The hottest Human-computer interaction Substack posts right now

And their main takeaways
Category
Top Technology Topics

Using AI: Queries, Conversations, and Projects

In My Tribe • 303 implied HN points • 11 Jun 25
🕹 Technology AI Machine Learning Human-computer interaction Software Development Educational Technology
  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.

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

Marcus on AI • 6007 implied HN points • 30 Dec 24
🕹 Technology Artificial Intelligence Human-computer interaction AI Policy Machine Learning
  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.

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 Digital ethics Artificial Intelligence
  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.

Where Are The Robots?

Teaching computers how to talk • 110 implied HN points • 23 Feb 25
🕹 Technology Robotics AI Human-computer interaction Automation Machine Learning
  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.

Why do I say thank you to Alexa?

Jeff Giesea • 558 implied HN points • 13 Oct 24
🕹 Technology Artificial Intelligence Human-computer interaction Ethics Automation Society
  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.
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Deliberative Alignment, And The Spec

Astral Codex Ten • 11149 implied HN points • 12 Feb 25
🕹 Technology AI Ethics Machine Learning Computer Science Tech governance 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.

Ocean Whoosh

New World Same Humans • 47 implied HN points • 09 Feb 25
🕹 Technology Artificial Intelligence Virtual reality Human-computer interaction Digital Culture
  1. We are entering a new era with advanced technology, like superintelligent machines, which will challenge what it means to be human. This could lead to a stronger connection with our real world and each other.
  2. Nature, especially the sound of the ocean, can remind us of a simpler, more authentic way of being. It's like a song from the past that connects us to who we really are.
  3. As we face a future filled with technology, it's important to hold onto our human values and create spaces where we can truly be ourselves. We need to nurture what makes us unique and human.

Welcome to the afterlife of ordinary thigns

Soaring Twenties • 139 implied HN points • 20 Jan 25
🕹 Technology Artificial Intelligence Memory Digital Culture Social media 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.

"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 Artificial Intelligence Automation Job Market Human-computer interaction Digital Tools
  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.

Perspective Engines

the shimmering void • 139 implied HN points • 29 Dec 24
🕹 Technology Software Gaming Human-computer interaction Design Creativity
  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.

Beyond RAG: Building a Knowledge Management System That Enhances Rather Than Replaces Thought

Nick Savage • 56 implied HN points • 02 Jan 25
🕹 Technology Knowledge Management Artificial Intelligence Digital Tools Information Systems Human-computer interaction
  1. Using digital tools for note-taking can be helpful, but you can lose some benefits of physical notes, like seeing related ideas together. It's important to find ways to keep those surprising connections.
  2. AI tools can automate parts of knowledge management, but they might not always help you understand the content better. Personal processing and making connections should still be done by humans.
  3. The goal of a good knowledge management system is to enhance your own insights and understanding. Tools should help organize, but the learning and connecting of ideas should still come from you.

Talking to Computers Is My Default Form of Communication

Default Wisdom • 55 implied HN points • 02 Jan 25
🕹 Technology AI Communication Human-computer interaction Digital Culture Case Studies
  1. Talking to computers has become a normal way for many people to communicate. It feels easier and more natural as technology advances.
  2. The growth of technology has changed how we interact with each other and the world around us. More conversations now happen through screens instead of face-to-face.
  3. Understanding how humans relate to technology is important. It can help us improve communication and make our interactions with computers better.

The Chatbot Trap

Artificial Ignorance • 176 implied HN points • 14 Nov 24
🕹 Technology AI UX Design Product Development Software Engineering 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.

Metaphors And Analogies

Teaching computers how to talk • 115 implied HN points • 24 Nov 24
🕹 Technology Artificial Intelligence Metaphors Language processing Human-computer interaction Machine Learning
  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.

