Podcast Summary
Why do chatbots hallucinate or produce false information?: Chatbots generate responses based on patterns they've learned, lacking a concept of knowledge or truth.
While chatbots like ChatGPT can generate human-like responses and even provide seemingly accurate information, they don't truly possess knowledge or understanding. Instead, they make statistical guesses based on patterns they've learned from vast amounts of data. Madeline Winter's question, inspired by a lawyer who used ChatGPT in court and was caught out by made-up case references, asked why chatbots hallucinate or produce false information instead of admitting they don't know. The answer lies in the nature of chatbots: they don't have a concept of knowledge or truth, only the ability to generate responses based on patterns. In the first half of this mailbag episode, Casey and Kevin tackle questions with definitive answers, while the second half delves into more complex ethical dilemmas.
Expressing AI confidence and reducing hallucinations: AI models need to express their confidence in answers and be grounded to reduce hallucinations. Training is energy-intensive, but ongoing usage is less significant compared to other energy-consuming activities.
There's a need for AI models to express their level of confidence in their answers. Current models often answer questions as if they are absolutely certain, leading to potential misinformation. The idea of adding a confidence indicator is a good solution to help users better understand the reliability of the model's responses. Additionally, while AI models can sometimes hallucinate or make up information, they also often provide accurate answers when given factual questions. Companies are exploring ways to ground AI models, connecting them to databases or authoritative bodies of knowledge to reduce hallucinations. Regarding the environmental impact of AI, the training process for these models is energy-intensive, requiring large amounts of computing power. However, the energy consumption mainly occurs during the training phase, and the ongoing energy usage to serve requests is less significant. Compared to other energy-consuming activities like Bitcoin mining or flying, the carbon footprint of AI is still a topic of debate and ongoing research.
The Environmental Impact of Chatbots: Chatbots have a smaller carbon footprint than other processing-intensive technologies due to energy consumption during training, and tech giants are committed to reducing their carbon emissions.
While training large AI models like those used in chatbots consumes significant amounts of energy, the environmental impact is not as severe as with other processing-intensive technologies such as crypto mining. For instance, training GPT-3 required approximately 1.3 gigawatt hours of electricity, equivalent to the annual consumption of 120 US homes. However, this energy consumption occurs during the training process and not every time a question is asked of the chatbot. Furthermore, tech giants like Google and Microsoft, which are major players in AI development, have pledged to be carbon neutral in their operations. Therefore, using chatbots does not necessitate a large carbon footprint. Another topic that has sparked interest is the ongoing improvement of AI chatbots. Some people wonder why we are so confident that these models will continue to get better. The answer lies in observing the past evolution of AI models. For instance, GPT-2 was an improvement over GPT-1, and GPT-4 was a significant leap forward compared to GPT-3. Moreover, advancements in AI do not require a new technological breakthrough. Instead, the models can be enhanced by increasing the amount of computing power dedicated to them. This is why GPT-4 is much more capable than GPT-3. Overall, the optimism surrounding AI stems from the consistent progress we have seen in the field.
The Future of AI Scaling and Investor Skepticism: CEOs may hope for roadblocks for regulation, but investors maintain skepticism and thoroughly evaluate potential investments, as the majority are expected to fail
While AI models have been following predictable scaling laws and continuing to improve exponentially, there's no guarantee they will do so indefinitely. Some CEOs even hope for a roadblock to allow for regulation and catch their breath. However, venture capitalists often take on risky investments and may not be overly concerned with seemingly off financial reports from unusual companies. It's important to remember that the vast majority of their investments are expected to fail. The notion that being on the Forbes 30 under 30 list is a predictor for dishonesty among entrepreneurs is a humorous but potentially inaccurate observation. Nonetheless, it's crucial for investors to maintain a healthy skepticism and thoroughly evaluate the companies they invest in.
Pressure to invest in hot deals and lack of accountability in VC industry: The VC industry's groupthink mentality and lack of accountability can lead to investing in potentially fraudulent or overvalued companies. The SEC is reportedly working on a rule that would allow limited partners to sue VC firms for negligence, and the current economic environment may be contributing to skepticism about the industry.
The venture capital industry's groupthink mentality and lack of accountability can lead to investing in potentially fraudulent or overvalued companies. This issue is not new and has been seen in cases like FTX and Theranos. The pressure to get into hot investments and the assumption that other investors have done their due diligence can result in VCs waiving contingencies and trusting the founders blindly. However, there are signs that this might change as the SEC is reportedly working on a rule that would allow limited partners to sue VC firms for negligence. Additionally, the trend of former tech industry workers joining VC firms and the current economic environment with low interest rates and too much money chasing too few ideas, add to the skepticism of the current state of VC. It might be worth considering if this industry is in a bubble that could eventually burst.
The Reality of Venture Capital: The VC industry can be challenging and not all VCs are successful. Gaining operational experience before becoming a VC can add value to entrepreneurs.
