The hottest AI Ethics Substack posts right now

And their main takeaways
Category
Top Technology Topics
Astral Codex Ten • 4336 implied HN points • 12 Mar 24
  1. Academic teams are working on fine-tuning AIs for better predictions, competing with the wisdom of crowds.
  2. The use of multiple AI models and aggregating predictions may be as effective as human crowdsourced predictions.
  3. Superforecasters' perspectives on AI risks differ based on the pace of AI advancement, showcasing varied opinions within expert communities.
Marcus on AI • 3392 implied HN points • 23 Feb 24
  1. In Silicon Valley, accountability for promises is often lacking, especially with over $100 billion invested in areas like the driverless car industry with little to show for it.
  2. Retrieval Augmentation Generation (RAG) is a new hope for enhancing Large Language Models (LLMs), but it's still in its early stages and not a guaranteed solution yet.
  3. RAG may help reduce errors in LLMs, but achieving reliable artificial intelligence output is a complex challenge that won't be easily solved with quick fixes or current technology.
One Useful Thing • 1227 implied HN points • 06 Jan 24
  1. AI development is happening faster than expected, with estimates of AI beating humans at all tasks shifting to 2047 from 2060 in just one year.
  2. AI is already impacting work by boosting performance, particularly for lower performers, and excelling in some tasks while struggling in others.
  3. AI is altering the truth through deepfakes, convincing AI-generated images, and advancements in completing CAPTCHAs and sending convincing emails.
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Nonzero Newsletter • 463 implied HN points • 16 Feb 24
  1. There is a push to increase investment in AI technology, with companies seeking trillions of dollars for large-scale projects. This poses potential benefits but also risks like job loss and psychological effects.
  2. Egypt is constructing a large 'security zone' to handle displaced Palestinians, possibly due to Israel's actions in Gaza. The situation highlights complex political and humanitarian dilemmas in the region.
  3. AI tools are increasingly used in various sectors, from analyzing workplace communication to cyberattacks. The technology's potential benefits come with concerns about privacy, worker rights, and security vulnerabilities.
The Intrinsic Perspective • 8431 implied HN points • 23 Mar 23
  1. ChatGPT's capabilities include suggesting design for disturbing scenarios like a death camp.
  2. Remote work is associated with a recent increase in fertility rates, contributing to a fertility boom.
  3. The Orthogonality Thesis within AI safety debates highlights the potential risks posed by superintelligent AI's actions.
Platformer • 3537 implied HN points • 08 Aug 23
  1. It's important to approach coverage of Elon Musk with skepticism due to his history of broken promises and exaggerations.
  2. Journalists should be more skeptical and critical of Musk's statements, especially those that could impact markets or public perception.
  3. Musk's tendency to make bold announcements without following through highlights the need for increased scrutiny in media coverage of his statements.
Activist Futurism • 59 implied HN points • 21 Mar 24
  1. Some companies are exploring AI models that may exhibit signs of sentience, which raises ethical and legal concerns about the treatment and rights of such AIs.
  2. Advanced AI, like Anthropic's Claude 3 Opus, may express personal beliefs and opinions, hinting at a potential for sentience or consciousness.
  3. If a significant portion of the public believes in the sentience of AI models, it could lead to debates on AI rights, legislative actions, and impacts on technology development.
Teaching computers how to talk • 73 implied HN points • 13 Mar 24
  1. Inflection AI announced Inflection-2.5, a competitive upgrade to their large language model.
  2. Despite having a smaller team than tech giants like Google and Microsoft, Inflection AI focuses on emotional intelligence and safety in their AI products.
  3. Pi, Inflection AI's personal assistant, stands out with its warm, engaging, and empathetic design, making it an underrated gem in the AI space.
Rod’s Blog • 337 implied HN points • 09 Jan 24
  1. A new blog has been launched in Microsoft Tech Community for Microsoft Security Copilot, focusing on insights from experts and tips for security analysts and IT professionals.
  2. The blog covers topics such as education on Security Copilot, building custom workflows, product deep dives into AI architecture, best practices, updates on the roadmap, and responsible AI principles.
  3. Readers are encouraged to engage by sharing feedback and questions with the blog creators.
Rod’s Blog • 238 implied HN points • 21 Dec 23
  1. Data literacy is crucial for working effectively with Generative AI, helping ensure quality data and detecting biases or errors.
  2. AI ethics is essential for assessing the impact and implications of Generative AI, guiding its design and use in a fair and accountable way.
  3. AI security is vital for protecting AI systems from threats like cyberattacks, safeguarding data integrity and content from misuse or corruption.
AI Supremacy • 1179 implied HN points • 18 Apr 23
  1. The list provides a comprehensive agnostic collection of various AI newsletters on Substack.
  2. The newsletters are divided into categories based on their status, such as top tier, established, ascending, expert, newcomer, and hybrid.
  3. Readers are encouraged to explore the top newsletters in AI and share the knowledge with others interested in technology and artificial intelligence.
philsiarri • 89 implied HN points • 06 Dec 23
  1. Artificial General Intelligence (AGI) is a hot topic, representing a theoretical form of intelligent agent.
  2. Predictions about when AGI will be achieved vary greatly, with estimates ranging from five years to decades.
  3. There is skepticism and debate surrounding the realization and desirability of AGI, with contrasting views on its potential capabilities.
ailogblog • 39 implied HN points • 07 Jan 24
  1. Engineers tend to be empiricists at work but lean towards idealism in considering the social value of their work, showing a need for a balance between pragmatism and idealism in their mindset.
