Generative AI and Deepfakes: Ethical Issues and Detection Techniques | BCS London Branches
Science & Technology
Introduction
Hello and welcome to another insightful session hosted by the BCS London Branches on Generative AI, Deepfakes, Ethical Issues, and Detection Techniques.
Introduction
Hello and welcome at the end of another sizzling week in the UK's TD summer. A few days of sunshine welcome us to another insightful session on AI, deep fakes, ethics, and cybersecurity. Hosted and moderated by Dr. Hisham Abug from the University of East London, today's panel features four distinguished experts from East and West London Universities.
Panel Introduction
Our moderator, Dr. Hisham Abug, invites the panelists to share their insights. These panelists are Professor Julie W, Dr. S Sharif, Dr. F Saf, and Dr. Mustansar.
Topic Overview
Today's session dives deep into generative AI and deep fakes, particularly focusing on ethical issues and detection techniques. Dr. S Sharif kicks off the discussion.
Dr. S Sharif's Perspective
Dr. S Sharif emphasizes the dual-edged nature of AI. While AI has numerous beneficial applications in art, creativity, and healthcare, it also poses risks like misinformation and invasion of privacy. He highlights the importance of policies and strategies, mentioning ongoing efforts in coordination and regulation to control AI misuse. Dr. Sharif wraps up his presentation with an emphasis on educating the public about AI and ensuring its positive societal impact.
Professor Julie's Insights
Professor Julie takes over, offering perspectives on deep fake speech and its impact on privacy, misinformation, disinformation, and mental health. She also discusses detection methods from traditional machine learning techniques to advanced authentication methods. Julie stresses that effective countermeasures require a holistic approach, integrating technology, education, and robust controls.
Dr. Fat's Contributions
Dr. Fat explores the intersection of fake news, social media, and deep fakes. He shares insights on the evolution of social media tactics from text and image verification to combating deep fakes. He mentions the importance of educating the public and the role of third-party fact-checkers in filtering out fake content.
Dr. Mustansar's Session
Dr. Mustansar delves into the technology behind generative AI and deep fakes, highlighting its massive impact on politics and society. He showcases examples of deep fakes and emphasizes the challenges in terms of bias, ethical concerns, and the need for regulatory frameworks. He applauds efforts by companies like Meta and Google, but also stresses the need for broader legislative measures.
Questions and Discussions
Several pertinent questions arise, covering topics like voice biometrics, misinformation, deep fake countermeasures, and blockchain technology. The panelists offer varied perspectives, underscoring the importance of collective action in combating AI misuse.
Conclusion
Dr. Hisham wraps up the event, expressing a wish for continued discussions on this critical topic.
Final Thoughts
Dalim, representing BCS, emphasizes the importance of staying abreast with the rapidly evolving technology landscape. He invites participants to explore further learning opportunities about Ethics in AI.
Keywords
- Generative AI
- Deepfakes
- Ethical Issues
- Detection Techniques
- Misinformation
- Disinformation
- Voice Biometrics
- Blockchain
- Social Media
- AI Literacy
- Regulatory Frameworks
FAQ
What is generative AI and how does it relate to deep fakes?
- Generative AI refers to algorithms capable of creating new content similar to existing data, such as text, images, and audio. Deep fakes are a manifestation of generative AI, primarily in audio and video forms, used often for unethical purposes like misinformation.
What are the primary concerns about deep fakes?
- The primary concerns are privacy violations, spreading misinformation, disinformation, and the psychological impact on individuals.
What detection techniques are effective against deep fakes?
- Detection methods include deep learning and machine learning models, voice biometrics, spectrogram analysis, and advanced authentication techniques like blockchain technology.
How can social media platforms help in combating deep fakes?
- Social media platforms can implement AI tools for detecting fake content, use third-party fact-checkers, and set stringent policies on AI-generated political advertisements.
What are the ethical implications of generative AI?
- Ethical implications include potential bias in AI outputs, misuse for spreading false information, and privacy issues. The need for robust regulatory frameworks is critical.
Are there legislative measures to curb the misuse of deep fakes?
- Yes, there are evolving legislative measures like the EU's AI Act and various state regulations in the USA aimed at curbing misuse, especially in political contexts.
For any further questions or detailed insights, feel free to reach out to the panelists or explore the BCS courses on Ethics and AI.