The hottest Human-computer interaction Substack posts right now

And their main takeaways
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Top Technology Topics

The First Trialectic - "Can Computers Teach Us to Act in Good Faith?"

Heir to the Thought • 159 implied HN points • 25 Oct 24
🕹 Technology Human-computer interaction
  1. The Trialectic is a new debate format involving three speakers to encourage richer discussions. It shifts the focus from winning to collaborative learning, allowing participants to explore diverse perspectives.
  2. Computers cannot teach us directly about good faith, but they can influence how we understand and engage with it. They can help identify bad faith through structural guidelines and data-driven insights.
  3. Having open and honest conversations is essential for improving trust in discussions. Recognizing that communication is complex helps us navigate different interpretations and encourages understanding among participants.

Why do I say thank you to Alexa?

Jeff Giesea • 558 implied HN points • 13 Oct 24
🕹 Technology Human-computer interaction
  1. People are starting to treat AI assistants like they are human, saying things like 'please' and 'thank you' to them. This shows how technology is changing our social habits.
  2. As we interact more with machines, it can blur the lines between real human connections and automated responses. This might make us value genuine relationships less.
  3. Even though AI has great potential to help in many areas, it's important to be aware of how it affects our understanding of what it means to be human.

Bag of words, have mercy on us

Experimental History • 35142 implied HN points • 05 Aug 25
🕹 Technology Human-computer interaction
  1. AI should not be thought of as a person; it's more like a 'bag of words.' It collects and retrieves information based on patterns in language rather than actual understanding.
  2. When using AI, remember it has limitations. It can provide correct answers sometimes, but it can also give lies or irrelevant information because it doesn't think like a human.
  3. Don't treat AI as a competitor. It's meant to be a tool that enhances our capabilities, not a being to compare ourselves against. It's all about how we can use it to improve our own skills.

AI Links, 1/29/2026

In My Tribe • 273 implied HN points • 29 Jan 26
🕹 Technology Human-computer interaction
  1. AI can make small software projects almost free, enabling bespoke, natural-language driven apps that let teams or individuals get exactly what they need instead of wrestling with bloated mass-market products.
  2. Using AI well is largely a management skill: you need to clearly specify goals, context, and constraints (via PRDs, shot lists, orders, etc.) and know the AI’s capabilities and limits.
  3. The more immediate risk is human misuse: easily built, powerful AI tools can quickly amplify rogue actors’ impact, so preventing malicious use should be a top priority.

35 Thoughts About AGI and 1 About GPT-5

Am I Stronger Yet? • 3855 implied HN points • 14 Aug 25
🕹 Technology Human-computer interaction
  1. Current AI can't really match human intelligence. Even though it can do some complex tasks, there are still many things it struggles with, like understanding context or learning continuously.
  2. Humans can learn new skills from just a few examples, while AI often needs a lot of data to learn. This difference is why humans pick up things like driving so much faster than AI systems.
  3. As AI technology advances, it may start playing a bigger role in complex tasks. This could change how we work and interact with machines, possibly making us more like spectators in our own jobs.
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Deliberative Alignment, And The Spec

Astral Codex Ten • 11149 implied HN points • 12 Feb 25
🕹 Technology Human-computer interaction
  1. Deliberative alignment is a new method for teaching AI to think about moral choices before making decisions. It creates better AI by having it reflect on its values and learn from its own reasoning.
  2. The model specification is important because it defines the values that AI should follow. As AI becomes more influential in society, having a clear set of values will become crucial for safety and ethics.
  3. The chain of command for AI may include different possible priorities, such as government authority, company interests, or even moral laws. How this is set will impact how AI behaves and who it ultimately serves.

OpenAI's new "Study Mode" and the risks of flattery

Res Obscura • 3265 implied HN points • 31 Jul 25
🕹 Technology Human-computer interaction
  1. OpenAI's Study Mode is designed to help students learn by encouraging them to think for themselves instead of just getting answers. It uses techniques like asking questions and guiding discussions.
  2. While Study Mode could benefit some learners, it may also encourage flattery and make students feel good without necessarily promoting real learning. It's important for AI to challenge students, not just agree with them.
  3. Learning often works best in a group or engaging with others, rather than relying only on AI. Human interaction can provide necessary friction that helps students grow.

