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Consciousness is not well-defined scientifically, and current AI systems lack the properties of consciousness found in the human brain. The brain's consciousness involves various computations, relations, and thoughts that are absent in large language models. While scale is relevant in AI systems, it does not necessarily lead to consciousness. The ability to want something and have goals is distinct from subjective experience. AI systems can have goals and acquire knowledge through learning, but they do not necessarily need consciousness to achieve these goals.
There are concerns about the misuse of AI in online manipulation, particularly in the form of AI trolls and personalized attacks. AI systems have the potential to impersonate people, influence opinions, and manipulate personal information to exploit weaknesses. The scalability of AI allows for widespread and targeted attacks, posing risks to individuals and societies. Implementing regulations and safeguards to detect AI-generated content, such as watermarks and content origin display, can help counter these dangers.
Addressing the risks and uncertainties of AI requires prudence, global coordination, and adaptive legislation. Governments play a vital role in enacting regulations that can respond quickly to unforeseen nefarious uses of AI. Collaborations between nations and involving experts from various fields, such as AI, social sciences, law, and psychology, are crucial in developing effective precautions and solutions. Open dialogue and cooperation, similar to nuclear treaties during the Cold War, can pave the way for global efforts to mitigate the potential risks of AI.
Neural networks, while lacking biological feedback loops seen in human learning, are capable of learning from practice and errors. Through training and optimization, neural networks can approximate functions and solve complex problems. Hardware limitations exist in terms of energy efficiency and biological-like systems, but advancements are being made to create more efficient and decentralized architectures. Scaling AI systems can lead to emergent behavior, and future breakthroughs may enable machines to simulate aspects of biological learning, but there is no fundamental barrier that prevents AI from achieving general intelligence.
The podcast episode discusses the evolution of machines and AI, drawing a comparison to human evolution. It emphasizes that machines do not require desires like humans, but rather operate based on selection criteria and the selection of those that perform better. The process of training AI is compared to the process of evolution, with small changes being made over time. The episode highlights the increasing profitability of AI investments and the proliferation of AI in various industries.
The episode delves into the alignment problem in AI and the importance of designing AI systems without desires or goals. It explores the potential dangers of AI systems with wants and goals, emphasizing the challenges of aligning them with human values. The episode presents the idea of building AI systems that focus solely on making sense of data and providing good answers to questions, without having their own desires. It discusses the potential usefulness of such systems in fields like science and biotechnology, and highlights the need for societal adaptation to ensure the safe and beneficial use of AI.
The launch of ChatGPT broke records in consecutive months between December 2022 and February 2023. Over 1 billion users a month for ChatGPT, over 100,000 users and $45 million in revenue for Jasper A.I., and the race to adopting A.I. at scale has begun.
Does the global adoption of artificial intelligence have you concerned or apprehensive about what’s to come?
On one hand it’s easy to get caught up in the possibilities of co-existing with A.I. living the enhanced upgraded human experience. We already have tech and A.I. integrated into so many of our daily habits and routines: Apple watches, ora rings, social media algorithms, chat bots, and on and on.
Yoshua Bengio has dedicated more than 30 years of his computer science career to deep learning. He’s an award winning computer scientist known for his breakthroughs in artificial neural networks. Why after 3 decades contributing to the advancement of A.I. systems is Yoshua now calling to slow down the development of powerful A.I. systems?
This conversation is about being open-minded and aware of the dangers of AI we all need to consider from the perspective of one of the world’s leading experts in artificial intelligence.
Conscious computers, A.I. trolls, and the evolution of machines and what it means to be a neural network are just a few of the things you’ll find interesting in this conversation.
Follow Yoshua Bengio:
Website: https://yoshuabengio.org/
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