AI w prawie

AI and law (legal AI) · id legalai · aliases: legal AI, AI and law, LegalAI, legal tech AI, sztuczna inteligencja w prawie, AI dla prawników

Zastosowania AI w pracy z prawem: wyszukiwanie informacji prawnej, analiza umów, przegląd dokumentów w sporach, rozumowanie i predykcja oraz formalizacja przepisów.

AI applied to legal work: legal information retrieval, contract analysis, document review in litigation, reasoning and prediction, and formalising legislation.

In one sentence

Programy, które pomagają szukać przepisów i orzeczeń, czytać umowy, przeglądać stosy dokumentów w sprawie i zapisywać reguły prawa tak, by liczył je komputer.

Software that helps find laws and rulings, read contracts, sift piles of case documents and write legal rules down so a computer can apply them.

Problem it solves

Prawo to góry tekstu: przepisy, wyroki, umowy i akta. Prawnicy toną w czytaniu, a zwykły człowiek nie wie, gdzie zacząć.

Law is mountains of text: statutes, rulings, contracts and case files. Lawyers drown in reading, and ordinary people do not know where to start.

What it does

Jak bystry aplikant, który w minutę przeczyta całe archiwum i podsunie fragmenty do sprawdzenia, ale podpis i odpowiedzialność zostają przy prawniku.

Like a sharp trainee who reads the whole archive in a minute and flags passages to check; the lawyer keeps the signature and responsibility.

Everyday example

Przed podpisaniem umowy najmu wrzucasz ją do asystenta i pytasz, kiedy możesz ją wypowiedzieć; dostajesz odpowiedź z zaznaczonym paragrafem.

Before signing a lease you give it to an assistant and ask when you can terminate it; the answer comes back with the clause highlighted.

This concerns you if you…

podpisujesz umowy i nie masz czasu ich czytać
pracujesz w kancelarii, dziale prawnym lub urzędzie
szukasz porady prawnej w czatbocie
sign contracts and have no time to read them
work in a law firm, legal department or public office
look for legal advice from a chatbot

Subtopics

Analiza umów (Contract analysis and review): Automated retrieval and classification of contract provisions, with identification of clauses that require human risk assessment.
- Przegląd umowy według zasad firmy (playbook) (Playbook-based contract review): Checking a contract against a company's set of standard positions and templates, locating deviations and missing provisions.
- Redagowanie i poprawianie umów z AI (AI contract drafting and redlining): LLM generation of clauses and proposed edits to contract drafts, often with retrieval of precedents and scoring of edit acceptability.
- Sprawdzanie twierdzeń o umowie (Contract natural language inference): Document-level inference: given a contract and a hypothesis, the model labels entailment, contradiction or not mentioned and identifies evidence spans.
- Wyszukiwanie klauzul w umowach (Contract clause extraction): Locating contract passages matching defined provision categories, usually framed as question-answering-style span extraction.
Benchmarki modeli prawniczych (Legal AI benchmarks): Task collections for evaluating models on legal text, covering language understanding, classification, and multiple forms of legal reasoning.
E-discovery i przegląd dokumentów (E-discovery and technology-assisted review): Identifying, reviewing and producing electronic evidence in proceedings; technology-assisted review is relevance classification trained on reviewers' judgements.
- Ciągłe aktywne uczenie w przeglądzie dokumentów (Continuous active learning for document review (CAL)): A TAR protocol in which the classifier is retrained continuously on reviewer judgements and always offers the top-ranked unreviewed documents.
- Przegląd dokumentów przez modele językowe (LLM-based document review (generative TAR)): Relevance assessment of documents in e-discovery by an LLM prompted with the request or fine-tuned on a seed set, with a generated rationale.
- Wykrywanie dokumentów objętych tajemnicą adwokacką (Privilege review in e-discovery): Classifying documents for privilege alongside responsiveness, with cost-based selection of which documents a human reviews.
Formalizacja prawa (Computational law and formal legal models): The symbolic strand of AI and law: representing norms in logic and programming languages, and computational models of legal reasoning and argument.
- Automatyczne sprawdzanie zgodności z przepisami (Automated regulatory compliance checking): Verifying business processes and documents against legal norms: classically with formal deontic rules, more recently also with LLMs and retrieval.
- Modele argumentacji prawniczej (Computational models of legal argument): Formal and computational models for generating, evaluating and using legal arguments, especially precedent-based reasoning with factors and dimensions.
- Prawo jako kod (Rules as code): Creating a machine-executable version of legislation alongside the legal text, in dedicated languages or frameworks, ideally at the drafting stage.
- Ustrukturyzowane dokumenty prawne (Structured legal documents): Standards for structured encoding and identification of legal documents in XML and RDF, enabling precise linking, versioning and consolidation.
Przetwarzanie tekstów prawnych (Legal text processing (legal NLP)): NLP tasks adapted to legal text: entity recognition, judgment structuring, summarisation, anonymisation and language models trained on law.
- Anonimizacja orzeczeń sądowych (Anonymisation of court decisions): Automatically detecting personal identifiers in court decisions and masking them before publication, and assessing re-identification risk.
- Modele językowe uczone na tekstach prawnych (Domain-adapted legal language models): Language models further pretrained or trained from scratch on legal corpora, sometimes with a custom vocabulary and instruction tuning on legal tasks.
- Podział wyroku na części (role retoryczne) (Rhetorical role labelling of court judgments): Classifying each sentence of a judgment into a functional role such as facts, party arguments, analysis, ratio decidendi and decision.
- Rozpoznawanie nazw w tekstach prawnych (Legal named entity recognition): Tagging entities in legal texts with fine-grained domain classes such as court, judge, party, provision, precedent and case number.
- Streszczanie wyroków i aktów prawnych (Legal document summarisation): Extractive and abstractive summarisation of long legal documents: judgments, case files and legislation, including multilingual settings.
Rozumowanie prawne i przewidywanie (Legal reasoning and outcome prediction): Modelling and evaluating models' legal reasoning (issue spotting, rule application, conclusion) and predicting court outcomes from text.
- Przewidywanie wyroków (Legal judgment prediction): Classifying the outcome (e.g. violation of an article, which party wins) from case text; outcome identification is distinguished from genuine forecasting.
- Stosowanie przepisu do faktów (rozumowanie z ustaw) (Statutory reasoning): Applying a given statute text to a described set of facts: deciding whether a provision applies or computing the legal outcome.
Wyszukiwanie informacji prawnej (Legal information retrieval and research): Retrieving and ranking rulings and statutes for a query or case description, increasingly combined with answer generation with citations (legal RAG).
- Agenci badań prawnych (Agentic legal research): Multi-step agent systems that plan queries, use search tools over legal databases and produce cited answers, often with a separate verifier.
- Odpowiedzi na pytania z przepisów (Statute retrieval and legal entailment): Retrieving the statute articles relevant to a question and yes/no inference on whether the question follows from those articles.
- Wyszukiwanie podobnych orzeczeń (Legal case retrieval (prior case retrieval)): The task of finding, in a large database of rulings, cases relevant to a query that is a case description or a whole document.
- Zmyślone orzeczenia i weryfikacja cytowań (Legal hallucinations and citation verification): Studying and detecting invented or misquoted legal authorities in model outputs, and automated verification of citations in filings.

Sources

How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence · Haoxi Zhong, Chaojun Xiao, Cunchao Tu, Tianyang Zhang, Zhiyuan Liu, Maosong Sun
Promises and pitfalls of artificial intelligence for legal applications · Sayash Kapoor, Peter Henderson, Arvind Narayanan