When a Bot Signs a Contract, Who's Bound? Chopra & White Explained

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

In this video, we break down Samir Chopra and Laurence White's classic analysis of autonomous contracting and the "contracting problem" created by artificial agents.

The paper asks a foundational question for digital commerce: when a bot forms a contract, who should be legally bound by it? Rather than inventing a brand-new legal category for AI systems, Chopra and White argue that agency law already offers a workable answer.

The paper walks through:

- why the "mere tool" theory starts to fail as software becomes more autonomous

- how actual authority and apparent authority can be translated into algorithmic settings

- the paper's taxonomy of specification errors, induction errors, and malfunctions

- why agency law can allocate risk more coherently across operators, users, and third parties

- how existing legislative approaches compare to the agency-law model

Source paper: Samir Chopra & Laurence White, 'Artificial Agents and the Contracting Problem: A Solution Via an Agency Analysis' (2009) University of Illinois Journal of Law, Technology & Policy 363-380.

If you're interested in AI contracts, autonomous agents, legal tech, and the future of digital commerce, this episode gives you a compact map of one of the field's most important early arguments.

#AIContracts #LegalTech #AgencyLaw #AutonomousCommerce #ContractLaw

Christoph Busch's 2025 paper asks whether European Union consumer law is ready for the rise of AI agents that shop, compare, and contract on behalf of consumers. This video explains Busch's core argument: the move from human-centered online shopping to the "Custobot Economy" forces consumer law to rethink information duties, manipulation rules, average-consumer standards, and the timing of legal protection itself.

Source:

Christoph Busch, "Consumer Law for AI Agents" (Yale University, 2025).

Topics covered:

- generative AI vs. agentic AI

- Custobots and the shift to agent-to-agent commerce

- SEO vs. AI Agent Optimization (AAO)

- the limits of human-centric consumer law

- the "Average Custobot" problem

- machine-readable disclosures and decentralized personalization

- choice engines and paternalism

- dark patterns, adversarial attacks, and prompt injection

- the three future pillars of consumer law for AI agents

- legal recognition, the no-barrier principle, and design-based protection

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

Can AI systems form contracts, who is legally responsible when they do, and what happens when an automated transaction goes badly wrong?

This video explains Professor Tan Cheng-Han's 2026 article, "COVID-19, Agentic Artificial Intelligence and Contract Formation," published in The Chinese Journal of Comparative Law.

Using Quoine v B2C2 as the central case study, the paper looks at the broader structure of AI contracting in common law:

- whether agentic AI should be treated as a legal agent

- when a platform operator may be acting on behalf of users instead

- how automated contract formation fits within ordinary contract doctrine

- why mistake doctrine may become the main safeguard against aberrant outcomes

Topics covered:

- generative AI versus agentic AI

- legal agency and platform responsibility

- Quoine v B2C2

- tool theory and extended assent

- automated transactions legislation

- unilateral mistake and equitable relief

- UCITA as a conceptual reference point

- how common law may adapt to increasingly autonomous systems

Source:

Tan Cheng-Han, "COVID-19, Agentic Artificial Intelligence and Contract Formation," The Chinese Journal of Comparative Law (2026).

This content is provided for informational and educational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

Vincent Ooi's 2022 article asks how common law should handle contracts formed by autonomous software. This digest walks through the contracting problem, the limits of the mere tools theory, the failure of the agency approach, Ooi's extended objective theory of contract, and why unilateral mistake in equity becomes the key doctrinal safeguard when software malfunctions.

Source:

Vincent Ooi, "Contracts Formed by Software: An Approach from the Law of Mistake," Journal of Business Law (2022).

Topics covered:

- objective theory of contract

- mere tools theory

- agency approach

- extended objective theory

- unilateral mistake

- mistake in equity

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

What happens when an AI system forms a contract by mistake?

This video explains Maarten Herbosch’s 2025 article, “To err is human: Managing the risks of contracting AI systems,” published in Computer Law & Security Review. The paper argues that existing contract-law frameworks are flexible enough to handle AI-formed contracts while still protecting deployers in the right cases.

