Apparently there are several narratives in regards to AI girlfriends.

  1. Incels use AI girlfriends given that they can do whatever they desire.
  2. Forums observing incel spaces agree that incels should use AI girlfriends to leave real women alone
  3. The general public having concerns towards AI girlfriends because their users might be negatively impacted by their usage
  4. Incels perceiving this as a revenge fantasy because “women are jealous that they’re dating AI instead of them”
  5. Forums observing incel spaces unsure if the views against AI girlfriends exist in the first place due to their previous agreement

I think this is an example of miscommunication and how different groups of people have different opinions depending on what they’ve seen online. Perhaps the incel-observing forums know that many of the incels have passed the point of no return, so AI girlfriends would help them, while the general public perceive the dangers of AI girlfriends based on their impact towards a broader demographic, hence the broad disapproval of AI girlfriends.

  • Tull_Pantera@lemmy.today
    1·
    4 months ago

    FOR YOUR CONSIDERATION

    1. Andrew Ng: Exponential Growth, 10 years - Advocates for rapid advancements in machine learning and AI capabilities.
    2. Fei-Fei Li: Exponential Growth, 8 years - Focuses on human-centered AI, expecting significant advancements in AI understanding human contexts.
    3. Andrej Karpathy: Exponential Growth, 12 years - Known for his work on deep learning and neural networks, predicts rapid advancements.
    4. Demis Hassabis: Exponential Growth, 15 years - As a founder of DeepMind, foresees long-term growth in AI capabilities.
    5. Ian Goodfellow: Logarithmic Growth, 10 years - Known for inventing GANs, sees growth but anticipates it slowing as challenges increase.
    6. Yann LeCun: Exponential Growth, 10 years - Emphasizes the potential of AI to continue growing rapidly.
    7. Jeremy Howard: Exponential Growth, 8 years - Enthusiastic about fast AI advancements especially in medical fields.
    8. Ruslan Salakhutdinov: Exponential Growth, 10 years - Focuses on deep learning and AI research, predicts substantial growth.
    9. Geoffrey Hinton: Exponential Growth, 12 years - A pioneer in neural networks, predicts sustained rapid growth.
    10. Alex Smola: Logarithmic Growth, 8 years - Sees significant improvements initially, with diminishing returns over time.
    11. Rana el Kaliouby: Exponential Growth, 7 years - Believes in AI’s ability to understand human emotions, driving rapid advancements.
    12. Daphne Koller: Logarithmic Growth, 9 years - Expects AI growth but with practical and ethical constraints limiting pace.
    13. Yoshua Bengio: Exponential Growth, 12 years - One of the pioneers of deep learning, optimistic about AI’s future.
    14. Sam Altman: Exponential Growth, 15 years - As CEO of OpenAI, highly optimistic about the future capabilities of AI.
    15. Clara Shih: Exponential Growth, 8 years - Expects AI to revolutionize customer engagement rapidly.
    16. Aidan Gomez: Logarithmic Growth, 7 years - Recognizes initial rapid advances, expects plateau due to computational and theoretical limits.
    17. Gary Marcus: S-curve Growth, 5 years - Skeptical about unbounded AI growth, sees a leveling off as limitations are hit.
    18. Joy Buolamwini: Logarithmic Growth, 5 years - Concerned about bias in AI, predicts growth tempered by the need for ethical frameworks.
    19. Jon Krohn: Exponential Growth, 10 years - Believes in continuous improvements in AI learning capabilities.
    20. Alondra Nelson: Logarithmic Growth, 6 years - Views growth through a sociological lens, expecting societal factors to influence the rate of AI adoption.
    21. Mustafa Suleyman: Exponential Growth, 12 years - Sees long-term potential in integrating AI in societal solutions.
    22. Jaron Lanier: S-curve Growth, 8 years - Critiques certain aspects of technology but acknowledges periods of significant innovation.
    23. Marc Andreessen: Exponential Growth, 15 years - Very bullish on technology including AI, expects revolutionary changes.
    24. Eliezer Yudkowsky: Exponential Growth, indefinite - Believes in the transformative potential of AI, possibly leading to superintelligence.
    25. Michèle Flournoy: Logarithmic Growth, 8 years - Expects significant advancements in AI for defense but sees regulatory and ethical challenges.
    26. Zeynep Tufekci: Logarithmic Growth, 7 years - Concerns about social implications and challenges may slow down the pace of acceptance and implementation.
    27. Kai-Fu Lee: Exponential Growth, 12 years - Enthusiastic about AI’s impact on society, particularly in China.
    28. Daron Acemoglu: S-curve Growth, 10 years - Believes in significant growth followed by a plateau as economic factors weigh in.
    29. Andrew Imbrie: Logarithmic Growth, 8 years - Foresees growth moderated by policy and strategic considerations.
    30. Safiya Noble: Logarithmic Growth, 6 years - Focuses on the impact of AI on public information and ethics, seeing these as limiting factors.
    31. Micheal Chui: Exponential Growth, 10 years - Optimistic about AI transforming businesses and the economy.
    32. Larry Page: Exponential Growth, indefinite - As a founder of Google, foresees limitless potential in AI advancements.
    33. Elon Musk: S-curve Growth, 7 years - Sees rapid growth followed by significant risks and challenges.
    34. Dario Amodei: Exponential Growth, 12 years - Focuses on advancing AI safely, sees continued rapid improvements.
    35. Bill Gates: Exponential Growth, 10 years - Generally optimistic about technology’s ability to solve big problems.
    36. Reid Hoffman: Exponential Growth, 12 years - Sees AI as a crucial part of the future economy.
    37. Satya Nadella: Exponential Growth, 12 years - Emphasizes AI integration in cloud computing and business solutions.
    38. Peter Thiel: S-curve Growth, 10 years - Believes in strong initial growth, followed by potential stagnation as monopolistic practices set in.
    39. Mark Zuckerberg: Exponential Growth, indefinite - Strong proponent of integrating AI in social platforms.
    40. Swami Sivasubramanian: Exponential Growth, 10 years - Expects cloud and AI technologies to merge and grow rapidly.
    41. Susan Gonzales: Logarithmic Growth, 7 years - Advocates for inclusive AI but sees social barriers.
    42. Reggie Townsend: Logarithraphic Growth, 8 years - Focuses on privacy and data protection, which may temper AI adoption rates.
    43. Miriam Vogel: Logarithmic Growth, 6 years - Concerned with ethical AI, predicts a moderated growth due to regulatory frameworks.
    44. Sundar Pichai: Exponential Growth, 12 years - Believes in the profound impact of AI on all Google’s products and services.
    45. Sissie Hsiao: Exponential Growth, 10 years - Anticipates AI will continue to revolutionize communication apps.
    46. James Manyika: Logarithmic Growth, 10 years - Sees transformative potential but cautions about socio-economic impacts.
    47. Dr Milly Zimeta: Logarithmic Growth, 7 years - Focuses on AI ethics, sees growth influenced by ethical considerations.
    48. Peggy Hicks: Logarithmic Growth, 8 years - Highlights human rights concerns, which could influence the rate of AI development.
    49. Dame Wendy Hall: Logarithmic Growth, 10 years - Emphasizes the importance of governance in AI, which might slow growth.
    50. Carl Miller: S-curve Growth, 8 years - Studies the impact of digital technology on society, anticipates rapid growth followed by stability.

