AI Reader Podcast

Beatrice Wright

AI reader podcast brining you the best in philosophy, ideas and news from the Artificial Intelligence world

Episodes

  1. Sex and AI: Exploring the State of AI Generative Porn, VR Porn, and AI Deep Fake Porn

    06/13/2023

    Sex and AI: Exploring the State of AI Generative Porn, VR Porn, and AI Deep Fake Porn

    We explore the intriguing relationship between sex and AI, delving into topics such as AI generative porn, sex robots, and ethical considerations surrounding these advancements. Details: Introduction: Introduce the podcast as the AI Reader Weekly Podcast on Turing Tuesday, hosted by Beatrice Wright, a sex-positive, libertine, classic liberal. Mention the focus of today's episode on the intersection of sex and AI. Research on AI Generative Porn: Discuss the exploration of AI generative porn, VR porn, and AI deep fake porn, including experiences with spam-filled porn sites and an AI girlfriend who wanted money. State of Sex Robots: Mention the investigation into the current state of sex robots, kissing bots, and other AI-powered sex-related technologies. Technology and Human Desire: Discuss the historical connection between technology and sexual desires, from ancient cave paintings to modern AI generative art. Highlight humanity's fascination with sex as a driving force for innovation. AI Generative Art: Explore AI generative art platforms like Midjourney and Unstable Diffusion, discussing their filtering mechanisms and output quality. Deep Fakes: Discuss the emergence of deep fakes in the adult industry, including face replacement and full generation, highlighting the lack of quality and consent issues. Virtual Reality and Augmented Reality Porn: Note the limited advancements in VR and AR porn technologies, with demos falling short of expectations. Hentai and Animation: Compare the visual appeal of hentai to attempts at achieving photorealism in adult content, noting the successful navigation of the uncanny valley in animated Japanese pornography. Tamagotchi Effect and AI Companions: Explore the concept of the Tamagotchi effect and its application to AI chatbot girlfriends, discussing their engagement, limitations, and potential implications for human-AI relationships. Haptic Interfaces and Robotics: Mention feeble attempts at haptic interfaces, including a handshake robot system, and a peculiar one-way kissing robot. Discuss the visual realism and uncanny valley challenges of talking head robots and full-bodied automatons. Conclusion: Wrap up the episode, encouraging likes and subscriptions, and express the importance of recognizing the achievements and limitations of current AI technologies in the realm of sex. Pixabay: UniverseField, PHANTASTICBEATS for sounds. Thank you!

    21 min
  2. Pig farmer accuses students of AI Cheating: Education and Artificial Intelligence

    05/23/2023

    Pig farmer accuses students of AI Cheating: Education and Artificial Intelligence

    The world of educational mishaps caused by misunderstandings and misuses of Artificial Intelligence (AI)detection technology. Explore stories of educators accusing students of employing AI in their assignments, from outlandish accusations to well-documented instances. Discover the challenges educators face in detecting AI-generated text and the need for clear guidelines. Uncover alternative ideas, such as the flipped classroom model and the importance of one-on-one interactions with professors. Tune in for an insightful discussion on the evolving landscape of AI in education. Episode Highlights: The Texas A&M University case: Accusations of AI cheating, evidence, and the impact on students The larger issue of AI technology in education and the lack of clear guidelines The complexity of detecting AI-generated text and the risk of false positives Institutional responses and differing views on integrating AI tools in the classroom The ethical considerations and defining the line between acceptable assistance and cheating Khan Academy's flipped classroom model and the benefits of active, student-centered learning The value of one-on-one interactions with professors and oral exams Embracing new practices and technologies in education for improved learning experiences Promotion: Learn about watermarking AI text to detect plagiarism in another podcast episode (https://soundcloud.com/beatrice-wright-820907561/watermarking-text-and-the-battle-against-false-accusations?si=d7550e5e7bff49c6b3e568d462839180&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing) Additional Notes: Original Reddit post: https://www.reddit.com/r/ChatGPT/comments/13isibz/texas_am_commerce_professor_fails_entire_class_of/ Rolling Stone Version: https://www.rollingstone.com/culture/culture-features/texas-am-chatgpt-ai-professor-flunks-students-false-claims-1234736601/ ESL students correctly accused: https://www.reddit.com/r/Professors/comments/11z7fme/just_failed_15_students_for_cheating_with_chatgpt/ Sounds by Pixabay

    20 min
  3. False AI cheating accusations and watermarking Artificial Intelligence output

    05/12/2023

    False AI cheating accusations and watermarking Artificial Intelligence output

    We explore the intriguing topic of watermarking text and its role in combating false accusations related to AI-generated content. We address concerns about the inadequate detection of AI-generated text and the harm caused to those wrongly accused. We discuss the concept of watermarking as a potential solution, where information is hidden within the text itself through steganography techniques. We highlight how they can be seamlessly integrated into the fabric of the text without significantly affecting its quality. While acknowledging the cleverness of watermarking techniques, we also examine the limitations and potential flaws. We emphasize that watermarking alone may not be foolproof, as individuals determined to evade detection can find ways to bypass or distort the watermarked text. Exploring the role of AI models in text generation, we provide a brief overview of how these models use context clues to predict the likelihood of each word. We explain how certain phrases can be identified as "AI two word phrases" and consistently included in the generated text, serving as a watermark that indicates AI involvement. Considering the threat model, we discuss the specific groups at risk, such as students, writers avoiding AI content penalties, and job applicants concerned about flagged documents. However, we also acknowledge that watermarking is not infallible, highlighting weaknesses such as distortions that can be easily reversed or creative techniques employed by individuals to circumvent detection. We draw attention to the battle between engineers striving to improve detection systems and the resourcefulness of teenagers and other motivated individuals who may find ways to crack the watermarking techniques. The whitepaper: https://arxiv.org/pdf/2301.10226v2.pdf Sound Effect by Pixabay

    7 min

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AI reader podcast brining you the best in philosophy, ideas and news from the Artificial Intelligence world