{"id":154920,"date":"2026-06-16T15:27:25","date_gmt":"2026-06-16T23:27:25","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/06\/16\/the-legal-tech-to-english-dictionary-2-0-the-ghosts-of-artificial-intelligence-past\/"},"modified":"2026-06-16T15:27:25","modified_gmt":"2026-06-16T23:27:25","slug":"the-legal-tech-to-english-dictionary-2-0-the-ghosts-of-artificial-intelligence-past","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/06\/16\/the-legal-tech-to-english-dictionary-2-0-the-ghosts-of-artificial-intelligence-past\/","title":{"rendered":"The Legal Tech-To-English Dictionary (2.0): The Ghosts Of Artificial Intelligence Past"},"content":{"rendered":"
\"\"
<\/figcaption><\/figure>\n

Auth. note<\/span><\/em>: <\/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 (2022)<\/em><\/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

Here, we\u2019re pleased to share Chapter 3. Check out the first installment here<\/a>, and feel free to pre-register for the full eBook using the form below.<\/p>\n

Historical Concepts That Are Still Valid Today<\/strong><\/p>\n

While many might believe that AI was not really introduced until ChatGPT hit the public zeitgeist in 2023, artificial intelligence (broadly speaking) has its own history, almost a century old.\u00a0\u00a0<\/p>\n

In fact, the birth of artificial intelligence occurred in the mid-1940s. That\u2019s right, AI \u2014 perhaps ironically \u2014 is part of the Silent Generation, when the concept of \u201cneural networks\u201d was first formulated by scientists.\u00a0 <\/p>\n

In this section, we\u2019ll address some foundational AI terminology that it still pays to know.<\/p>\n

machine learning <\/strong>n. <\/em>1. <\/strong>an application of artificial intelligence that allows for the launch and maintenance of computer systems that use algorithms to analyze data and make predictions therefrom.<\/p>\n

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

artificial intelligence, data training, models, outputs, unsupervised learning, loss function, overfitting<\/p>\n

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

human intelligence, harebrained scheming, zany follies<\/p>\n

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

When my Tesla drove off the road in a roundabout and exploded into a fireball, that\u2019s an example of machine learning still learning.<\/p>\n

neural networks <\/strong>n. <\/em>1. <\/strong>in artificial intelligence, a data processing and prediction engine, where nodes are substituted for neurons in the human brain, as a way to replicate natural thinking. 2.<\/strong> the model by which, you know, actual human brains process data inputs.<\/p>\n

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

Neural networks in computing were first proposed in 1944, by Warren McCollough and Walter Pitts, then University of Chicago researchers. In 1957, Cornell psychologist Frank Rosenblatt created the first trainable neural network, Perceptron \u2014 which, I believe, was also a microscope that could change into a robot in the \u2018Transformers\u2019 cartoon series.<\/p>\n

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

neural net, semantic network, nervous system, intelligent retrieval, Krang from the \u2018Teenage Mutant Ninja Turtles,\u2019 M.O.D.O.K from the Marvel Universe, Mother Brain from the \u2018Metroid\u2019 video game<\/p>\n

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

Tech Bro 1: My neural network is more layered than Carole in accounting\u2019s bean dip.<\/p>\n

Tech Bro 2: Yooooooooo!!!!<\/p>\n

natural language processing <\/strong>n. <\/em>1. <\/strong>a cluster of technologies that allows machines to understand, manipulate and generate human language, and, through commonly used GPTs, to tell you you\u2019re doing an amazing job at everything. (Go you!)<\/p>\n

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

computational linguistics, speech processing, natural language interaction, human language technology<\/p>\n

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

John Grinder:<\/a> Who\u2019s down with NLP?<\/p>\n

Richard Bandler<\/a>: Yeah, you know me!<\/p>\n

Treach<\/a>: Wait, what?<\/p>\n

Turing Test <\/strong>n. <\/em>1. <\/strong>a process to determine whether a computer is displaying human-like intelligence by producing output that would be indistinguishable from what a human would generate.<\/p>\n

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

This \u201cimitation game,\u201d developed by British mathematician Alan Turing in 1949, involves a human judge, who can submit written questions, attempting to correctly identify, as between two texts, which one was drafted by a human and which one was drafted by a computer. If the human arbiter cannot reliably select between the two, the machine passes the test and has displayed human-like intelligence.<\/p>\n

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

CAPTCHA (Reverse Turing Test), The Marcus Test<\/a>, The Lovelace Text<\/a>, The Ship of Theseus<\/a>, The Prisoner\u2019s Dilemma<\/a>, The Trolley Problem<\/a>, The Ring of Gyges<\/a>.\u00a0<\/p>\n

ELIZA Program <\/strong>n. <\/em>1.<\/strong> the first chatbot<\/p>\n

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

ELIZA was developed by Joseph Weizenbaum, a computer scientist at the Massachusetts Institute of Technology, from 1964-67. Users could converse with ELIZA by typing on a keyboard, and the program would respond. While the program did not exhibit any artificial intelligence per se<\/em>, users nevertheless experienced emotional responses to the \u201cchatterbot,\u201d even attributing human feelings to it. That interaction process became known as \u201cthe ELIZA Effect.\u201d Users now engage with GPTs in a similar fashion.<\/p>\n

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

Eliza Doolittle<\/a>, PARRY, A.L.I.C.E.<\/p>\n

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

Human:\u00a0Well, my boyfriend made me come here.
ELIZA:\u00a0Your boyfriend made you come here?
Human:\u00a0He says I\u2019m depressed much of the time.
ELIZA:\u00a0I am sorry to hear you are depressed.
Human:\u00a0It\u2019s true. I\u2019m unhappy.
ELIZA:\u00a0Do you think coming here will help you not to be unhappy?<\/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 The Legal Tech-To-English Dictionary (2.0): The Ghosts Of Artificial Intelligence Past<\/a> appeared first on Above the Law<\/a>.<\/p>\n

