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Dr. Shiva, inventor of email, discusses artificial intelligence with Mike Adams

Dr. Shiva joins Mike Adams and Todd Pittenger to discuss the implications of Artificial Intelligence (AI) on society. Dr. Shiva expresses concern over the current trajectory of AI, which is dominated by large companies, including Microsoft, Google, IBM, Facebook and Meta, which operate closed systems. These AI systems may have built-in prejudices that are put there to advance the companies ' agenda, and that do not necessarily mirror reality.

Dr. Shiva highlights the need for people to understand what artificial intelligence really is, emphasizing its three main components: hardware, software, and the data that drives it. He also discusses the importance of decentralization, using the presidential campaign as an example, where volunteers collect signatures in a grassroots effort rather than a centralized approach taken by elites. Dr. Shiva's intentions are to educate people about AI and the dangers of top-down, centralized AI systems controlled by large corporations

Dr. SHIVA discusses the trajectory of technology and the potential consequences of relying on large conglomerates to control it. He uses the example of e-mail, which started as a decentralized system, but was eventually centralized by a few large companies. Dr. SHIVA expresses concern about lawmakers ' lack of understanding of technology and their inability to implement effective policies. He also discusses his role in the invention of email and the transition from a complex, on-premises system to a consumer application, which paved the way for KI to become necessary. Dr. SHIVA has been involved in both email and the KI field and emphasizes the importance of understanding these technologies and who controls them to create the world we want.

In the late 1990s when email usage surpassed snail mail, marking a crossroads in the development of artificial intelligence (AI). At the time, Dr. Ayyadurai was working on his PhD in information cybernetics at MIT, focusing on pattern recognition which is the foundation of AI. He noted that various scientific fields were independently developing pattern recognition algorithms, such as in cardiology, non-destructive evaluation, and face analysis.

These algorithms relied on three fundamental processes: feature extraction, clustering, and learning. Feature extraction involves recognizing key features of patterns, clustering groups similar patterns, and learning from experiences to improve pattern recognition. Dr. Ayyadurai drew an analogy to human evolution, suggesting that our ability to recognize patterns and make decisions based on them was crucial to our survival and evolution. Since the 1960s and 1970s, these processes have been the foundation of AI and its development has continued to progress.

Dr. SHIVA discusses how AI learns from human experts and the implications of who owns the training data. He uses the example of a cytologist analyzing cells under a microscope to make a decision about whether a cell is cancerous or not. The cytologist categories cells and is trained by a higher-level person (pathologist). AI systems observe and learn from the cytologists' decisions, which is called training data, but the ownership of this data is a policy question.

The training data was once in the cytologist's mind but is now owned by a large centralized company. The cytologist could potentially be replaced by a virtual cytologist, and the deep concern lies in who owns the training data. Dr. SHIVA notes that people interacting with large platforms, like social media, inadvertently offer training data for AI systems, ultimately replacing themselves for various job functions, such as creative writing, behavior analysis, or image analysis. He also emphasizes that the US Congress has created backdoor portals to every social media company under CISA, allowing them to surveil and censor US citizens, violating the First Amendment. Watch the attached video to catch up on the rest of the discussion. Watch the attached video to catch the rest of the discussion.