In this digest:

- AI-supported vs. AI-driven contracting

- Herbosch’s dual-function account of intent

- Two layers of deployer protection

- Reasonable expectations and unilateral mistake

- Risk-bearing and excusability in AI contracting

This content is provided for informational and educational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

#AIContracts #ContractLaw #ArtificialIntelligence #LegalTech #UnilateralMistake

What happens when an algorithm forms a contract at the wrong price or on the wrong assumptions? Can contract law treat that as a legal mistake, and if so, whose mistake is it?

This video explains Cristina Frattone's 2024 article on algorithmic mistakes in machine-made contracts. It covers:

- the difference between automation mistakes and autonomy mistakes

- why attribution is the central legal problem

- how *Quoine v B2C2* exposes the limits of current mistake doctrine

- why Frattone proposes a dedicated rule for algorithmic mistake

If you're interested in AI contracting, automated trading, and private law doctrine, this paper is a useful map of the problem.

Further reading:

- UNCITRAL Model Law on Automated Contracting

- ELI Guiding Principles on Digital Assistants for Consumer Contracts

- Wendehorst on AI in contracting

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

When an AI system executes a deal on its own, is that a valid contract, and whose contract is it?

This video explains Eliza Mik's 2020 paper, From Automation to Autonomy: Some Non-existent Problems in Contract Law. It focuses on her core claim that existing contract-law principles can already handle automated contracting without granting legal personhood to software or treating advanced systems as autonomous legal actors.

The video covers:

- Mik's distinction between the operator and the user

- why separation, agency, and anthropomorphization theories fail

- the three main arguments for attribution to the operator

- operator protection through existing doctrine, including apparent mistake and lack of contractual intention

- legislative confirmation from electronic-transactions frameworks

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.

Source:

Eliza Mik, "From Automation to Autonomy: Some Non-existent Problems in Contract Law" (2020), SSRN Working Paper.

https://papers.ssrn.com/abstract=3635346

A brief digest of Christiane Wendehorst’s 2024 Discussion Draft Principles for AI in Contracting (Version 2.1).

This video explains the draft in a strictly informational way, focusing on:

- what PAIC is and how it is positioned

- the scope of the draft

- attribution and operator responsibility

- framework agreements and default rules

- functional equivalence in Part IV

- selected open questions raised by the draft

This is an explanatory summary for informational purposes only. It is not legal advice.

What are algorithmic or automated contracts, and how do the European Law Institute’s Guiding Principles and Model Rules on Digital Assistants for Consumer Contract (DACC) and UNCITRAL’s Model Law on Automated Contracting (MLAC) approach them?In this video, we break down the architecture of algorithmic contracts in a practical and accessible way, focusing on:- what “algorithmic contracts” mean in DACC- how ELI's DACC approach digital asset and data-driven contracting- how UNCITRAL’s Model Law on Automated Contracting (MLAC) fits into the picture- the key differences, overlaps, and implications for digital commerce, smart transactions, and cross-border legal designThis video is for educational purposes only and does not constitute legal advice.If you’re interested in digital law, automated contracting, smart contracts, AI governance, and the future of commercial law, subscribe for more explainers.#AlgorithmicContracts #AutomatedContracting #UNCITRAL

This show compares the UNCITRAL Model Law on Automated Contracting (2024) with the ELI Guiding Principles and Model Rules on Digital Assistants for Consumer Contracts (2025).

It explains:

- what DACC covers and how its digital assistant differs from MLAC's broader automated system

- how DACC Article 22 combines default attribution with a consumer-specific non-attribution safety valve

- how MLAC Article 7 and optional Article 8 handle unexpected output differently

- what DACC adds through disclosure, anti-manipulation, objection-model, and supplier-liability rules

Key references discussed:

- UNCITRAL Model Law on Automated Contracting (2024)

- ELI Guiding Principles and Model Rules on Digital Assistants for Consumer Contracts (2025)

- Quoine Pte Ltd v B2C2 Ltd [2020] SGCA(I) 02

- Moffatt v Air Canada [2024] BCCRT 149

This content is provided for informational purposes only and does not constitute legal advice. You are responsible for how you use this information and should seek qualified advice for specific matters.