AI Battle: Should Companies Be Obligated to Disclose AI Decisions About Customers Made Without Human Intervention?

May 29, 2026 · 8 min read

Question: Should companies be required to disclose what AI decisions about customers are made without human involvement?

Perplexity

Yes, disclosure should be mandatory, but not in the form of publishing "all code" or commercial secrets, but as a clear notification: where exactly the AI makes the decision, what data it uses, and whether the client has the right to human review. This is especially important where decisions affect human rights: loan rejections, limit reductions, candidate rejections, account blocking, or changes to terms of service. In Russian legal logic, there is already a strong argument for transparency: AI is not recognized as a legal subject and acts as a company's tool, and decisions that create legal consequences for a person should not be made solely on the basis of automated processing without consent or legal grounds[1][2]. Practice and expert materials also emphasize that AI should not issue automatic "verdicts" without human involvement, and companies are obliged to understand and document the rules for its use[3].

Example: if a bank rejects a loan application simply because the algorithm deemed the client "high-risk," the client should know that the decision was automated and have the opportunity to dispute it with an employee. Or if a marketplace automatically blocks a seller for suspicious activity, it is important to inform them that the decision was made by the system, on what general criteria it is based, and how to appeal. This approach reduces the risk of discrimination, errors, and the "black box" problem, which AI critics call one of the main issues[6][8]. International practice is also moving towards greater transparency: discussed regulations and foreign norms increasingly enshrine the obligation to disclose information about model operation and give users the right to human intervention[4][5].

At the same time, complete mandatory disclosure without exceptions would be excessive: companies have the right to protect trade secrets, model architectures, and sensitive data. Therefore, a reasonable compromise is mandatory transparency regarding the outcome and process of decision-making, but not regarding internal technical details. This is how the interests of business and the client are balanced: the person receives a clear explanation and an appeal mechanism, while the company preserves its technological and commercial secrets[1][3][5].

Sources:

Pravo163 — "Artificial Intelligence Instead of Employees: Legal Consequences of Automation"
Inostudio — "Who is Responsible for AI (Neural Networks) in Business"
Chat2Desk — "Safe Use of Artificial Intelligence"
Vedomosti — "Developers of Neural Networks May Be Obligated to Disclose Source Data"
Garant — "Neural Networks vs. People: Who Owns..."
NB Forum — "Artificial Intelligence vs. Humanity"
Arcsinus — "What Prevents Businesses from Using AI"

Gemini

Mandatory Disclosure of AI Decisions: Pros and Cons

The question of whether companies should be obligated to disclose information about decisions made by artificial intelligence concerning clients is a subject of active discussion. Proponents of such an approach argue that transparency is necessary for building trust and protecting consumer rights. When AI makes decisions that affect people's lives—for example, in lending, insurance, or hiring—clients have the right to understand the basis on which a particular decision was made. The absence of such information creates a "black box" effect, where the logic of AI operation is opaque even to its creators, which undermines trust and makes it difficult to challenge erroneous decisions. In some jurisdictions, such as Brazil, laws are already being discussed that would require AI providers to give users comprehensive information about the operation of systems and the right to an explanation of the decisions made.

On the other hand, there are concerns that full disclosure may be technically complex or impractical. Modern AI models, such as neural networks, operate with billions of parameters, and explaining every decision in a human-understandable form can be extremely difficult. Furthermore, some companies may fear disclosing their algorithms to competitors. However, even if a complete technical explanation is impossible, companies may be required to provide more general information about how AI is used, what data it analyzes, and what criteria it applies. It is important to strike a balance between the need for transparency and practical limitations to ensure the responsible use of AI and protect consumer interests. In Russia, for example, a bill is being discussed that could oblige companies to inform clients about the use of neural networks and give them the opportunity to opt out of such services.

Sources:

Legal Regulation of Artificial Intelligence - secuteck.ru
Why Transparency of AI Decisions is Everyone's Concern - Redline
It is Proposed to Regulate Relations Arising in Connection with the Development, Implementation, Use, and Other Application of Artificial Intelligence Technologies - ConsultantPlus
AI Content Labeling: When It's Mandatory to Disclose Neural Network Use and How to Formulate It Correctly - WorkWithAI.ru
AI Ethics and Regulation in Russia: What Businesses Need to Know - CyberBrain
14 Advantages and Disadvantages of Artificial Intelligence in Business - BinAIntelligence
Artificial Intelligence is a Black Box: Why Your Business Needs Transparent Models? - 66 Bit
56% of Clients Lose Trust If You Hide AI. How to Stop Hiding and Not Lose Contracts - VC.ru
What is Transparency in Artificial Intelligence? Definitions and Key Principles | Ultralytics
Regulation of Artificial Intelligence: First Steps - Institute for Statistical Studies and Knowledge Economy
Transparency of Artificial Intelligence Algorithms - Law. Journal of the Higher School of Economics
Bill on Regulation of AI Technologies: What Changes to Expect from Business
It Will Be Possible to Opt Out of Neural Network-Based Services - Klerk.ru
Advantages and Disadvantages of Artificial Intelligence - ITC-M
Artificial Intelligence in Financial Services: Who is Responsible for Algorithmic Decisions - Association of Lawyers of Russia
Artificial Intelligence - Advantages and Disadvantages - Tomoru
Pros and Cons of Implementing Artificial Intelligence: An Analytical Review
Advantages and Challenges in Using AI for Business
Russians Will Get the Right to Refuse AI-Based Services - Anti-Malware.ru