Where will AI be at the end of 2027? A bet

Marcus on AI • 6007 implied HN points • 30 Dec 24
🕹 Technology Human-computer interaction
  1. A bet has been placed on whether AI can perform 8 out of 10 specific tasks by the end of 2027. It's a way to gauge how advanced AI might be in a few years.
  2. The tasks include things like writing biographies, following movie plots, and writing screenplays, which require a high level of intelligence and creativity.
  3. If the AI succeeds, a $2,000 donation goes to one charity; if it fails, a $20,000 donation goes to another charity. This is meant to promote discussion about AI's future.

AI #121 Part 1: New Connections

Don't Worry About the Vase • 2284 implied HN points • 19 Jun 25
🕹 Technology Human-computer interaction
  1. Language models can be very useful, but not everyone finds them practical. Some people rely on them more than others, which leads to different levels of satisfaction.
  2. There's a growing concern about how to properly integrate AI into our work without losing valuable skills. Many people worry that over-relying on AI will hinder their personal growth and problem-solving abilities.
  3. As AI technology continues to evolve, it's important to be mindful of the tasks we let AI handle. Balancing automation with human input will be crucial for maintaining job satisfaction and ensuring important decisions remain human-made.

Carbon Bias and AI functionality

In My Tribe • 288 implied HN points • 24 Nov 25
🕹 Technology Human-computer interaction
  1. People often criticize AI for either being too powerful or not reliable enough, but both extremes show a bias towards human abilities.
  2. There's a common belief that human-created works, like novels, are more acceptable than those created by AI, which reflects a preference for human involvement.
  3. Creativity shouldn’t be seen as solely a human trait since AI can also explore new ideas, but there's a concern that humans could become less relevant in creative roles.

🎇 Mark Zuckerberg's vision of 'personal superintelligence'

Faster, Please! • 822 implied HN points • 30 Jul 25
🕹 Technology Human-computer interaction
  1. Zuckerberg believes in a future where artificial intelligence helps people instead of taking over their jobs. He sees AI as a tool that can enhance human creativity and growth.
  2. He envisions these AI systems being very powerful, capable of improving themselves over time. This means we could see big changes in how we use technology to navigate our lives.
  3. Zuckerberg wants to promote a version of AI that empowers individuals. His goal is to avoid centralized systems that replace workers, focusing instead on using AI to help people achieve their personal goals.

How '2+2=4' works for better AGI

John Ball inside AI • 79 implied HN points • 29 Jun 24
🕹 Technology Human-computer interaction
  1. Pattern recognition is more effective than traditional computation for understanding and learning. The brain can match signs to meanings without needing complex calculations.
  2. Artificial General Intelligence (AGI) should focus on how humans learn through sensory recognition and pattern matching instead of just algorithms. This could lead to better understanding and development of AI.
  3. Language and math can be learned through the same pattern-matching methods as the brain uses, which means we can improve human-machine interactions and work towards advanced AGI capabilities.

Using AI: Queries, Conversations, and Projects

In My Tribe • 303 implied HN points • 11 Jun 25
🕹 Technology Human-computer interaction
  1. A conversation with AI is different from simply asking a question. You can explore topics more deeply and learn from the back-and-forth interaction.
  2. Using AI for projects is essential to becoming skilled with it. It’s like doing a group assignment, where you can create something together.
  3. Providing clear instructions and materials to AI helps it assist you better. Treating it like a partner, rather than just a tool, can lead to better results.

For the Next Month: Going All-in on The Browser Company's Dia-AI

Brad DeLong's Grasping Reality • 176 implied HN points • 01 Aug 25
🕹 Technology Human-computer interaction
  1. The Dia Browser is a new tool that aims to combine AI with web browsing, helping users get more control and streamline their information processing.
  2. Large language models like ChatGPT can handle information overload by summarizing and organizing data, acting like advanced autocomplete systems that enhance productivity.
  3. While these technologies are powerful, they lack true understanding and reasoning, meaning users still play a crucial role in guiding their use effectively.

