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A practical AI dispute risk matrix for assessing confidentiality, evidence, bias, vendor, governance, consumer, employment, and urgency risks before conflict escalates. Many AI disputes look similar on the surface and then break in completely different ways once confidentiality, evidence, consumer sensitivity, or governance failure enters the picture. This risk matrix…

A practical guide to AI consumer disputes, including deceptive AI claims, chatbot failures, privacy issues, automated decisions, refunds, evidence, and arbitration risk. AI consumer disputes are rarely just about a model giving a wrong answer. They usually involve something more operational: a misleading product claim, a broken chatbot support loop,…

A practical guide to training data disputes, including ownership claims, permission, provenance, licensing, privacy, contractual restrictions, and proof problems. Training data disputes often sound like debates about AI policy, but in practice they are usually disputes about permission, provenance, contracts, privacy, proof, and who can actually show what happened. This…

A practical explainer on Ciarb’s Guideline on the Use of AI in Arbitration, including party use, arbitrator use, disclosure, tribunal powers, and model language. Ciarb’s Guideline on the Use of AI in Arbitration is one of the most detailed institutional treatments of AI use in arbitral proceedings. This explainer shows…

A practical AI evidence preservation checklist covering prompts, outputs, logs, version history, incidents, internal records, and confidentiality controls. If an AI dispute looks likely, evidence can disappear or become ambiguous quickly. This checklist helps businesses and counsel preserve the records that usually matter most: prompts, outputs, logs, versions, evaluations, incident…

A practical guide to AI vendor disputes, including performance failures, hallucinations, misleading claims, confidentiality issues, product changes, and evidence problems. Many AI disputes will start as vendor disputes. A buyer expected one thing, the system did another, the records are messy, and the contract was written as if the product…

A practical guide to AI model licensing disputes, including access rights, scope limits, fine-tuning, sublicensing, output rights, termination, and evidence problems. AI model licensing disputes rarely begin as abstract technology debates. They usually begin when a contract leaves too much unsaid about access, scope, restrictions, outputs, updates, or responsibility after…

A practical guide to California AI arbitration, including neutral ethics, disclosure, confidentiality, privacy, consumer and employment sensitivity, and contract drafting issues. California matters in AI disputes because it combines technology concentration, active privacy enforcement, employment and consumer sensitivity, and a well-developed framework for neutral arbitrator ethics. This guide explains what…

A practical comparison of AI dispute resolution and litigation, including confidentiality, speed, cost, evidence, technical complexity, injunctive relief, and enforceability. Not every AI dispute belongs in arbitration, and not every court case should have been private. This guide compares AI dispute resolution and litigation across confidentiality, evidence, cost, speed, technical…