SnippSkip or NotifSkip and Instant Messaging Multi–Layered Interface

In the world of "instant messaging", we propose the term "SnippSkip" (or "NotifSkip") to describe the action of a user choosing to skip reading a message after briefly reviewing its snippet. This behavior is primarily observed within message list views (SnippSkip) or notification panels (NotifSkip).

Potential motivations for SnippSkip might include:

1. Time Constraints: Users may be occupied and unable or unwilling (or both) to fully engage with all messages.
2. Read Receipt Avoidance: Users may seek to avoid triggering read receipts. Although there are settings to disable "Read receipts", the setting has its own limitations.While SnippSkip may serve as a temporary or personal solution, it warrants some investigation to address potential underlying issues.

Uncle Sam meme
informing "SnippSkip"

Multi–layered Messaging Interface

At present, the instant messaging interfaces predominantly offer a single-layered structure, presenting all chat contacts within a side panel. In the single–layered interface users start or continue conversations by selecting individual chat heads. While some services or platforms offer supplementary features, such as "Restrict" (e.g., Facebook Messenger) or "Grouping" (e.g., WhatsApp, Telegram), these functionalities remain limited.

There is a growing need to transition towards multi-layered interfaces and offer enhanced user control. The following suggestions and recommendations propose potential avenues for this evolution.

Priority Mode (Interface selection ability)

While some instant messaging services, such as Google Chat, offer availability icons and custom status messages, these primarily serve to convey basic availability. A better approach possibly could be to let users choose different priority levels for their messaging interfaces.

We propose to consider some of the following priority–based interfaces as examples:

• General Interface (Default): This interface mirrors the current single-layered structure, and display all chat contacts and discussions.
• Busy Interface: This mode filters the interface to display only pre–selected or preset contacts or chat heads. This interface effectively hide all other messages and contacts.
• Groups–Only Interface: This interface restricts visibility to group discussions, and exclude individual chats.
• Chats–Only Interface: This mode eliminates all group discussions, communities, status updates (e.g., WhatsApp), stories (e.g., Telegram, WhatsApp), notes (e.g., Facebook Messenger), displaying only individual chats.

WhatsApp interface stock photo
shows a potential single–click
interface changed dropdown

In clearer words an interface selection feature would enable users to dynamically switch between different interface modes based on their current needs. For example, a WhatsApp user could enable a "Busy Interface" (or a customized interface) to filter out updates, communities, and other distractions, displaying only the essential content they wanted.

Ideally this interface selection could be implemented with a single-click dropdown menu located in a corner of the interface. For privacy reasons one's interface choice should be kept private.

Multiple Interfaces: Benefits

Introducing multiple interfaces offers several potential benefits:

• Enhanced User Control: Users gain the ability to customize their view, displaying only the content relevant to their current needs. This might be quite helpful during periods of high workload.
• Reduced Distractions: By filtering out unnecessary information, users can improve focus and minimize distractions. Hopefully, this might reduce the incidence of helpless SnippSkip behavior.
• Scalability for Advanced Features: The multi-layered interface structure will provide a foundation for incorporating more granular interface-level controls, including parental supervision features.

Therefore, possibly the suggestions and recommendations of implementing and evolving into a multi–layered interface could be explored. In this website, we'll continue publishing various other ideas, suggestions, and concerns around digital life, and the life in general.

Let Him Be Caesar First — Generative Artificial Intelligence: Adaptability, Acceptance and User Experience

"I propose to consider the question, 'Can machines think?' This should begin with definitions of the meaning of the terms 'machine; and 'think'. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous."

— These were the opening sentences of Alan Turing's 1950 seminal paper "Computing Machinery and Intelligence" in which the famous Turing Test was introduced. The Turing Test is a method that evaluates a machine's ability to think imitating (like) a human. 

In 2025, with the rapid advancement in the fields of Artificial Intelligence and Machine learning, we propose to consider "Can machines create/generate (like humans)"? On one hand there are arguments that Generative AIs are generating content based on machine learning of the huge amount of existing data. On the other hand there are arguments and results (outputs) that various AI tools are generating content such as prose, poem, images etc, definitely much faster than, and sometimes possibly better than a human. 