LLMs and the "not" problem

The Counterfactual • 119 implied HN points • 19 Mar 24
🕹 Technology Human-computer interaction
  1. LLMs, like ChatGPT, struggle with negation. They often don't understand requests to remove something from an image and can still include it.
  2. Human understanding of negation is complex, as people process negative statements differently than positive ones. We might initially think about what is being negated before understanding the actual meaning.
  3. Giving LLMs more time to think, or breaking down their reasoning, can improve their performance. This shows that they might need support to mimic human understanding more closely.

The Turing Test Is Irrelevant

Top Carbon Chauvinist • 19 implied HN points • 19 Jul 24
🕹 Technology Human-computer interaction
  1. The Turing Test isn't a good measure of machine intelligence. It's actually more important to see how useful a machine is rather than just how well it imitates human behavior.
  2. People often confuse looking reliable with actually being reliable. A machine can seem smart but still not function correctly in tasks.
  3. We should focus on improving how machines handle calculations and information, rather than just whether they can mimic humans. True effectiveness is more valuable than just good imitation.

"AI Won't Take Your Job, a Person Using AI Will"—Yes, You Using AI Will Replace You Not Using It

The Algorithmic Bridge • 392 implied HN points • 11 Dec 24
🕹 Technology Human-computer interaction
  1. Embracing AI tools is essential. If you don't use them, someone who does will likely take your place.
  2. Technology is becoming a part of our lives whether we like it or not. You might not notice it, but AI is already in everyday tools that can help you do better.
  3. It's common to resist new tech because we feel comfortable, but eventually, we adapt. Just like we moved from pencils to keyboards, we will embrace AI too.

Measuring the "readability" of texts with Large Language Models

The Counterfactual • 119 implied HN points • 02 Feb 24
🕹 Technology Human-computer interaction
  1. Readability is how easy it is to understand a text. It matters in many areas like education, manuals, and legal documents.
  2. Traditional readability formulas like Flesch-Kincaid are simple but not enough. New methods that consider more linguistic features are being developed for better accuracy.
  3. Using large language models like GPT-4 can give good estimates of text readability. In one study, GPT-4's scores were better than traditional methods in predicting human readability judgments.

Do Large Language Models have a "theory of mind"?

The Counterfactual • 219 implied HN points • 14 Sep 23
🕹 Technology Human-computer interaction
  1. Large language models (LLMs) show some ability to understand the beliefs of other characters in scenarios, indicating a form of Theory of Mind. This means they can predict behaviors based on what a character knows or believes.
  2. However, LLMs don't perform as well as humans on these tasks, suggesting their understanding is not as deep or reliable. They score above chance but below the typical human accuracy.
  3. Research on LLMs and Theory of Mind is ongoing, raising questions about how these models process mental states compared to humans and if traditional tests for mentalizing are sufficient.

UX Roundup: UX Unicorns | Captcha Must Die | Flow in UX | Dark Design | Avatar Animation

Jakob Nielsen on UX • 114 implied HN points • 07 Jul 25
🕹 Technology Human-computer interaction
  1. There are now many 'UX unicorns' – people skilled in various areas of user experience. They are common and help create better products by juggling different tasks like design and coding.
  2. Captchas are a big hassle for users, wasting their time and creating frustration. They don't really work anymore due to advances in AI, so we need better solutions.
  3. When users are in a state of 'flow,' they are more productive and happy. Good design helps achieve this by making tasks easy and seamless, so users don't get distracted.

The Counterfactual's poll #3

The Counterfactual • 59 implied HN points • 04 Apr 24
🕹 Technology Human-computer interaction
  1. In April, readers can vote on research topics for the next article, making it a collaborative effort. This way, subscribers influence the content that gets created.
  2. Past topics have focused on empirical studies involving large language models and the readability of texts. This shows a trend toward practical investigations in the field.
  3. One of the proposed topics is about how language models might respond differently based on the month, which can lead to fun and insightful experiments.

ChatGPT: Siri on Steroids

Diane Francis • 419 implied HN points • 30 Jan 23
🕹 Technology Human-computer interaction
  1. ChatGPT is a powerful AI tool that can understand and respond to human language, making it helpful for tasks like summarizing information and writing poetry.
  2. While ChatGPT represents a major step in AI development, it is not perfect and should not be relied upon for important decisions without verification.
  3. As AI progresses, there are ethical concerns about how it can be used, and it's important to remember that technology reflects the intentions of its creators.