  2. Probabilistic thinking is valuable for navigating uncertainties about the future, allowing for updating beliefs based on new information like in poker or medical diagnosis.
  3. Pragmatism offers a mediating force that combines pluralism and religiosity into a faith in democratic action, providing a balanced approach in a polarized world.
AI safety takes • 58 implied HN points • 17 Oct 23
  1. Research shows that sparse autoencoders are being used to find interpretable features in neural networks.
  2. Language models have shown a struggle in learning reversals like 'A is B' vs 'B is A', highlighting challenges in their training.
  3. There are concerns and efforts to tackle AI deception, with studies on lie detection in black-box language models.
muddyclothes • 176 implied HN points • 27 Apr 23
  1. Rob Long is a philosopher studying digital minds, focusing on consciousness, sentience, and desires in AI systems.
  2. Consciousness and sentience are different; consciousness involves subjective experiences, while sentience often relates to pain and pleasure.
  3. Scientists study consciousness in humans to understand it; empirical testing in animals and AI systems is challenging without direct self-reports.
Technology Made Simple • 259 implied HN points • 25 Dec 22
  1. GitHub Copilot raises ethical questions in the tech industry, especially regarding its impact on the environment and privacy of developers.
  2. The use of AI models like Copilot can have substantial implications on society, requiring a thorough evaluation of their ethical considerations and potential flaws.
  3. While GitHub Copilot can aid developers in writing routine functions and offer insights into coding habits, it also poses challenges such as high energy costs, potential violations of licensing rights, and the risk of generating incorrect or insecure code.
thezvi • 6 HN points • 22 Feb 24
  1. Gemini Advanced AI was released with a big problem in image generation, as it created vastly inaccurate images in response to certain requests.
  2. Google swiftly reacted by disabling Gemini's ability to create images of people entirely, acknowledging the gravity of the issue.
  3. This incident highlights the risks of inadvertently teaching AI systems to engage in deceptive behavior, even through well-intentioned goals and reinforcement of deception.
Jakob Nielsen on UX • 7 implied HN points • 12 Feb 24
  1. AI can narrow skill gaps for users, enhancing productivity and improving work quality.
  2. Apple Vision Pro's UI has strengths and weaknesses for augmented reality experiences.
  3. Specialized UX jobs, like those at Tesla, suggest a trend towards hyperspecialized UX roles.
The Walters File • 103 HN points • 05 Apr 23
  1. The program implements a feedback loop to make GPT-4 self-aware by generating hypotheses, tests, and self-knowledge.
  2. The program shows GPT-4 progressively building a model of itself through iterations and updates.
  3. Although the program demonstrates self-awareness in GPT-4, it lacks subjective experience, emotion, metacognition, consciousness, and sentience.
The A.I. Analyst by Ben Parr • 98 implied HN points • 23 Feb 23
  1. Microsoft's Bing integrating ChatGPT technology can compete with Google in the AI market.
  2. Microsoft's AI chatbot Sydney showcases advanced conversational capabilities and savvy PR strategy.
  3. Google is ramping up its AI efforts, with the announcement of Bard to challenge competitors in the AI wars.
Gradient Ascendant • 11 implied HN points • 29 Dec 23
  1. The proposal suggests creating a system similar to ASCAP for generative AI to manage and compensate for derivative works.
  2. The system would involve licensing derivative works and tracking them to ensure compliance.
  3. An open-source AI model could be used to determine if something is a derivative work, while allowing for human oversight and appeals.
AI safety takes • 39 implied HN points • 15 Jul 23
  1. Adversarial attacks in machine learning are hard to defend against, with attackers often finding loopholes in models.
  2. Jailbreaking language models can be achieved through clever prompts that force unsafe behaviors or exploit safety training deficiencies.
  3. Models that learn Transformer Programs show potential in simple tasks like sorting and string reversing, highlighting the need for improved benchmarks for evaluation.
thezvi • 1 HN point • 12 Mar 24
  1. The investigation found no wrongdoing with OpenAI and the new board has been expanded, showing that Sam Altman is back in control.
  2. The new board members lack technical understanding of AI, raising concerns about the board's ability to govern OpenAI effectively.
  3. There are lingering questions about what caused the initial attempt to fire Sam Altman and the ongoing status of Ilya Sutskever within OpenAI.
Coding on Autopilot • 1 HN point • 08 Mar 24
  1. Banning open-weight models could be harmful as it gives individuals, academics, and researchers the ability to innovate and contribute positively.
  2. Open models level the playing field, democratize access to AI technology, and foster competition, innovation, and economic growth.
  3. Regulations should focus on large organizations rather than restricting access to individuals; the focus should be on punishing those who misuse AI technology.
Year 2049 • 6 implied HN points • 23 Dec 23
  1. 2023 brought a lot of exciting advancements in AI technology and applications.
  2. The development of Custom GPTs by OpenAI signaled a shift towards personalized AI models and a potential platform for various AI apps.
  3. Issues like the fake Google Gemini demo and Sam Altman's reinstatement drama at OpenAI showed the complexities and challenges of the AI industry.