Latest news with #AIgeneratedcontent
Forbes
4 days ago
- Business
- Forbes
New Study Shows AI Is AI Biased Toward AI. 10 Steps To Protect Yourself
Large language models show dangerous favoritism toward AI-generated content. What does this means for human agency In the sprawling digital landscape of 2025, where artificial intelligence generates everything from news articles to marketing copy, a troubling pattern has emerged: AI systems consistently favor content created by other AI systems over human-written text. This "self-preference bias" isn't just a technical curiosity—it's reshaping how information flows through our digital ecosystem, often in ways we don't even realize. Navigating Digital Echo Chambers Recent research reveals that large language models exhibit a systematic preference for AI-generated content, even when human evaluators consider the quality equivalent. When an LLM evaluator scores its own outputs higher than others' while human annotators consider them of equal quality, we're witnessing something unprecedented: machines developing a form of algorithmic narcissism. This bias manifests across multiple domains. Self-preference is the phenomenon in which an LLM favors its own outputs over texts from other LLMs and humans and studies show this preference is remarkably consistent. Whether evaluating product descriptions, news articles, or creative content, AI systems demonstrate a clear favoritism toward machine-generated text. The implications are worrisome. In hiring processes, AI-powered screening tools might unconsciously favor résumés that have been "optimized" by other AI systems, potentially discriminating against candidates who write their own applications. In academic settings, AI grading systems could inadvertently reward AI-assisted assignments while penalizing less polished, but authentic human work. The Human Side Of The Bias Equation And here's where the story becomes even more complicated: humans show their own contradictory patterns. Participants tend to prefer AI-generated responses. However, when the AI origin is revealed, this preference diminishes significantly, suggesting that evaluative judgments are influenced by the disclosure of the response's provenance rather than solely by its quality. This reveals a fascinating psychological complexity. When people don't know content is AI-generated, they often prefer it — perhaps because AI systems have been trained to produce text that hits our cognitive sweet spots. However, the picture becomes murkier when AI origin is revealed. Some studies find minimal impact of disclosure on preferences, while others document measurable penalties for transparency, with research showing that revealing AI use consistently led to drops in trust. Consider the real-world implications: This inconsistent response to AI disclosure creates a complex landscape where the same content might be received differently depending on how its origins are presented. During health crises or other critical information moments, these disclosure effects could literally be matters of life and death. The Algorithmic Feedback Loop The most concerning aspect isn't either bias in isolation. It's how they interact. As AI systems increasingly train on internet data that includes AI-generated content, they're essentially learning to prefer their own "dialects." Meanwhile, humans who unconsciously consume and prefer AI-optimized content are gradually shifting their own writing and thinking patterns. GPT-4 exhibits a significant degree of self-preference bias, and researchers hypothesize this occurs because LLMs may favor outputs that are more familiar to them, as indicated by lower perplexity. In simpler terms, AI systems prefer content that feels "normal" to them, which increasingly means content that sounds like AI. This creates a dangerous feedback loop. As AI-generated content proliferates across the internet, future AI systems will train on this data, reinforcing existing biases and preferences. Meanwhile, humans exposed to increasing amounts of AI-optimized content might unconsciously adopt its patterns, creating a convergence toward machine-preferred communication styles. The Stakes Are Already High These biases aren't hypothetical future problems — they're shaping decisions today. In recruitment, AI-powered tools are already screening millions of job applications. If these systems prefer AI-optimized résumés, candidates who don't use AI assistance face an invisible disadvantage. In content marketing, brands using AI-generated copy might receive algorithmic boosts from AI-powered recommendation systems, while human creators see their reach diminished. The academic world provides another stark example. As AI detection tools become commonplace, students face a perverse incentive: write too well, and you might be falsely flagged as using AI. Write in a more AI-compatible style and you might avoid detection but contribute to the homogenization of human expression. In journalism and social media, the implications are even more profound. If AI-powered content recommendation algorithms favor AI-generated news articles and posts, we could see a systematic amplification of machine-created information over human reporting and authentic social expression. Building Double Literacy For The AI Age Navigating this landscape requires double literacy — a holistic understanding of ourselves and society, and of the tools we interact with. This type of 360° comprehension encompasses both, our own cognitive biases and the algorithmic biases of AI systems we interact with daily. Here are 10 practical steps to invest in your double bias shield today: The Hybrid Path Forward A pragmatic solution in this hybrid era isn't to reject AI or pretend we can eliminate bias entirely. Instead, we need to invest in hybrid intelligence – the complementarity of of AI and NI, to develop more refined relationships with both human and artificial intelligence. This means creating AI systems that are transparent about their limitations and training humans to be more discerning consumers and creators of information. Organizations deploying AI should implement bias audits that specifically look for self-preference tendencies. Developers need to build AI systems that can recognize and compensate for their own biases. Most importantly, we need educational frameworks that help people understand how AI systems think differently from humans. Beyond good and bad judgment this is the time to acknowledge and harness differences deliberately. The AI mirror trap puts a spotlight on this moment we're living through. We're creating assets that reflect our own patterns back at us, often in amplified form. Our agency in this AI-saturated world depends not on choosing between human and artificial intelligence, but on developing the wisdom to understand and navigate both. The future belongs not to those who can best mimic AI or completely avoid it, but to those who can dance skillfully with both human and artificial forms of music has just begun. Let's start practicing.
