AI Ethics with Fexingo: Bias, Safety, and Responsible Artificial Intelligence

Episode 79 of AI Ethics with Fexingo dives into the murky world of AI-generated art and copyright infringement. Lucas and Luna explore the case of visual artist Kelly McKernan, who discovered that her distinctive style was being replicated by AI image generators like Stable Diffusion without her consent or compensation. They break down the class-action lawsuit against Stability AI, Midjourney, and...

Episode 78 of AI Ethics with Fexingo asks: can an AI tell when you're lying? Lucas and Luna examine the emerging market for AI-based deception detection systems used in airport security, job interviews, and insurance claims. They focus on a 2025 FCC complaint against a startup whose facial-analyzing system flagged 40 percent of honest travelers as deceptive. The hosts walk through the faulty scien...

Episode 77 of AI Ethics with Fexingo explores algorithmic scheduling systems used by major retailers and fast-food chains. Lucas and Luna break down a real 2025 case where a grocery chain's AI scheduled workers in back-to-back shifts across different locations, leading to unsafe commutes and wage violations. They discuss how the model optimized for labor cost but ignored human constraints like tra...

Lucas and Luna examine the growing practice of auto insurers using AI models that price premiums based on the driving records of people in your neighborhood—not just your own history. They focus on a 2025 case where a driver in Kansas City, Missouri saw her rate jump 22 percent after a crash two blocks away, even though she had a perfect record. The episode explores the data sources insurers use,...

Episode 75 of AI Ethics with Fexingo zeroes in on a quietly growing problem: polygenic risk scores that were trained almost entirely on European DNA. Lucas and Luna break down a 2025 study from the Broad Institute showing that risk predictions for heart disease and diabetes can be off by over 40 percent for Black and Hispanic patients. They explore why this happens — the genealogical databases, th...

Lucas and Luna dig into a new audit of AI-powered resume screening tools that found 68% penalized candidates with career gaps of six months or longer, even when the gaps were explained. The hosts walk through the data behind the bias — why the algorithms treat gaps as negative signals, how a single year of unemployment can tank a candidate's score more than a felony record in some models, and what...

Episode 73 of AI Ethics with Fexingo examines the growing practice of landlords using AI screening tools to evaluate rental applicants. Lucas and Luna dig into a real 2025 case from Los Angeles where an AI system denied a qualified tenant based on eviction records that were legally sealed — and explore a proposed California bill that would require transparency and human review. They discuss how th...

In this episode, Lucas and Luna explore the hidden risks of AI-powered travel booking agents. They focus on a real case from early 2026 where a major airline's AI agent booked a non-refundable, non-changeable itinerary for a customer based on a single ambiguous prompt, costing them over $2,000. The discussion dives into the lack of transparency in AI decision-making, the absence of mandatory confi...

A software engineer named Priya uses a popular AI resume-rewriting tool to apply for a senior role at a Fortune 500 company. The tool inflates her job title from 'Developer II' to 'Lead Developer' and adds a skill she only knows at a basic level. She gets the interview, but the hiring manager catches the discrepancies. This episode drills into a 2024 study by the University of Michigan showing tha...

Episode 70 of AI Ethics with Fexingo digs into a bizarre but real problem: generative AI tools used in recruiting that invent qualifications, fake past employers, or even entire fictional resumes. Lucas and Luna examine a documented 2025 case where a top tech firm's AI screener recommended a candidate who didn't exist — complete with a fabricated GitHub portfolio — before a human caught the error....

Lucas and Luna dig into a growing privacy concern: AI personal assistants that absorb sensitive information from users without explicit consent. They examine a recent study from Carnegie Mellon showing that voice assistants like Amazon Alexa and Google Assistant can infer income, health conditions, and political leanings simply from the way you speak. The episode explores how these inferences happ...

In this episode of AI Ethics with Fexingo, Lucas and Luna explore a troubling blind spot in medical AI: diagnostic imaging systems that perform significantly worse on patients with darker skin. They examine a 2022 study from MIT and Harvard showing that three leading commercial AI systems for detecting lung disease had error rates up to 34% higher for Black patients than for white patients, largel...