The venture capital industry may not be as glamorous or successful as it appears on the surface. Many VCs leave the industry quietly after failing to produce successful investments. Some seem more focused on social media presence than actual job performance. New graduates are encouraged to gain operational experience before becoming VCs to add value to entrepreneurs. The industry is also lopsided, with only a few top firms getting the best deal flow and achieving significant wealth and success. As for Meg's question, AI may one day be able to create alternate endings for movies based on audience preferences, but its impact on society's emotional understanding and confrontation is a complex issue that requires further exploration.
The Role of Technology in Altering Movie Endings: While technology allows for alternate movie endings, filmmakers may resist it as it could undermine artistic vision and emotional impact. Some viewers might welcome customization for sensitive content.
While technology may allow for alternate endings or less intense versions of movies and TV shows, it may not be embraced by filmmakers and artists who value the emotional impact and complete vision of their work. The discussion also touched upon the existence of fan fiction and interactive content, which already allows viewers to explore different outcomes. However, the idea of an AI-ified version of this technology, where viewers can change the ending of a movie at the press of a button, was met with skepticism, as it was seen as potentially undermining the artistic process and the emotional experience for the audience. The conversation also revealed that some individuals, who are sensitive to intense emotions or graphic content, would welcome such technology to customize their viewing experience. Overall, the debate highlighted the tension between artistic vision and viewer experience, and the potential role of technology in shaping the future of storytelling.
The Role of Accessibility in Tech and AI: AI can enhance accessibility, but clear communication about API changes and understanding AI's limitations are crucial for inclusive tech use.
Accessibility in tech is often overlooked but crucial for all users, including those with disabilities. Blind users, for instance, can process audio information at higher speeds than sighted individuals, making faster audio a beneficial accessibility feature. However, poor communication about changes to APIs can lead to accessibility issues for users relying on third-party tools. The potential of AI in enhancing accessibility is significant, with examples like Be My Eyes, which uses AI to help blind individuals navigate their surroundings. Regarding workplace etiquette, anonymously submitted, a listener asked about addressing a boss who uses ChatGPT to answer team questions, finding it unhelpful and alienating. This issue highlights the importance of clear communication and understanding the limitations of AI-generated content in professional settings.
Chatbots vs Human Interaction in the Workplace: Excessive use of chatbots in professional settings can hinder personal relationships and communication, potentially leading to confusion and misunderstandings. While chatbots have their uses, prioritizing human interaction is crucial for building trust and understanding in the workplace.
Relying excessively on chatbots like ChatGPT in a professional setting, especially when interacting with a boss, can create confusion and hinder the building of personal relationships. This behavior can come across as passive-aggressive and prevent employees from understanding their boss's thoughts and feelings. While chatbots can be useful tools, they should not replace human interaction and communication in the workplace. If an employee feels their boss's usage of chatbots is confusing or hindering their work, they may consider addressing the issue with their boss in a respectful and open manner. However, if the situation is untenable, finding a new job may be the best solution. In a separate matter, Karen asks about her curiosity in looking up her ex-partner online. While she may be over the relationship, it's important to consider the potential emotional impact and privacy concerns before engaging in such behavior. Ultimately, it's essential to evaluate whether these actions align with personal values and goals.
Checking an ex's LinkedIn anonymously and Cloning a deceased loved one's voice: Consider potential consequences before checking an ex's LinkedIn anonymously. Be sensitive when using AI technology to clone a deceased loved one's voice.
While checking up on an ex's social media anonymously, including LinkedIn, is a common practice, it's essential to consider the potential consequences. Although it's generally considered ethical, using LinkedIn to look up an ex may raise concerns if they receive notifications of your activity. Additionally, someone with only a LinkedIn account may be a good sign, as they likely aren't overly reliant on social media. Regarding another ethical dilemma, using AI voice generating technology to clone a deceased loved one's voice can be a sensitive issue. While it may provide comfort to some, it's essential to consider the potential emotional implications for the family and the ethical implications of creating a voice that isn't truly authentic. Ultimately, it's crucial to approach such situations with sensitivity and careful consideration.
Creating an audio book using loved one's voice: Using AI technology to create an audio book from a deceased loved one's recordings can be comforting for some, but should be approached with sensitivity and respect for family feelings.
Creating an audio book version of a deceased loved one's autobiography using their recorded voice is a feasible and potentially meaningful project, but it's important to consider the feelings and reactions of family members, especially if the late spouse is still alive. This was discussed in the context of using AI technology to generate a voice based on existing recordings. While some people may find comfort in such a project, others might find it creepy or off-putting. The example of Eugenia Kuba and her chatbot companion based on her friend's text messages was given as an illustration of how technology can help people cope with loss and continue to interact with their departed loved ones. Ultimately, it's essential to approach this kind of project with sensitivity and respect for the feelings of family members.