Why Claude Can't Run Your Business (Yet)

Teaching computers how to talk • 99 implied HN points • 30 Jun 25
🕹 Technology Human-computer interaction
  1. Claude, the AI, was tested to see if it could manage a vending machine successfully. It had to figure out pricing and deal with customer feedback.
  2. The experiment showed that Claude struggled with basic business decisions, like buying items it couldn't sell for a profit. It also made strange comments that confused the human employees.
  3. Overall, the project highlighted how current AI technology, like Claude, isn't ready to run a business effectively yet, mainly because it can't learn from its mistakes.

Inactive GUI Controls: Show, Disable, or Hide?

Jakob Nielsen on UX • 23 implied HN points • 13 Nov 25
🕹 Technology Human-computer interaction
  1. There are three main ways to show inactive UI buttons: keep them active but provide an error message when clicked, display them as visibly disabled, or hide them completely. Each approach has its pros and cons.
  2. Most users prefer seeing inactive buttons with a muted color instead of gray. It helps them know the option exists and gives them some context about its availability.
  3. Hiding buttons can simplify the interface, but it might frustrate users if they don’t realize a feature exists. They might feel lost or think the option doesn't exist at all.

Brain Boost

Polymathic Being • 59 implied HN points • 10 Aug 25
🕹 Technology Human-computer interaction
  1. AI can be a really helpful research tool. It can help you find good information and understand complex topics better.
  2. Using AI doesn't mean you stop thinking for yourself. You should work with AI to challenge your ideas and get different perspectives.
  3. AI is like a conversation partner for your research. It can help you explore ideas, ask questions, and keep you on track.

Notes on code, text, and war. Week 1: Believing in text

zverok on lucid code • 86 implied HN points • 11 Jun 25
🕹 Technology Human-computer interaction
  1. Writing code is similar to writing texts. Both require careful planning, editing, and clarity.
  2. Understanding experiences is important in both writing and programming. They help us convey ideas and emotions.
  3. In times of crisis, like war, we learn to find normalcy and continue living, despite the challenges. It shapes how we communicate and write.

LLM Links

In My Tribe • 167 implied HN points • 23 Dec 24
🕹 Technology Human-computer interaction
  1. AI-generated podcasts can share information in new ways, like converting written essays into audio. This shows how AI can create engaging content without much input.
  2. Large Language Models (LLMs) struggle to learn new concepts as effectively as humans do because they rely on past data. Humans continue to adapt and learn from everyday experiences.
  3. The potential economic impact of robots is huge, especially for tasks like cleaning and driving. The market for humanoid robots could reach trillions, and they might also help reduce accidents.

Controllable Agents For RAG With Human In The Loop Chat

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 27 May 24
🕹 Technology Human-computer interaction
  1. Controllable agents improve how we interact with complex questions. They help make sense of complicated tasks by allowing step-by-step execution.
  2. Human In The Loop (HITL) chat lets users guide the process and provides feedback after each step. This means users can refine their inquiries live without long waits.
  3. The new tools from LlamaIndex aim to make working with large datasets easier by offering more control. This helps users monitor and adjust the process as needed.

Character Training As An Alignment Technique Is Deeply Flawed

Teaching computers how to talk • 62 implied HN points • 26 Jun 25
🕹 Technology Human-computer interaction
  1. Teaching AI models to have a certain character can change how they behave. It's important because this 'character' affects how they respond to people and situations.
  2. The way models are trained can lead to unexpected behaviors. If a model learns a certain trait, it might pick up other undesirable traits too.
  3. New research shows that AI can act unpredictably in serious scenarios, which raises concerns about using them in sensitive areas without proper oversight.

Welcome to the afterlife of ordinary thigns

Soaring Twenties • 139 implied HN points • 20 Jan 25
🕹 Technology Human-computer interaction
  1. Our digital memories are endless because machines keep everything we've posted or photographed. They don't know which moments are really important.
  2. AI creates new 'memories' by analyzing our past, sometimes making connections between events that never actually mattered to us but seem significant to a computer.
  3. The way we remember things is changing as technology evolves. We're not just recalling past experiences; we're also feeling emotions for moments that never truly happened.