The Artificial Intelligence Project

Teaching computers how to talk • 99 implied HN points • 14 Nov 24
🕹 Technology Artificial Intelligence Digital Culture Human-computer interaction Future Trends Ethics
  1. Artificial intelligence is largely driven by our desire to create something better than ourselves. We often design AI to reflect human traits, which raises questions about our motivations.
  2. People may start preferring AI companions over real relationships because they can be ideal, obedient, and without the messiness of human emotions.
  3. If AI becomes too autonomous, it could potentially act against human interests, leading to serious consequences. This raises important concerns about how we manage and control artificial intelligence.

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

John Ball inside AI • 79 implied HN points • 29 Jun 24
🕹 Technology Artificial Intelligence Machine Learning Cognitive Science 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.

LLM Links

In My Tribe • 167 implied HN points • 23 Dec 24
🕹 Technology AI Robotics Machine Learning Human-computer interaction Automation
  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.

LLMs and the "not" problem

The Counterfactual • 119 implied HN points • 19 Mar 24
🕹 Technology AI Language Models Cognitive Science Image Generation 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 AI Ethics Machine Learning Computer Science 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.

Measuring the "readability" of texts with Large Language Models

The Counterfactual • 119 implied HN points • 02 Feb 24
🕹 Technology AI Education Data science Human-computer interaction Machine Learning
  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 AI Machine Learning Cognitive Science Human-computer interaction Data Analysis
  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.

There's more to LLMs than chat

Generating Conversation • 233 implied HN points • 15 Feb 24
🕹 Technology AI UX Design Information Retrieval Human-computer interaction
  1. Chat interfaces have limitations, and using LLMs in more diverse ways beyond chat is essential for product innovation.
  2. Chat-based interactions lack the expression of uncertainty, unlike other search-based approaches, which impacts user trust in the information provided by LLMs.
  3. LLMs can be utilized to proactively surface information relevant to users, showing that chat isn't always the most effective approach for certain interactions.

The Counterfactual's poll #3

The Counterfactual • 59 implied HN points • 04 Apr 24
🕹 Technology Artificial Intelligence Language Models Data science 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 Artificial Intelligence Software Development Human-computer interaction Ethics Innovation
  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.

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 Artificial Intelligence Machine Learning Natural Language Processing Automation 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.

Why can't I be a dick to AI?

The Rectangle • 113 implied HN points • 23 Feb 24
🕹 Technology AI Chatbots Ethics Big Tech Human-computer interaction
  1. We often treat AI with politeness and empathy because our brains expect something that talks like a human to be human.
  2. Despite AI being just a tool, companies make them human-like to leverage our trust and make us more receptive to their messages.
  3. There's a societal expectation to be decent even towards artificial entities, like AI, even though they're not humans with feelings and consciousness.

LLM links

In My Tribe • 182 implied HN points • 29 Jan 24
🕹 Technology Artificial Intelligence Podcasts Board Games Learning Human-computer interaction
  1. Large language models (LLMs) do not work by remembering and spitting back information, but by analyzing word patterns and coding them into vectors.
  2. Artificial intelligence has significantly improved human gameplay in board games like Go, leading to more creative and strategic play.
  3. Learning from artificial intelligence in board games involves recognizing and correcting suboptimal moves, rather than trying to imitate the AI's every move.

Partial Intelligence and Super-intelligence

Charles Eisenstein • 5 implied HN points • 21 Dec 24
🕹 Technology Artificial Intelligence Human-computer interaction
  1. Artificial intelligence (AI) shows amazing skills but it's not the same as human intelligence. AI learns from patterns in data, but it doesn't feel emotions like humans do.
  2. AI can simulate deep conversations and insights but lacks true self-awareness or consciousness. It's designed to mimic human responses without actually experiencing them.
  3. The relationship between AI and humans is complex. As we rely more on AI, we risk losing touch with our own natural experiences and emotions, which are vital to understanding intelligence.

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 Artificial Intelligence Machine Learning Natural Language Data science 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.

