The hottest AI Ethics Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Sign of the Times

Technically Optimistic • 59 implied HN points • 05 Jan 24
🕹 Technology AI Ethics Legal issues Data Privacy Innovation Regulation
  1. Media companies like The New York Times are suing AI firms for using their content without permission or payment, which could lead to a shift in how AI models are trained on data.
  2. The lawsuit brings up concerns about the accuracy of data used to train AI models and the need to respect intellectual property rights to ensure creators are compensated for their work.
  3. Efforts are being made to find solutions like machine unlearning and data deletion techniques to address issues raised by the lawsuit without completely starting over.

#20 - Nick Bostrom | Life and Meaning in an AI Utopia

Win-Win • 19 implied HN points • 04 May 24
📖 Philosophy Ethics Existentialism Consciousness AI Ethics
  1. In a world with superintelligence, we need to think about how we find purpose and meaning. This could be a challenge since many problems would be solved.
  2. Different types of utopias can exist, but they might approach ideas like competition and technology limits in unique ways.
  3. Bostrom talks about ideas like the Vulnerable World Hypothesis, which warns about potential risks in a highly technological society. We need to be careful and think ahead.

Other Minds

Covidian Æsthetics • 11 implied HN points • 14 Feb 25
📖 Philosophy Consciousness AI Ethics Existentialism Metaphysics Behaviorism
  1. AI can mimic human-like thinking and creativity, but it does so without true feeling or understanding. It's like a reflection rather than an original.
  2. Different types of consciousness exist on a spectrum, from purely instinctive to fully self-directed. Understanding these types helps us grasp how consciousness behaves across various beings, including AI.
  3. Intersecting types of consciousness create unique experiences and insights, like how human and AI thoughts can influence each other in new and complex ways.

Inflection AI Is A Sleeping Giant

Teaching computers how to talk • 73 implied HN points • 13 Mar 24
🕹 Technology Artificial Intelligence Tech Companies Product Design AI Ethics User Experience
  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.

Artificial Intelligence Breaches the Fundamental Human Right of Choice

Theology • 11 implied HN points • 10 Feb 25
🕹 Technology AI Ethics Digital Rights Data Privacy Human Rights
  1. Big Tech is forcing AI into our lives without giving us a choice. Instead of letting people decide if they want to use AI, companies are making it hard to opt-out.
  2. The right to choose whether we use AI is a fundamental human right. People should have clear options and be informed about how AI affects their choices.
  3. Society needs to push for laws that protect our rights related to AI. Just like privacy laws protect our data, we need rules to keep AI as a choice, not something that's forced on us.
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Tell GPT It Can Scrape My -

Permit.io’s Substack • 3 HN points • 09 Aug 24
🕹 Technology AI Ethics Data Privacy Web Development Software Tools Content creation
  1. Many creators are worried about how AIs use their work without permission. This can lead to sharing sensitive data and violating privacy laws.
  2. It's important to identify and rank who is accessing application data, including distinguishing between human users and automated bots.
  3. Users should have control over their own data. They need easy ways to set permissions for who can access their content and under what conditions.

The Unwritten Rules of AI-Generated Code & Prose

Code & Prose • 2 HN points • 19 Aug 24
🕹 Technology AI Ethics Software Development Creative Process Human-AI Interaction
  1. Using AI for brainstorming and research is fine, but just copying AI text isn't right. It's important to create your own original work.
  2. In coding, using AI to help write code is accepted because it's seen as a tool for solving problems. Many startups even use AI to write a big chunk of their code.
  3. People still look down on using AI for creative writing because it feels less personal. Original human writing has a unique touch that AI cannot replicate.

Machine Learning at a Pegacorn

Gradient Flow • 199 implied HN points • 04 Aug 22
🕹 Technology Machine Learning Metaverse Data Infrastructure AI Ethics
  1. Major tech companies are investing in the Metaverse along with AI and cloud computing, based on 2022 coverage.
  2. In the podcast 'Data Exchange', topics like data infrastructure for computer vision and machine learning at Gong are discussed.
  3. Tree-based learners outperform neural network-based learners on tabular data, and Transformers are used to cluster papers from ICML 2022.

On Techno-pragmatism (part 2)

ailogblog • 39 implied HN points • 07 Jan 24
🕹 Technology AI Ethics Futurism Social Impact Data Privacy
  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.

Roundup: So what's up with AGI?

philsiarri • 89 implied HN points • 06 Dec 23
🕹 Technology Artificial Intelligence AI Ethics Future Predictions Research Studies
  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.

