St. Bonaventure professor announces congressional run for NY23 in 2026 election
Aaron Gies, of Olean, a current assistant professor of Theology and Franciscan Studies at St. Bonaventure, and leader of a non-profit organization, announced his bid for Congress on Tuesday, July 15.
Gies intends to challenge Nick Langworthy, emphasizing the need to elect leaders who listen to and lift up those they serve, according to his announcement.
Candidate for New York's 23rd Congressional District makes stop at Harris Hill
'We're in an affordability crisis in New York State,' Gies said, 'The American Dream is out of reach for most people. A government that favors those at the top isn't just wrong because it's unfair, it's wrong because it doesn't work,' he said. 'This crisis can only be solved by all of us together. Rural folks know how to take care of themselves. They need their government to support them, not sell them out to elite interests,' Gies said in his announcement.
Gies made claims in his announcement that Congressman Langworthy refuses to meet with his constituents, tariffs and high prices are ruining small businesses, while Langworthy rubber-stamps everything the Trump administration does, regardless of the issue.
Gies pointed out that these are some of the key issues why he is running for Congress.
Born in rural North Carolina, Gies now lives in Alleghany County and understands small-town life. He spends time as a bookkeeper and helps run a non-profit vegetable farm.
Gies now joins Kevin Stocker in the democratic race running against Langworthy.
18 News reached out to Congressman Langworthy's office for a statement on Wednesday. Langworthy said he will not comment on any campaign matters at this time.
Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
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Forbes
35 minutes ago
- Forbes
OpenAI: ChatGPT Wants Legal Rights. You Need The Right To Be Forgotten.
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But they won't be the only ones asking questions. Every conversation becomes a four-party exchange: the user, the model, the platform's internal optimization engine, and the advertiser paying for access. It's entirely plausible for a prompt about the Pittsburgh Steelers to return a response that subtly inserts 'Buy Coke' mid-paragraph. Not because it's relevant—but because it's profitable. Recent research shows users are significantly worse at detecting unlabeled advertising when it's embedded inside AI-generated content. Worse, these ads are initially rated as more trustworthy until users discover they are, in fact, ads. At that point, they're also rated as more manipulative. 'In experiential marketing, trust is everything,' says Jeff Boedges, Founder of Soho Experiential. 'You can't fake a relationship, and you can't exploit it without consequence. If AI systems are going to remember us, recommend things to us, or even influence us, we'd better know exactly what they remember and why. Otherwise, it's not personalization. It's manipulation.' Now consider what happens when advertisers gain access to psychographic modeling: 'Which users are most emotionally vulnerable to this type of message?' becomes a viable, queryable prompt. And AI systems don't need to hand over spreadsheets to be valuable. With retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF), the model can shape language in real time based on prior sentiment, clickstream data, and fine-tuned advertiser objectives. This isn't hypothetical—it's how modern adtech already works. At that point, the chatbot isn't a chatbot. It's a simulation environment for influence. It is trained to build trust, then designed to monetize it. Your behavioral patterns become the product. Your emotional response becomes the target for optimization. The business model is clear: black-boxed behavioral insight at scale, delivered through helpful design, hidden from oversight, and nearly impossible to detect. We are entering a phase where machines will be granted protections without personhood, and influence without responsibility. If a user confesses to a crime during a legally privileged AI session, is the platform compelled to report it or remain silent? And who makes that decision? These are not edge cases. They are coming quickly. And they are coming at scale. Why ChatGPT Must Remain A Model—and Why Humans Must Regain Consent As generative AI systems evolve into persistent, adaptive participants in daily life, it becomes more important than ever to reassert a boundary: models must remain models. They cannot assume the legal, ethical, or sovereign status of a person quietly. And the humans generating the data that train these systems must retain explicit rights over their contributions. What we need is a standardized, enforceable system of data contracting, one that allows individuals to knowingly, transparently, and voluntarily contribute data for a limited, mutually agreed-upon window of use. This contract must be clear on scope, duration, value exchange, and termination. And it must treat data ownership as immutable, even during active use. That means: When a contract ends, or if a company violates its terms, the individual's data must, by law, be erased from the model, its training set, and any derivative products. 'Right to be forgotten' must mean what it says. But to be credible, this system must work both ways: This isn't just about ethics. It's about enforceable, mutual accountability. The user experience must be seamless and scalable. The legal backend must be secure. And the result should be a new economic compact—where humans know when they're participating in AI development, and models are kept in their place. ChatGPT Is Changing the Risk Surface. Here's How to Respond. The shift toward AI systems as quasi-participants—not just tools—will reshape legal exposure, data governance, product liability, and customer trust. Whether you're building AI, integrating it into your workflows, or using it to interface with customers, here are five things you should be doing immediately: ChatGPT May Get Privilege. You Should Get the Right to Be Forgotten. This moment isn't just about what AI can do. It's about what your business is letting it do, what it remembers, and who gets access to that memory. Ignore that, and you're not just risking privacy violations, you're risking long-term brand trust and regulatory blowback. At the very least, we need a legal framework that defines how AI memory is governed. Not as a priest, not as a doctor, and not as a partner, but perhaps as a witness. Something that stores information and can be examined when context demands it, with clear boundaries on access, deletion, and use. The public conversation remains focused on privacy. But the fundamental shift is about control. And unless the legal and regulatory frameworks evolve rapidly, the terms of engagement will be set, not by policy or users, but by whoever owns the box. Which is why, in the age of AI, the right to be forgotten may become the most valuable human right we have. Not just because your data could be used against you—but because your identity itself can now be captured, modeled, and monetized in ways that persist beyond your control. Your patterns, preferences, emotional triggers, and psychological fingerprints don't disappear when the session ends. They live on inside a system that never forgets, never sleeps, and never stops optimizing. Without the ability to revoke access to your data, you don't just lose privacy. You lose leverage. You lose the ability to opt out of prediction. You lose control over how you're remembered, represented, and replicated. The right to be forgotten isn't about hiding. It's about sovereignty. And in a world where AI systems like ChatGPT will increasingly shape our choices, our identities, and our outcomes, the ability to walk away may be the last form of freedom that still belongs to you.