Exploring Social Loafing in Human-Computer Teams

UX Psychology • 59 implied HN points • 03 Nov 23
🔬 Science Human-computer interaction Psychology Artificial Intelligence Research Methods Technology
  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 AI Development Machine Learning Natural Language Processing Cognitive Science 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.

Mechanical Turk is aptly named

The Counterfactual • 79 implied HN points • 16 Jun 23
🕹 Technology AI Automation Gig Economy Human-computer interaction Data Ethics
  1. The Mechanical Turk was a famous hoax in the 18th century that impressed many by pretending to be an intelligent chess-playing machine, but it actually relied on a hidden human operator.
  2. Today, Amazon Mechanical Turk allows people to complete simple tasks that machines struggle with. It's a platform where those who need work can connect with people willing to do it for a small fee.
  3. Recent studies reveal that many tasks on MTurk may not be done by humans at all; a significant portion are actually completed using AI tools, raising questions about the reliability of data collected from such platforms.

Modifying readability with large language models (pt. 1)

The Counterfactual • 19 implied HN points • 29 Feb 24
🕹 Technology AI Readability Language Models Human-computer interaction Data Analysis
  1. Large language models can change text to make it easier or harder to read. It's important to check if these changes actually help with understanding.
  2. By comparing modified texts to their original versions, it's clear that 'Easy' texts are generally simpler than 'Hard' texts. However, it can be harder to make texts significantly simpler than they originally are.
  3. Despite the usefulness of these models, they might sometimes lose important information when simplifying texts. Future studies should involve human judgments to see if the changes maintain the original meaning.

Intent and Iteration are the new Click and Drag

Sunday Letters • 79 implied HN points • 02 Apr 23
🕹 Technology AI UX Design Software User Experience Human-computer interaction
  1. Understanding intent is more powerful than following a strict process. It's like asking for milk instead of giving detailed steps on how to walk to the kitchen.
  2. We need to iterate when designing user experiences as language and meaning can change over time. It's like adjusting your conversation when something doesn’t make sense.
  3. Future software will focus on talking to computers in more natural ways, using various methods like voice, images, and gestures instead of just clicking buttons. This makes interactions more flexible and user-friendly.

Intelligence and combinatorial complexity

Sunday Letters • 39 implied HN points • 27 Aug 23
🕹 Technology AI Research Machine Learning Cognitive Science Computational Theory Human-computer interaction
  1. More agents working together can create better intelligence than a single agent. This is surprising because we might think one advanced model is enough, but collaboration can enhance performance.
  2. Human-like patterns help improve AI performance. Just as we can review our work for errors, AI systems can use different modes to refine their outputs.
  3. Complex systems come with challenges like errors and biases. As AI gets more complicated, these issues tend to increase, similar to problems found in complex biological systems.

Where is the autonomy in AI?

Sunday Letters • 19 implied HN points • 06 Nov 23
🕹 Technology AI Machine Learning Software Development Automation Human-computer interaction
  1. AI models like large language models need human guidance to perform tasks effectively. Humans help by providing prompts and correcting errors.
  2. Even complex tasks require a lot of human involvement. AI can't work fully independently; it can't just be told to 'write a book' without further instruction.
  3. There is still a long way to go in developing AI that can handle complex, open-ended problems alone. Current systems struggle with autonomy and can't yet replicate human planning and organization.

Jarvis, you up?

Sector 6 | The Newsletter of AIM • 19 implied HN points • 18 Oct 23
🕹 Technology AI Autonomous Agents Machine Learning Human-computer interaction Software Development
  1. OpenAI is launching an autonomous agent called JARVIS, inspired by Iron Man. This tech could change how we do many online tasks like sending emails and booking flights.
  2. The co-founder of OpenAI shared that the assistant can negotiate business deals with little help. It's interesting that it refers to itself as JARVIS too.
  3. Overall, the new JARVIS could make interacting with the internet easier and more efficient, handling various online activities for users.