em><\/p>\n

human in the loop <\/strong>n. <\/em>1. <\/strong>a human being entrenched in the chain of command, who makes the ultimate decision whether to advance an AI process and\/or verify a final output.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The term is almost as old as AI itself. It was coined by Norbert Wiener as a method for adding human failsafes into government intelligence programs. Post-Cold War, the term was adopted for machine learning.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

degenerate, cockroach, brute (actually, that\u2019s probably how the AI would describe it \u2014 that, or I\u2019m simply hallucinating).<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Barry: You know how I know Carl is a complete dork?<\/p>\n

Sandra: How?<\/p>\n

Barry: He\u2019s wearing a T-shirt that says \u2018Human in the Loop\u2019?<\/p>\n

Sandra: Oh, my God. That\u2019s so <\/em>embarrassing.<\/p>\n

Barry: I know.<\/p>\n

Sandra: Probably why his wife left him.<\/p>\n

Barry: For sure.<\/p>\n

synthetic media <\/strong>n. <\/em>1. <\/strong>text, images, audio, and\/or video generated \u2014 in whole, or in part \u2014 by artificial intelligence\u00a0<\/p>\n

Related Words<\/em><\/strong><\/p>\n

deepfake, general adversarial networks, voice cloning, natural language generation, autoencoding, anti-spoofers, artifacts, cheapfakes, uncanny valley\u00a0<\/a><\/p>\n

Antonyms<\/em><\/strong><\/p>\n

Like, anything real. Just go outside.<\/p>\n

\n

CosmoLex is proud to sponsor this edition of the Legal Tech-to-English Dictionary. As an end-to-end practice management platform built specifically for small to midsize law firms, CosmoLex integrates AI directly into the workflows attorneys rely on every day \u2014 summarizing documents, filtering matters and invoices in plain language, automating intake, and streamlining firm workflows. No separate tool to learn, no AI layer dropped onto a legacy system. Practical functionality built into the platform where the work already happens, with the compliance guardrails law firms actually need.<\/em><\/p>\n

Pre-Register for the Legal Tech-to-English Dictionary \u2014 Version 2.0<\/strong><\/p>\n

Registrants will receive the eBook via email this summer. <\/em><\/p>\n

<\/div>\n
\n

Jared Correia<\/a>, a consultant and legal technology expert, is the host of \u201cAdventures in Legal Tech,\u201d the featured podcast of Above the Law\u2019s Legal Tech Center<\/em><\/strong>.<\/p>\n

The post Introducing The Legal Tech-To-English Dictionary \u2014Version 2.0<\/a> appeared first on Above the Law<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Auth. note: Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0 Welcome to the sequel to the Legal Tech-to-English Dictionary (2022). This edition updates a vestige of the pre-AI world to share all of the […]<\/p>\n","protected":false},"author":3,"featured_media":153471,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-153470","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-above_the_law"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/xira.com\/p\/wp-content\/uploads\/2026\/06\/ornaw-book-3986102-1024x683-sQEob1.jpg?fit=1024%2C683&ssl=1","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/153470","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/comments?post=153470"}],"version-history":[{"count":0,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/153470\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media\/153471"}],"wp:attachment":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media?parent=153470"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/categories?post=153470"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/tags?post=153470"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}