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

Auth. note<\/em>: <\/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 (2022)<\/em><\/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

Here, we\u2019re pleased to share Chapter 3. Check out the first installment here<\/a>, and feel free to pre-register for the full eBook using the form below.<\/p>\n

Historical Concepts That Are Still Valid Today<\/strong><\/p>\n

While many might believe that AI was not really introduced until ChatGPT hit the public zeitgeist in 2023, artificial intelligence (broadly speaking) has its own history, almost a century old.\u00a0\u00a0<\/p>\n

In fact, the birth of artificial intelligence occurred in the mid-1940s. That\u2019s right, AI \u2014 perhaps ironically \u2014 is part of the Silent Generation, when the concept of \u201cneural networks\u201d was first formulated by scientists.\u00a0 <\/p>\n

In this section, we\u2019ll address some foundational AI terminology that it still pays to know.<\/p>\n

machine learning <\/strong>n. <\/em>1. <\/strong>an application of artificial intelligence that allows for the launch and maintenance of computer systems that use algorithms to analyze data and make predictions therefrom.<\/p>\n

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

artificial intelligence, data training, models, outputs, unsupervised learning, loss function, overfitting<\/p>\n

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

human intelligence, harebrained scheming, zany follies<\/p>\n

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

When my Tesla drove off the road in a roundabout and exploded into a fireball, that\u2019s an example of machine learning still learning.<\/p>\n

neural networks <\/strong>n. <\/em>1. <\/strong>in artificial intelligence, a data processing and prediction engine, where nodes are substituted for neurons in the human brain, as a way to replicate natural thinking. 2.<\/strong> the model by which, you know, actual human brains process data inputs.<\/p>\n

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

Neural networks in computing were first proposed in 1944, by Warren McCollough and Walter Pitts, then University of Chicago researchers. In 1957, Cornell psychologist Frank Rosenblatt created the first trainable neural network, Perceptron \u2014 which, I believe, was also a microscope that could change into a robot in the \u2018Transformers\u2019 cartoon series.<\/p>\n

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

neural net, semantic network, nervous system, intelligent retrieval, Krang from the \u2018Teenage Mutant Ninja Turtles,\u2019 M.O.D.O.K from the Marvel Universe, Mother Brain from the \u2018Metroid\u2019 video game<\/p>\n

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

Tech Bro 1: My neural network is more layered than Carole in accounting\u2019s bean dip.<\/p>\n

Tech Bro 2: Yooooooooo!!!!<\/p>\n

natural language processing <\/strong>n. <\/em>1. <\/strong>a cluster of technologies that allows machines to understand, manipulate and generate human language, and, through commonly used GPTs, to tell you you\u2019re doing an amazing job at everything. (Go you!)<\/p>\n

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

computational linguistics, speech processing, natural language interaction, human language technology<\/p>\n

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

John Grinder:<\/a> Who\u2019s down with NLP?<\/p>\n

Richard Bandler<\/a>: Yeah, you know me!<\/p>\n

Treach<\/a>: Wait, what?<\/p>\n

Turing Test <\/strong>n. <\/em>1. <\/strong>a process to determine whether a computer is displaying human-like intelligence by producing output that would be indistinguishable from what a human would generate.<\/p>\n

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

This \u201cimitation game,\u201d developed by British mathematician Alan Turing in 1949, involves a human judge, who can submit written questions, attempting to correctly identify, as between two texts, which one was drafted by a human and which one was drafted by a computer. If the human arbiter cannot reliably select between the two, the machine passes the test and has displayed human-like intelligence.<\/p>\n

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

CAPTCHA (Reverse Turing Test), The Marcus Test<\/a>, The Lovelace Text<\/a>, The Ship of Theseus<\/a>, The Prisoner\u2019s Dilemma<\/a>, The Trolley Problem<\/a>, The Ring of Gyges<\/a>.\u00a0<\/p>\n

ELIZA Program <\/strong>n. <\/em>1.<\/strong> the first chatbot<\/p>\n

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

ELIZA was developed by Joseph Weizenbaum, a computer scientist at the Massachusetts Institute of Technology, from 1964-67. Users could converse with ELIZA by typing on a keyboard, and the program would respond. While the program did not exhibit any artificial intelligence per se<\/em>, users nevertheless experienced emotional responses to the \u201cchatterbot,\u201d even attributing human feelings to it. That interaction process became known as \u201cthe ELIZA Effect.\u201d Users now engage with GPTs in a similar fashion.<\/p>\n

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

Eliza Doolittle<\/a>, PARRY, A.L.I.C.E.<\/p>\n

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

Human:\u00a0Well, my boyfriend made me come here.
ELIZA:\u00a0Your boyfriend made you come here?
Human:\u00a0He says I\u2019m depressed much of the time.
ELIZA:\u00a0I am sorry to hear you are depressed.
Human:\u00a0It\u2019s true. I\u2019m unhappy.
ELIZA:\u00a0Do you think coming here will help you not to be unhappy?<\/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

\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","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":154921,"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-154920","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-3986102-1024x683-5Qgdty.jpg?fit=1024%2C683&ssl=1","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/154920","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=154920"}],"version-history":[{"count":0,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/154920\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media\/154921"}],"wp:attachment":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media?parent=154920"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/categories?post=154920"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/tags?post=154920"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}