In June 2024 OpenAI's former CTO Mira Murati observed— "Some creative jobs maybe will go away, but maybe they shouldn't have been there in the first place." The last part of her observation might not be fully accurate (or explained) because— 

• a) as long as any previous job or creation sets foundation or base of our current works, that is important. We may recall Isaac Newton's metaphor "Standing on the Shoulders of the Giants".
• b) even if any work does not have direct or indirect functionality today, if it served any purpose anytime in the past, still they should have been there (as they did).

However, the question we are pondering on is "Can machines create (like humans)?"

A Small-Scale Turing Test

In the second half of 2024, i conducted a small–scale Turing test where i presented visual and other content to the participants without labeling and sometimes deliberately mislabeling the creation type/process. The triggering point of the test was when i, during normal chat conversations, sent photos of something, and got remarks "Is this AI generated?" As this confusion took place more than once and the questions were honest, i thought to do this small–scale test inspired by Turing's.

In the next few months, sometimes during random conversations, i presented content (mostly images, and text based) to people either by not mentioning how and who created it, or by intentionally mislabeling the creator (labeling human creation as AI creation and the vice versa).

i can not draw any major conclusion from the small sample size i had. However the test results definitely showed some interesting confusion in detection/appreciation. What is more important, (and the main topic of this writing), it is highly possible that human intelligence ("we") tend to ignore things and give less importance to a creation, the moment we get to know that it is an AI–creation.

Generative AI: Adaptability, Acceptance for Larger Market Share (User Connect)

There are various companies and institutions offering generative artificial intelligence services. While, a lot of resources are being invested to train the AI models, some attention is to be given towards studying the reasons and possible hindrances that might ("is") creating an "emotional distancing". 

It is not uncommon to see a person, when gifted a hand–drawn painting, shows deep gratitude and preserves it with care. The same person, if gifted a much better quality AI–generated painting or portrait, may not show similar interest.

One opinion might be: AI can never be humans, and create like humans. On the other hand there can be an inquisitive approach. There is a thought experiment question— "If a tree falls in a forest and no one is around to hear it, does it make a sound?" The answer is "yes", the falling tree still makes a sound even if there is no one around to hear. Similarly, does AI creation deserve same acceptance and esteem that a human gets if the AI creation is of the same/better quality? Possibly can not be answered immediately.

Even if we completely ignore this "Artificial Intelligence Rights" aspect (possibly the paragraph above sounded so), a company, most probably, is compromising and losing on its user base unless the above mentioned adaptability and acceptance issues are studied further. This is directly linked with user connect and over–all user experience.

"Let Him Be Caesar First"
William Shakespeare Act 3, Scene 2
Image source: Wikimedia Commons

Possible reasons

It is a subject of broad studies to investigate "what actually makes things human?" Possible reasons are—

• We Appreciate the Process and Not Only the Output: We respect the process, and not the one time output. If someone is gifted a painting they appreciate the time and efforts given for it, not only the painting.
• Human Interaction Uncertainty Principle: We humans, when interact with each other, there is always some uncertainty — we don't know what's coming from the other side. The moment we can find and presume patterns, possibly human intelligence tends to ignore it.
• Perfection is Not Perfect Always: In human interaction, communication, and creation there are imperfections of different kinds (errors, inaccuracies, typos etc.). We are used to it. Completely error–free perfect things might also make things "not" human like. Perfection may not be perfect always (however this does not suggest to generate AI responses with minor errors/typos. That will be an easy but a pathetic solution).

This might be interesting and impactful to get expert views of neuropsychologists and psychologists (who have studies on human mind), social/human interaction specialists, AI psychologists and other experts. Possibly there can be surveys, interviews and experiments with larger and diversified audience and sample size. The learnings can be incorporated in the AI services in a systematic manner. This should result in over–all user experience improvement, and service improvement.