The hottest Human-computer interaction Substack posts right now

And their main takeaways
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Top Technology Topics

There's more to LLMs than chat

Generating Conversation • 216 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.

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 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.

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.
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