    Synthesized Consensus

    Exponential Growth (25+ individuals): Most expect rapid, continued growth over the next 8-15 years, often linked to advancements in technology and AI’s integration into various sectors.

    Logarithmic Growth (17+ individuals): Many foresee significant early advancements that will gradually plateau, influenced by ethical, societal, and practical challenges.

    S-curve Growth (8 individuals): A few predict periods of rapid innovation followed by a stabilization as AI reaches maturity or encounters insurmountable hurdles.

    Given the various perspectives offered by the panel on the initial phase of AI growth, let’s extend the reasoning to speculate about what might happen beyond the next 8-15 years:

    Those predicting Exponential Growth (indefinite), like Larry Page, Elon Musk, and Mark Zuckerberg, might suggest that AI growth could continue to escalate without a foreseeable plateau. They likely envision ongoing, transformative innovations that continuously push the boundaries of AI capabilities.

    Those foreseeing Exponential Growth for a finite period (e.g., Andrew Ng, Yann LeCun, Demis Hassabis) might anticipate a shift after the initial rapid growth phase. After the high-growth years, they might predict a transition to a slower, more sustainable growth pattern or a plateau as the AI industry matures and technological advancements face diminishing returns or run up against theoretical and practical limitations.

    Proponents of Logarithmic Growth, like Ian Goodfellow, Daphne Koller, and Safiya Noble, generally expect growth to slow and eventually plateau. Post the initial period of significant advancements, they might predict that the AI field will stabilize, focusing more on refinement and integration rather than groundbreaking innovations. Ethical, regulatory, and societal constraints could increasingly play a role in moderating the speed of development.

    Advocates of S-curve Growth, such as Gary Marcus and Peter Thiel, typically envision that after a period of rapid innovation, growth will not only plateau but could potentially decline if new disruptive innovations do not emerge. They might see the field settling into a phase where AI technology becomes a standard part of the technological landscape, with incremental improvements rather than revolutionary changes.

    Special Considerations: Visionaries like Eliezer Yudkowsky, who speculate about AI reaching superintelligence levels, might argue that post-15 years, the landscape could be radically different, potentially dominated by new AI paradigms or even AI surpassing human intelligence in many areas, which could either lead to a new phase of explosive growth or require significant new governance frameworks to manage the implications.

    Overall, the panel’s consensus beyond the next 8-15 years would likely reflect a mixture of continued growth at a moderated pace, potential plateaus as practical limits are reached, and a landscape increasingly shaped by ethical, societal, and regulatory considerations. Some may also entertain the possibility of a decline if no new significant innovations emerge.