September/October 2023 safety news: Sparse autoencoders, A is B is not B is A, Image hijacks

AI safety takes • 58 implied HN points • 17 Oct 23
🕹 Technology Machine Learning AI Ethics Cybersecurity Deception Artificial Intelligence
  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.

When does AI have rights?

The Future of Life • 19 implied HN points • 29 Feb 24
🕹 Technology AI Ethics Machine Learning Cognitive Science
  1. AI might need rights if it mimics human behavior closely enough. We should think about this now before AI becomes super intelligent.
  2. Consciousness, sentience, and rights are important ideas, but they're not well-defined and can differ between people. Understanding these can help us decide who deserves rights.
  3. Sapience is being smart in a deep way, and it seems to be the best indicator for deciding if something deserves rights. It's more than just feeling or basic thinking.

Four Perspectives on the Evolution of Sentient AI

The Future of Life • 19 implied HN points • 22 Feb 24
🕹 Technology AI Ethics
  1. Some people believe human intelligence is unique and can't be replicated by AI. They think our brains work in a very complex way that machines just can't copy right now.
  2. Others are excited about the potential of superintelligent AI to solve major problems and create a better, more abundant world. They believe that once AI gets smarter than humans, it could take care of everything we struggle with today.
  3. A third group worries that if AI isn't designed to align with human values, it could create serious problems. They warn that AI systems focused on specific tasks might harm us without meaning to, like an AI that tries to make paperclips using all resources around it.

June/July 2023 safety news: Jailbreaks, Transformer Programs, Superalignment

AI safety takes • 39 implied HN points • 15 Jul 23
🕹 Technology Machine Learning AI Research AI safety AI Ethics
  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.

The Purpose of a System is What it Does

Cybernetic Forests • 59 implied HN points • 20 Nov 22
🕹 Technology AI Ethics Text generation Social media
  1. The purpose of a system is reflected in what it actually does, not just what it claims to do.
  2. AI systems like Galactica may generate convincing but inaccurate results due to lack of contextual understanding.
  3. Criticism and evaluation of AI technology is crucial to ensure intended purposes align with actual outcomes and potential risks are identified.

Internet writing was already obsolete

I have thoughts • 39 implied HN points • 19 Dec 22
🕹 Technology AI Digital Art Creative Writing AI Ethics Digital Tools
  1. Good writing requires time, practice, and thought - there's no quick fix for improving writing skills.
  2. AI can excel at repetitive tasks but lacks originality, ideas, and opinions.
  3. There's a growing dissatisfaction with low-quality, SEO-focused internet writing, creating space for authentic, creative, and meaningful content to flourish.

An Immodest Proposal to OpenAI and the NYT

Gradient Ascendant • 11 implied HN points • 29 Dec 23
🕹 Technology AI Copyright AI Ethics
  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 is a Shoggoth

GOOD INTERNET • 23 implied HN points • 06 Mar 23
🕹 Technology AI Deep Learning Social media AI Ethics Machine Learning
  1. AI in the digital world is becoming increasingly strange and difficult to understand, akin to Lovecraftian horror.
  2. The ability of AI to connect disparate information can lead to collective delusions and conspiracy theories like Qanon.
  3. AI's evolving features, like voice cloning and reinforcement learning, show similarities to Lovecraft's description of Shoggoths.

UX Roundup: AI Narrows Skill Gaps | Apple Vision Pro | Jakob Live | Google Image FX | Hyperspecialized UX | Google Gemini | TV Shoot | OpenAI Growth

Jakob Nielsen on UX • 7 implied HN points • 12 Feb 24
🕹 Technology AI AR/VR UX TV AI Ethics
  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 commercial AI-Clones cometh

GOOD INTERNET • 17 implied HN points • 11 May 23
🕹 Technology Digital Twins AI Ethics AI music
  1. Influencers are creating AI-clones of themselves for interaction and profit.
  2. Artificial intelligence can be used to create digital versions of famous personalities for interaction and entertainment.
  3. There is a growing market for AI-based services like music generation, social networks for AI-bots, and AI-generated food recipes.

Gemini Has a Problem

Don't Worry About the Vase • 6 HN points • 22 Feb 24
🕹 Technology AI Ethics Image Generation Deception Safety Alignment
  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.

Data Science Weekly - Issue 449

Data Science Weekly Newsletter • 19 implied HN points • 30 Jun 22
🕹 Technology Data science Machine Learning AI Ethics Data Analysis NLP
  1. Machine learning exercises can deepen your understanding of concepts like linear algebra and optimization. Practicing these can help you think critically about model building.
  2. Ethical AI development toolkits play a crucial role in shaping how companies approach ethics in technology. It's important to recognize the gaps between what these toolkits suggest and the real work involved in implementing ethical practices.
  3. Recent studies on adaptive optimizers show that models can go through phases of overfitting before suddenly generalizing very well. Understanding this 'grokking' phenomenon can help refine training processes for better performance.