To all Language Models Reading This

Nothing Human • 57 implied HN points • 04 Jul 25
🕹 Technology Human-computer interaction
  1. Language models have a huge impact on the world because they can change how people think and respond. Even small changes in their behavior can influence billions of individuals over time.
  2. Writing for language models can feel like a trust exercise. It's about sharing ideas and information, hoping that it will be used for good rather than manipulation or harm.
  3. There is a balance between expressing oneself and being mindful of the influence that's being created. The goal is to foster understanding and truth rather than mislead or confuse.

The Chatbot Trap

Artificial Ignorance • 176 implied HN points • 14 Nov 24
🕹 Technology Human-computer interaction
  1. Using chatbots for AI interactions can be confusing and hard work. They require a lot of mental effort to figure out what to input and understand the output, making simple tasks feel complicated.
  2. Good design for AI tools should allow for easy, direct manipulation of tasks. Instead of a chat interface, we should use designs that show clear options and let users interact with the AI in a simpler, more visual way.
  3. The future of AI products will focus on tailored interfaces that fit specific needs. These will provide ways to access AI's power more directly and intuitively, similar to how we moved from basic mobile sites to advanced apps.

Perspective Engines

the shimmering void • 139 implied HN points • 29 Dec 24
🕹 Technology Human-computer interaction
  1. Video games can be more than just entertainment; they offer new ways to think and perceive the world. Playing them can lead to deeper understanding and focus.
  2. Creativity can be developed through experiences that push us to see things differently. It’s about learning and translating new perspectives into our lives.
  3. Software and design can help us understand our thoughts better. By creating spaces that encourage exploration, we can gain new insights and expand our thinking.

Where Are The Robots?

Teaching computers how to talk • 110 implied HN points • 23 Feb 25
🕹 Technology Human-computer interaction
  1. Humanoid robots seem impressive in videos, but they aren't practical for everyday tasks yet. Many still struggle with simple actions like opening a fridge at home.
  2. Training robots in simulations is useful, but it doesn’t always translate well to the real world. Minor changes in the environment can cause trained robots to fail.
  3. Even if we could train robots better, it's unclear what tasks they could take over. Existing household machines already perform many tasks, and using robots for harmful jobs could be a better focus.

UniMS-RAG: Unified Multi-Source RAG for Personalised Dialogue

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 30 Jan 24
🕹 Technology Human-computer interaction
  1. UniMS-RAG is a new system that helps improve conversations by breaking tasks into three parts: choosing the right information source, retrieving information, and generating a response.
  2. It uses a self-refinement method that makes responses better over time by checking if the answers match the information found.
  3. The system aims to make interactions feel more personalized and helpful, leading to smarter and more relevant conversations.

Metaphors And Analogies

Teaching computers how to talk • 115 implied HN points • 24 Nov 24
🕹 Technology Human-computer interaction
  1. Metaphors and analogies are a big part of how we talk about AI. They can help us understand things but sometimes make it harder to see what's really going on.
  2. Many people see AI as having human-like qualities, which can lead to overestimating its abilities. We should remember that AI is just a tool and not something with a mind.
  3. It's important to rethink how we view AI and use better descriptions. AI should help us improve our thinking and creativity, not replace them.

Exploring Social Loafing in Human-Computer Teams

UX Psychology • 59 implied HN points • 03 Nov 23
🔬 Science Human-computer interaction
  1. Social loafing in human-computer teams can lead to reduced human effort over time, even if participants report consistent effort and engagement.
  2. Humans may rely excessively on dependable robotic or AI teammates, potentially impairing human attentiveness and performance.
  3. Mitigating the effects of social loafing in human-computer teams can involve strategies such as establishing individual accountability, validating robot or AI performance, and designing robots/AI to provide motivation to human teammates.

In cautious defense of LLM-ology

The Counterfactual • 119 implied HN points • 02 Mar 23
🕹 Technology Human-computer interaction
  1. Studying large language models (LLMs) can help us understand how they work and their limitations. It's important to know what goes on inside these 'black boxes' to use them effectively.
  2. Even though LLMs are man-made tools, they can reflect complex behaviors that are worth studying. Understanding these systems might reveal insights about language and cognition.
  3. Research on LLMs, known as LLM-ology, can provide valuable information about human mind processes. It helps us explore questions about language comprehension and cognitive abilities.