Forbes
14-07-2025
- Business
- Forbes
17 Ways To Build Stakeholder Trust In The Age Of AI & Info Overload
In today's digital era, misinformation spreads quickly and AI-generated content is everywhere. Clarity and credibility in communication matter more than ever, especially for leaders communicating with their stakeholders. Stakeholders are increasingly attuned to tone, intent and authenticity, especially when decisions impact people directly. Below, 17 Forbes Human Resources Council members share strategies that can help you reinforce trust across every layer of communication. Remember, it's not just about what you say, but how you validate it. 1. Lead With Purpose To Keep Communication Human In An AI World As AI accelerates, the organizations that earn trust will be those that remain deeply human. Trust is built through communication that explains what AI does, why it matters, who remains accountable and how decisions are made. The most credible leaders communicate with precision, lead with purpose and foster trust through every interaction. Stakeholders are drawn to that clarity and conviction. - Stella H. Kim, HRCap, Inc. 2. Clarify AI Use Through Transparent And Consistent Messaging Trust starts with transparency. Be clear about how and where you use AI: what it does, what it doesn't and how it is governed. Don't overpromise, acknowledge limitations and take accuracy seriously. Most importantly, communicate like humans and stay consistent in messaging across teams and channels. The best way to earn trust is through clarity, consistency and real accountability. - Amy Cappellanti-Wolf, Dayforce 3. Equip Leaders To Understand And Model Responsible AI Adoption AI is far from perfect. Get your experts and leaders adopting AI into their workflows and data analysis quickly, so they can see firsthand the limitations and opportunities for the organization. Critical-minded leaders can establish workflows that yield trustworthy results and teach their teams the pitfalls to avoid. - James Glover, Flint Learning Solutions 4. Provide Ethical Guidelines And Create Feedback Loops The recent Hacking HR AI Virtual Summit spotlighted this: To build trust and reduce misinformation, organizations must disclose how AI is used, provide ethical guidelines and create feedback loops. It is important to align AI with an organization's mission and values, provide ongoing training with teams to question outputs and identify improvements. Trust starts with transparency. - Sherry Martin 5. Maintain A Human Voice While Scaling With AI In the age of AI and misinformation, trust starts with intention. Don't let AI take over your company's voice. Use the technology to enhance speed and scale, but always apply critical thinking and add your human touch. People recognize authenticity. When communication feels real, thoughtful and consistent, trust follows. - Simon De Baene, Workleap Forbes Human Resources Council is an invitation-only organization for HR executives across all industries. Do I qualify? 6. Balance Innovation With Honest Conversations About Change Be honest. Explain to them the importance of a balance of innovative technologies and human intelligence to move the organization forward. This is not limited to AI but to any technological advancement. This is not about making promises about job security, but being transparent about how you expect the two to intersect. Lack of clarity and vision creates fear and chaos. - Jalie Cohen, Radiology Partners 7. Establish Authenticity Through A Distinct Organizational Voice Invest moderate effort in an original voice. It's not so hard to prove your unique identity and, therefore, authenticity via language cues. Invoke signature phrases and verbs, hark back to familiar themes and mention valued people. Going beyond lazy, generic communication, the kind people snooze through or ignore, sets your company and leaders apart, and one day might buy you credibility in a crunch. - John Kannapell, CYPHER Learning 8. Anchor Messaging In Values, Not Just Information Speed In an era where AI can generate answers faster than humans can verify them, people crave authenticity over perfection. Organizations earn trust by being transparent about how decisions are made, how tech is used and where human judgment still leads. HR can model this by anchoring communication in values, context and accountability. - Nicole Brown, Ask Nikki HR 9. Pace Your Communication Strategy To Align With Regulations Although AI is advancing rapidly, that doesn't mean you have to move as quickly. Instead, create your communication plans in line with current legislative standards to ensure your stakeholders have up-to-date information that reflects your company's plans and compliance needs. Building trust can take time. - Caitlin MacGregor, Plum 10. Explain The 'Why' Behind AI To Build Long-Term Trust In the age of AI and misinformation, trust is built on three pillars: transparency, consistency and humanity. Organizations must clearly explain how AI is being used—and more importantly, why. When the purpose behind a move is identified, understood and communicated with honesty, people are more likely to see its value. Trust grows when stakeholders don't just hear "what" but "why," too. - Ankita Singh, Relevance Lab 11. Own Your AI Use With Honest, First-Person Transparency You can instill trust with honesty. 