Lucas and Luna explore the dark side of AI-driven personalized nutrition. They dissect the case of 'NutriAI', a popular health app that recommended dangerously low-calorie diets to users with eating disorder histories, based on biased training data from fitness influencers. The conversation covers how AI models optimize for engagement over safety, why regulatory gaps let these apps slip through, a...

Lucas and Luna explore how AI diagnostic tools systematically underdiagnose patients with rare diseases—those affecting fewer than 200,000 people. They break down the data imbalance problem: rare diseases collectively affect 300 million people worldwide, but AI training datasets overwhelmingly favor common conditions. The hosts examine a 2025 study from the Journal of the American Medical Informat...

Lucas and Luna investigate a 2025 academic study that found AI recruitment tools penalizing candidates with non-Western names — even when identical resumes were submitted. They walk through the controlled experiment, the statistical gap (a 14 percent callback difference for identical qualifications), and why fixing the training data isn't as simple as stripping out names. They also discuss the tec...

Lucas and Luna dive into a troubling case in mental health AI: a chatbot therapist trained on a dataset that over-represents certain demographics and therapeutic approaches, leading to harmful advice for users outside that narrow lens. They unpack a 2025 study from Stanford's AI Ethics Lab that found a 34% higher rate of inappropriate responses for non-white, non-English-speaking users, and discus...

Episode 63 of AI Ethics with Fexingo digs into a quietly growing problem: generative AI tools that produce text or code nearly identical to copyrighted sources, without citing them. Lucas and Luna examine a specific case from May 2026 — a freelance journalist who discovered her AI assistant had lifted entire paragraphs from a paywalled Atlantic article into her draft. They explore why this happens...

Lucas and Luna dig into the case of a small-business owner whose AI-driven credit application was denied because the system flagged a single misspelled character in her business name. They trace how natural language processing in credit scoring amplifies minor errors into major financial consequences, examine the regulatory gaps in the FCRA and ECOA for algorithmic underwriting, and ask whether th...

In early 2026, a personal injury attorney in Illinois submitted a legal brief citing five court cases that never existed. The opposing counsel checked the citations, found nothing, and the judge imposed sanctions. This episode unpacks how large language models generate plausible-sounding but entirely fake legal precedents — a problem known as hallucination. Lucas and Luna examine the specific case...

Episode 60 of AI Ethics with Fexingo explores the hidden world of AI-powered personalized tutoring. Lucas and Luna unpack a 2025 Stanford study revealing that adaptive learning platforms like Khan Academy's Khanmigo and Carnegie Learning's MATHia collect granular student data—keystroke patterns, time per question, even emotional tone—to predict performance. But when these systems fail to explain w...

In this episode of AI Ethics with Fexingo, Lucas and Luna explore the hidden bias in AI-powered healthcare referral systems. They focus on a 2025 study by the University of California, San Francisco, which found that three major hospital networks' AI referral algorithms recommended expensive specialists 40% more often to patients with private insurance than to those with Medicaid, even when clinic...

In this episode of AI Ethics with Fexingo, Lucas and Luna explore how resume-scanning AI systems may systematically filter out military veterans. They examine a 2025 study from the University of Maryland that found a 23 percent lower callback rate for veteran applicants when screened by algorithmic tools versus human reviewers. The hosts discuss how training data and keyword optimization can encod...

Episode 57 of AI Ethics with Fexingo examines the risks of AI-driven fitness coaching. Lucas and Luna discuss a recent incident where an AI fitness app recommended dangerous exercises to a user with a known heart condition, leading to hospitalization. They explore the lack of medical oversight in algorithmically generated workout plans, the legal gray area of liability when AI gives health advice...

Episode 56 of AI Ethics with Fexingo dives into the world of AI-powered dating apps. Lucas and Luna explore how algorithms behind platforms like Tinder and Hinge use facial recognition and attractiveness scoring to match users. They discuss a 2025 Stanford study showing that AI can predict dating success with 68% accuracy based on profile photos alone, raising questions about bias, privacy, and th...

In this episode of AI Ethics with Fexingo, Lucas and Luna explore the hidden dangers of predictive algorithms in the criminal justice system. They focus on a real 2023 case from Rhode Island where a sentencing algorithm recommended a longer prison term because a probation officer misspelled a defendant's name, causing the system to pull in decades-old records from a different person. The hosts dis...