INTERVIEW ON THE PRICE OF BUSINESS SHOW, MEDIA PARTNER OF THIS SITE.
Recently Kevin Price, Host of the nationally syndicated Price of Business Show, interviewed Alexander Paykin.
The Alexander Paykin Commentaries
Artificial intelligence is increasingly used not just for tasks like translation or search, but for advice—on life decisions, relationships, career moves, and moral questions. Tools like ChatGPT or Replika simulate thoughtful, conversational guidance, leading many to rely on them as informal counselors. But this growing trend carries serious, often overlooked consequences.
AI-generated advice creates a false sense of authority. The language is confident, coherent, and sometimes even reassuring. Yet behind the words is no real understanding—just a prediction engine trained on vast datasets. These systems can’t assess context, grasp emotional nuance, or reflect on the consequences of their suggestions.
When users make significant life choices based on AI input—whether quitting a job, ending a relationship, or confronting a legal dilemma—they may suffer real-world harm. Unlike professional advisors or consultants, AI systems carry no legal duty of care. If a human counselor gives poor advice, they can be held accountable. When AI does, there’s typically no recourse. Most platforms shield themselves with disclaimers that state the information is for entertainment or general purposes only, regardless of how persuasive or specific it may sound.
There are also unresolved legal questions around data privacy. People routinely share personal stories and decisions with AI systems, unaware that their input may be stored, analyzed, or used to train future models. In jurisdictions like the EU, this may conflict with data protection laws such as the GDPR, which require clear consent for processing sensitive personal data. In countries like the U.S., where consumer privacy laws are more fragmented, users have even fewer guarantees.
Beyond the legal risks is the deeper ethical concern: users may start to outsource judgment to machines. Over time, turning to AI for personal decisions erodes self-agency and critical thinking. Worse, AI systems may carry subtle biases inherited from their training data, influencing users in ways that are neither visible nor accountable.
There is currently no consistent regulation that defines the boundaries of AI’s role in personal advising. Without clearer rules, platforms are free to offer what looks like guidance without taking on the responsibility that normally comes with it. Developers influence user behavior on a massive scale—yet can avoid consequences when that influence leads to harm.
Until robust legal frameworks are in place, users must treat AI-generated advice with caution. These tools can assist with brainstorming or offering perspective—but they should not be mistaken for wise, neutral, or reliable counsel. Advice without accountability is not just risky—it’s potentially dangerous.