'I wrote this. I used AI to source peer-reviewed studies to augment and support my position. That said, I was the thought leader on the concept we are discussing. I used AI to increase my productivity and bring points of view I would not have known if I were doing a general search.' Take ownership of your use of AI and provide honest transparency on how you use AI. This helps everyone. - John Pierce, John Pierce Consulting 12. Communicate With Precision To Foster Psychological Safety Trust isn't built through volume—it's built through precision. In an AI-driven world, organizations must lead with source transparency, clarify decision logic and name the limits of what they know. Equip leaders to communicate with psychological safety in mind. The goal isn't just to inform—it's to foster trust that holds under pressure. - Apryl Evans, USA for UNHCR 13. Use Technology Responsibly And Prioritize Human Oversight Organizations can build trust by using secure and effective technology, clearly communicating their efforts and educating their stakeholders. They should leverage powerful tools like AI responsibly, with human oversight, and deliver personalized, proactive and transparent interactions, especially within critical channels like digital banking. - Julie Hoagland, Alkami 14. Show The Humans Behind The Automation To Build Credibility Don't hide the humans behind the AI. Show who's accountable, what safeguards exist, and why automation supports (not replaces) your workforce. That's how you earn stakeholder trust. After all, AI doesn't erode trust; opacity does. Build credibility by clearly explaining how decisions are made, especially when they impact hiring, compliance or livelihoods. - Vardhan Kapoor, Firstwork 15. Blend Human Insight With AI For Clearer, Trusted Messaging Effective workplace communication will only help businesses achieve better results if they leverage both AI and human intelligence. Maintaining an adequate level of communication becomes increasingly challenging as a company grows, yet relying solely on AI can be problematic. To ensure that employees understand the communication, it must be accurate and analyzed by human experts. - Dr. Nara Ringrose, Cyclife Aquila Nuclear 16. Create A Verified AI Portal To Validate Organizational Information Organizations seeking to instill trust in the era of AI should establish a dedicated AI portal that verifies all types of internal and external information (memos, reports, corporate rumors), essentially generated by AI, and should be cross-referenced by multiple AI systems for validation. Credible, automated and independent sources should be utilized to reinforce the credibility of the sources. - Kevin Walters, Top DEI Consulting 17. Include Employees In Tech Decisions To Strengthen Transparency Transparency is key to effective communication in the workplace. Employees want to feel informed and included in decisions being made in their organization—and this includes bringing new technology onboard and how to effectively and ethically use AI to support your work (not replace your workers). - Marcy Klipfel, Businessolver
Yahoo
10-06-2025
- Yahoo
Hilliard man allegedly aletered photos to depict child pornography
COLUMBUS, Ohio (WCMH) – A Hilliard man is under arrest for possessing sexual material depicting children, including images generated by artificial intelligence. Austin Pittman, 25, was arrested last month and faces federal charges of pandering sexually oriented matter involving a minor. According to court records filed Monday, electronic devices belonging to Pittman allegedly contained hundreds of images depicting children engaging in sexual acts, including some generated and used by law enforcement officials to track suspects. Pittman allegedly altered images he took to have them depict child sexual abuse. The investigation into Pittman started in Fort Bragg, North Carolina, where Pittman was given an 'other than honorable discharge' from the U.S. Army, court records state. The investigation traced IP addresses and Kik usernames all registered to Pittman, according to court records. When confronted by law enforcement, Pittman allegedly admitted to viewing the child pornography for the 'shock factor,' court records state. He then allegedly admitted to exchanging child sexual material with others and that he had a pornography problem. He is charged with receipt/transportation/distribution/possession of child pornography, possession of AI generated child pornography, and production of morphed image or AI generated child pornography. There is currently no scheduled court appearance for Pittman. Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