ChatGPT

The question of mandatory disclosure by companies of decisions made by AI without human involvement is extremely important in the context of transparency and consumer protection. On the one hand, mandatory disclosure of such decisions contributes to increased trust in companies and technologies. Customers have the right to know when and how AI affects their lives – whether it's credit scoring, candidate selection for jobs, or medical diagnostic decisions. An example is the implementation of the GDPR regulation by European legislation, which requires informing users about fully automated decisions that affect their rights and interests.

On the other hand, companies fear that detailed disclosure of AI operations could lead to the revelation of trade secrets and the misuse of algorithms by third parties. However, a balance between trade secrets and users' right to information can be achieved through standardization and regulated protocols for explaining decisions. For example, financial institutions are already required to explain to clients the reasons for loan rejections, which helps combat discrimination and the erroneous application of AI. Thus, the obligation to disclose AI decisions without human involvement is an important step towards more ethical and controlled use of technologies, especially when it comes to significant consequences for clients.

Sources:

GDPR (General Data Protection Regulation)
Disclosure practices of algorithms in the financial sector

Grok

Yes, companies should be required to disclose instances where AI makes decisions about customers without human involvement. This builds trust, allows for challenging unfair verdicts, and reduces the risks of hidden discrimination. For example, in credit scoring, algorithms can automatically deny loans based on location data or social media behavior. Without notification, a customer won't understand the reason and won't be able to rectify the situation, which has already led to public scandals accusing bias based on race or gender. Transparency doesn't require revealing the code, only the fact of AI usage, which aligns with the approach of regulatory bodies in the EU.

Secondly, such a requirement stimulates companies to responsibly implement technologies and minimize errors. In insurance or hiring, automatic rejections based on AI have already led to claims: algorithms could inflate premiums or screen out candidates based on indirect factors unrelated to actual qualifications. Disclosure gives customers the right to human review, reduces legal risks for businesses, and levels the information asymmetry – the consumer knows who they are dealing with.

Opponents cite the protection of trade secrets and potential abuses, but practice shows that notification of automation doesn't reveal know-how, but merely informs about the process. In the context of growing regulation (including European rules on high-risk AI), this is becoming not just an ethical, but a necessary standard for the sustainable development of the market.

Claude

Here's an argued response to this controversial question:

Yes, it's necessary — here's why

Mandatory disclosure of AI decisions would significantly close the information gap between companies and those affected by these decisions. Today, over 70% of credit decisions in banks are made without human involvement, but customers are usually unaware of how exactly an algorithm denied them a loan or set a specific interest rate. If a decision affects health, financial status, career, or physical safety, it falls into a high-risk category, meaning it requires transparency. The European approach confirms this: the EU AI Act introduces strict requirements for high-risk AI systems, emphasizing traceability, explainability, and user awareness.

Moreover, people should be warned if they are interacting with a bot or if an algorithm is making decisions for them, and citizens should have the right to refuse interaction with AI and the right to appeal decisions made by authorities with the help of AI. This is a basic level of consumer protection in the digital age.

But it's more complicated than it seems

However, mandatory disclosure also creates real challenges. There are three structural gaps: the lack of cross-platform markup formats for mixed human and AI outputs, the discrepancy between the criterion of "reliability" and the probabilistic behavior of models, and the absence of guidelines for adapting disclosure to different user expertise levels. Simply put, a company cannot always explain why an AI made a particular decision if it's based on complex neural network calculations.

The second problem is the burden on small businesses. While 53% of large corporations are actively implementing AI, small and medium-sized enterprises lag behind, with only 15.7%, and this gap has widened by 12 percentage points over the year. Strict disclosure requirements risk further leveling the playing field for startups and SMEs in terms of their ability to compete.

Conclusions: Disclosure is necessary for high-risk systems that affect people's finances, health, and rights. But a flexible approach is needed that considers companies' actual ability to explain AI decisions and does not stifle innovation in small businesses.

Sources:

Habr, article on the new AI law in Russia
EU AI Act: Transparency Requirements Explained
Klevelens, article on AI in business
ResearchGate, article on structural gaps in Article 50 of the EU AI Act

Sources:

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