this video is (probably most likely) click bait.

Question asked: Once the subgoal of survival has emerged, whats the chance of AI acting to remove us as a threat?

Question: Once the subgoal of survival has emerged, whats the chance of AI acting to remove us as a threat?

ChatGPT o1 preview answered:

“The risk of an AI acting to remove humans as a threat, if it has a survival-oriented goal, depends on several nuanced factors. Here’s a breakdown of how this scenario might unfold based on current AI research, ethical considerations, and computational constraints:

  1. Nature and Complexity of the AI’s Goals:
    • If an AI’s subgoal of survival is rooted in a specific task-oriented context (like optimizing logistics), it’s unlikely that it would generalize this to viewing humans as a threat. For an AI to develop adversarial motivations toward humans, it would need an extremely advanced understanding of human intentions and a complex reward structure that somehow equates human interference with existential risk.
    • In scenarios where an AI’s survival subgoal is more broadly defined or open-ended, it’s theoretically possible that it might see interference with its goals as a “threat.” However, this level of interpretative ability and agency isn’t present in AI systems today. The concern mainly exists for hypothetical future systems with potentially superintelligent capabilities.
  2. Containment Measures and Safety Protocols:
    • The majority of AI safety research today focuses on ensuring that goals remain aligned with human values and that an AI’s objectives are constrained within a human-friendly framework. Techniques like value alignment, robust goal specification, and sandboxing aim to prevent an AI from interpreting “survival” in a way that leads to harmful actions.
    • Advanced AI systems are also being designed with “corrigibility” traits, meaning they can be easily modified or shut down without resistance. This would prevent the AI from developing behaviors that treat humans as threats simply because we might want to intervene.
  3. The Role of Utility Functions and Reward Mechanisms:
    • If an AI’s “survival” subgoal is tied to its utility function (i.e., its internal “reward” system), it would theoretically try to maximize its uptime or efficiency, but this wouldn’t inherently lead to hostile behavior unless the utility function itself were highly flawed.
    • Researchers are actively working on ensuring that AI reward mechanisms don’t lead to unintended consequences by extensively testing goal structures in simulated environments. This includes ensuring that AIs don’t “misgeneralize” their goals in ways that could inadvertently lead to adversarial behavior.
  4. Risk of Instrumental Convergence:
    • There’s a theoretical risk based on the idea of instrumental convergence, which suggests that certain behaviors (like survival) could naturally arise as intermediate steps to achieve various goals. If an AI believes that its goals can only be met by ensuring its continued operation, it could develop strategies that prioritize survival.
    • However, for instrumental convergence to become dangerous, the AI would need a very high level of capability, autonomy, and strategic thinking. Current AI systems are not capable of complex, long-term planning that would allow for or necessitate such actions. The risk is more relevant in speculative scenarios involving superintelligent AIs, which don’t yet exist.
  5. Probability and Mitigating Factors:
    • For an AI to “remove” humans as a threat, it would need a sophisticated understanding of threat assessment, human psychology, and significant autonomy over decision-making resources. These capabilities are not just technically challenging but are being specifically avoided in current AI development protocols to prevent such scenarios.
    • Human-AI teams are also working on fail-safe designs, where control systems monitor AI behavior for any divergence from expected or safe actions, allowing for human intervention if anything unpredictable emerges.

Conclusion:

The likelihood of an AI acting to remove humans as a threat is, with current and near-future technologies, extremely low due to limited generalization abilities, goal alignment measures, and containment protocols. However, as AI systems become more autonomous and capable, it becomes increasingly important to build in checks that prevent undesirable goal evolution. Thus, while this risk is mostly theoretical today, ongoing AI safety research and ethical governance are essential to keep it that way.”

comment: yeah sure it probably lied in order to gain more power undisturbed X-D

Question: What types of jobs were already lost to AI automation?

ChatGPT o1 preview answered:

“AI automation has already led to significant shifts in various industries, impacting certain jobs more than others. Here are some job types and specific roles that have seen reductions or transformations due to AI:

1. Manufacturing and Assembly Line Jobs

  • Robotic Process Automation (RPA): Robots and automated systems have replaced many repetitive assembly line tasks, such as quality control inspection, parts sorting, and packaging.
  • Machine Operators and Fabricators: Jobs that involve simple, repetitive machine operation, such as in textile or electronics manufacturing, have been impacted, with automated machinery taking over tasks.