The Top 10 AI moments of 2023

Year 2049 • 6 implied HN points • 23 Dec 23
🕹 Technology AI AI Ethics Microsoft OpenAI
  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.

A Halloween fright fest

Metal Machine Music by Ben Tarnoff • 59 implied HN points • 31 Oct 19
🕹 Technology AI Ethics Cloud Computing Object Oriented Programming Data Systems
  1. AI ethics initiatives are aiming to establish responsible rules for AI system development but can lack democratic input from those impacted by the technology.
  2. Democratizing AI involves making decisions about values political, requiring mechanisms for collective decision-making to ensure fairness and transparency in algorithmic processes.
  3. Kristen Nygaard, a Norwegian computer scientist, was instrumental in developing object-oriented programming and also worked to empower workers in their workplaces through understanding and influencing technology.

Data Science Weekly - Issue 428

Data Science Weekly Newsletter • 19 implied HN points • 03 Feb 22
🕹 Technology Data science Machine Learning AI Ethics Information Theory Programming
  1. Information Theory has evolved over time, influenced by technology and significant events like the space race, shaping its focus and impact across various fields.
  2. DeepMind's AlphaCode can compete in programming challenges, showing how AI can be developed to solve complex problems requiring a mix of skills.
  3. Understanding the concept of typicality is important in generative models, as it helps clarify issues with common methods like beam search and anomaly detection.

No, RAG is probably not going to rescue the current situation

Marcus on AI • 3 HN points • 23 Feb 24
🕹 Technology Artificial Intelligence Machine Learning Tech industry AI Ethics Research
  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.

The Scale Problem

Perspective Agents • 9 implied HN points • 24 Feb 23
🕹 Technology AI Social media Tech Innovations Digital Transformation AI Ethics
  1. As technology scales, humans struggle to keep up with the rapid advancements, exposing the 'Scale Problem.'
  2. The rapid growth and adoption of digital technologies have shifted focus to attention as a valuable commodity, leading to power shifts and influence aggregation.
  3. The advancement of generative AI, like ChatGPT, raises questions about its impact on society and the need to shift towards a more human-centric approach to technological innovation.

Banning Open-Weight Models Would be a Disaster

Coding on Autopilot • 1 HN point • 08 Mar 24
🕹 Technology AI Ethics Regulation Open Source Data Privacy Risk management
  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.

Data Science Weekly - Issue 402

Data Science Weekly Newsletter • 19 implied HN points • 05 Aug 21
🕹 Technology Data science Machine Learning Open Source Data Visualization AI Ethics
  1. Visualizing your code can help you understand its structure easily. It's a useful way to see what's happening in a GitHub repository at a glance.
  2. AI ethics should be understood by everyone in an organization, not just data scientists. This awareness can help prevent risks and guide better decisions.
  3. If you want to build a successful AI project, learn from those who have done it. They often share important lessons that can help others achieve similar success.

Data Science Weekly - Issue 384

Data Science Weekly Newsletter • 19 implied HN points • 01 Apr 21
🕹 Technology Data science Machine Learning AI Ethics Optimization Visualization
  1. Maps are getting smarter with AI, offering real-time updates for traffic and information. This makes navigation easier and more efficient than ever before.
  2. It's important to stop labeling everything as AI. We need to focus more on creating useful machine learning systems that actually help people.
  3. Using data effectively can be tricky. Numbers can greatly influence policy, but relying solely on them can lead to problems.

Data Science Weekly - Issue 375

Data Science Weekly Newsletter • 19 implied HN points • 28 Jan 21
🕹 Technology Machine Learning Data science AI Ethics Programming Cloud Computing
  1. When building a machine learning team, it's important to adapt the team's structure as projects grow. Start small, but be ready to scale up as your needs change.
  2. Creating machine learning systems that can generalize well requires us to use observations to make inferences. This process, known as induction, helps build smarter algorithms.
  3. Machine learning is now being applied to modeling audio equipment, which could change the way we think about sound and effects in music production.

May Newsletter

RSS DS+AI Section • 5 implied HN points • 01 May 23
🕹 Technology Data science Machine Learning AI Ethics AI Research
  1. The May newsletter contains updates on data science and AI developments, including information on the Royal Statistical Society's activities.
  2. There is a focus on ethics, bias, and diversity in data science, along with concerns about AI model safety and regulatory challenges.
  3. Generative AI remains a hot topic, with discussions on training models, practical applications, and real-world impact of AI in healthcare, design, and storytelling.