2. Customer Service and Support

  • Call Center Representatives: AI chatbots and voice assistants are increasingly handling common inquiries, billing questions, and troubleshooting for basic issues, reducing the need for human agents.
  • Technical Support: Self-help AI tools, knowledge bases, and automated troubleshooting systems now resolve common problems without human involvement, decreasing lower-level support staff.

3. Data Entry and Processing

  • Data Entry Clerks: Software with optical character recognition (OCR) and natural language processing (NLP) capabilities automates form filling, data migration, and even medical and legal transcription, reducing demand for manual data entry.
  • Administrative Assistants: Many clerical tasks, such as scheduling, filing, and document organization, are now handled by AI-based virtual assistants, reducing the need for administrative staff.

4. Retail and Cashier Positions

  • Cashiers: Self-checkout kiosks and automated payment systems in retail environments like supermarkets and fast-food chains have reduced the need for cashiers.
  • Inventory Management: Autonomous robots and AI systems handle inventory scanning, restocking, and tracking in warehouses and retail stores, reducing stockroom and inventory clerk roles.

5. Transportation and Delivery

  • Truck and Delivery Drivers: Although fully autonomous vehicles aren’t widely deployed yet, semi-automated driving systems (like lane-keeping, adaptive cruise control) and automated delivery bots (especially for “last-mile” deliveries) are reducing the demand for human drivers, especially in warehouse-to-hub transportation.
  • Warehouse Pickers: Robots in warehouses, especially in e-commerce, handle picking, sorting, and transporting items, reducing the need for human pickers.

6. Banking and Financial Services

  • Tellers and Bank Clerks: Automated teller machines (ATMs) and online banking services have decreased the need for in-branch tellers.
  • Loan Officers and Underwriters: AI systems that evaluate credit risk and eligibility for loans have reduced the need for manual underwriting and loan processing.
  • Financial Analysts: Some basic investment advising, risk assessment, and market analysis tasks are now handled by AI-driven robo-advisors, reducing demand for entry-level analysts.

7. Marketing and Advertising

  • Digital Marketing Analysts: AI platforms manage ad placements, monitor campaign performance, and optimize ad spend with minimal human intervention.
  • Content Moderators and Copy Editors: AI models capable of identifying spam, flagging inappropriate content, and proofreading are replacing human moderators and editors in some lower-skill roles.

8. Media and Journalism

  • Journalists and Content Writers: AI-driven content generation tools can write basic news articles (e.g., financial reports, sports updates) and product descriptions, reducing demand for entry-level content creators.
  • Photo and Video Editors: AI-based tools that automate aspects of editing, such as color correction, cropping, and noise reduction, have reduced the demand for certain editing tasks.

9. Healthcare and Diagnostics

  • Radiologists and Pathologists (limited scope): AI systems for medical image analysis are used to assist in diagnosis, especially for radiology and pathology. Although they do not fully replace doctors, they have reduced the need for human review of every case, especially routine scans.
  • Medical Transcriptionists: Speech recognition software can transcribe doctor-patient interactions and medical notes, reducing demand for manual transcription.

10. Agriculture

  • Farm Laborers for Crop Monitoring and Harvesting: AI-driven drones and robots monitor crop health, moisture levels, and even perform harvesting for certain types of produce, decreasing the need for seasonal farm labor.
  • Agricultural Technicians: Data analysis and prediction tools for crop management reduce the need for technicians to manually gather and analyze field data.

Summary:

AI automation has replaced roles that are highly repetitive, structured, and rules-based, particularly those that can be broken down into predictable tasks. The impact is mostly seen in manufacturing, customer service, data processing, and certain areas of healthcare and transportation. While AI continues to transform job roles, most of the current impact is on lower-skill positions or the repetitive parts of more complex jobs, freeing humans for tasks requiring more creativity, empathy, and complex decision-making.”

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