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AI Notetakers in Meetings—Innovation, Invasion, or Something in Between?

The rise of AI notetakers in meetings: productivity perks, pitfalls and how to balance collaboration with privacy and security concerns.

Published

3 months ago

February 20, 2025

AIinAsia

TL;DR – What You Need to Know in 30 Seconds

AI notetakers are on the rise, popping into Zoom calls to record and summarise discussion points.
Productivity benefits: 30–50% reduction in manual note-taking, 78% better engagement, fewer disputes over who said what.
Potential downsides: Self-censorship, privacy concerns, AI “hallucinations,” overshadowing junior voices, and compliance nightmares under GDPR/all-party consent laws.
Behavioural shift: People become more formal, more cautious, and less creative when they know they’re being recorded—an effect tied to fear of accountability, self-presentation, and the Observer Effect.

The Rise of AI Notetakers in Meetings

Picture this: It’s Monday morning, you’ve barely taken a sip of your Earl Grey, and you hop into your first Zoom of the day. Glancing at the attendee list, you see a curious name—something like “Fireflies.ai,” “Sharpen Notes,” or “MeetGeek”, or “Read.ai“. Congratulations, you’ve just met your new colleague: the AI notetaker.

Over the last year or two, these AI-driven meeting assistants have surged in popularity. On paper, they promise less admin, better accountability, and an end to your frantic scribbling. Yet, we’re discovering a range of pitfalls, from privacy and consent issues to the not-so-obvious threat of stifling free-flowing discussion. So in today’s chatty but comprehensive feature, let’s delve into why these digital note-takers might save you time—but at a cost you never saw coming.

A Quick Scene-Setter: The Rise of the AI Notetaker

According to Gokul Rajaram, cofounder at Marathon Management Partners, AI notetakers appear in 80% of the meetings he attends. Sometimes multiple bots show up, introduced by different participants. Why the explosion in popularity? Because, in theory, they do away with the chore of note-taking and allow every attendee to stay present in the conversation. Afterwards, you get a neat summary, key decisions, and follow-up tasks. No more “Who was assigned that again?”

Firms like Microsoft and Google have jumped on the bandwagon, integrating notetaking AI into Teams or Workspace. Smaller startups—Bubbles, Sharpen Notes, Otter.ai, Fireflies.ai, and others—have also joined the fray, offering everything from voice-to-text transcripts to advanced analytics (like speaking-time breakdowns).

Indeed, the efficiency claims can’t be dismissed out of hand. One study from a financial firm using Filenote.ai found each meeting’s notetaking chores dropped by 30–40 minutes. And that’s real time. Yet, the question remains: Is convenience overshadowing crucial ethical and psychological considerations?

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A Balanced Analysis: Productivity Benefits vs. Discussion Inhibitors

Before we dive into the darker side of AI notetakers, let’s present a balanced look at both the good and the not-so-good. After all, these tools do offer tangible benefits—provided you implement them wisely.

Productivity Benefits

Efficiency Gains
Research shows AI notetakers can reduce manual transcription time by 30–50%. Tools like Sharpen Notes and Bubbles provide real-time transcripts and automated action items, meaning staff can focus on the actual content rather than scribbling away.
Improved Focus
In one internal user survey, 78% of respondents reported better meeting engagement when they weren’t bogged down by note-taking. Paying closer attention to the conversation leads to richer discussion and fewer “Sorry, can you repeat that?” moments.
Enhanced Accountability
An AI notetaker creates a single source of truth—removing the dreaded “he said, she said” scenario. According to Workplace Options case studies, 40% fewer disputes arise when participants can review the conversation transcripts and see assigned tasks in black and white.

Potential Discussion Inhibitors

Psychological Barriers
In a Bloomberg survey, 34% of employees expressed discomfort about AI listeners, especially around sensitive topics like layoffs, pay cuts, or performance evaluations. Knowing your words are stored can curb candid dialogue and hamper creativity.
Power Dynamics
Some AI notetakers inadvertently weight senior voices more heavily in summaries—especially if the CEO or director interrupts others or uses more “dominant” phrases. This can silence junior contributors, who may feel overshadowed by the algorithmic summary.
Technical Limitations
- Non-verbal cues (tone, sarcasm, etc.) often go undetected, risking misinterpretation of jokes or playful banter.
- Cross-talk in heated debates can result in a jumbled transcript.
- Confidential legal or HR discussions might require more nuance than a machine can manage.

So where does that leave us? Many see AI notetakers as a double-edged sword: they can simplify drudgery, but they must be deployed thoughtfully, with clear guidelines and a thorough understanding of each meeting’s context.

The Psychological Tendency to Alter Behaviour When Being Recorded

It’s not just compliance with laws like GDPR or HIPAA that should worry us—human beings simply behave differently when they know they’re on record. There is an entire field of study surrounding how people self-censor or modify their tone and content the moment they realise a third party (even a robot) is listening.

Fear of Accountability: When statements are documented verbatim, participants spend more time refining their words to avoid negative consequences, mistakes, or future scrutiny. One study showed employees in enterprise social media platforms exert 23% more “codification effort” (careful wording and editing) to avoid misunderstandings.
Observer Effect: Similar to the Hawthorne Effect, where individuals change their behaviour because they’re aware of being observed, police body camera studies reveal a 39% reduction in use-of-force incidents when officers know their actions are recorded.
Self-Presentation Theory: Humans want to look good, or at least avoid looking bad. Neurological research found a 58% reduction in informal speech, 41% increase in “politically correct” phrasing, and 27% longer pause times when subjects know they’re being recorded.

These factors lead to more cautious, less spontaneous exchanges. In cross-cultural settings, these modifications can be even more pronounced; collectivist societies (e.g., many in Asia) have shown a 29% stronger behavioural shift under observation than individualistic cultures.

All of which begs the question: Aren’t meetings meant to encourage free-flowing innovation and real-time problem-solving? If people self-censor, will the best ideas even see the light of day?

Privacy and Consent: It’s (Not) Just a Checkbox

The Consent Minefield

In an all-party consent jurisdiction—like California, Massachusetts, or Illinois—everyone in the meeting must explicitly agree to be recorded. In places governed by GDPR (such as the EU), participants must be clearly informed about what’s being recorded, how data is stored, and for how long. If a single person says, “No, I’m not comfortable,” you need to turn that AI off, full stop.

Pre-Meeting Emails: Many companies are setting up 24-hour advanced notices, explaining the presence of an AI notetaker and offering an opt-out.
Landing Page Gateways: Some tools require participants to click “I Agree” to proceed into the meeting, ensuring explicit consent.
Real-Time Alerts: Platforms like Zoom or Microsoft Teams flash notifications or announcements as soon as recording begins, letting latecomers know a bot is capturing every word.

The Big (Data) Question

Even if you have consent, there’s still the matter of where the data goes. Companies such as Fireflies.ai claim not to train on customer data, but it’s vital to read the fine print. If you’re discussing trade secrets, creative concepts, or sensitive HR matters, who’s to say your IP isn’t helping build the next big language model?

And let’s not forget the possibility of data breaches. If your transcripts sit on a poorly secured server, it’s not just your social chatter at risk but potentially entire product roadmaps, personnel evaluations, or contract negotiations.

Where AI Shines: Best Practices for Balance

So, can AI notetakers work if we navigate the pitfalls? Absolutely—if you follow some measured guidelines.

Transparent Implementation
- Announce AI presence at the meeting start and outline how transcripts will be used.
- Allow opt-out periods for sensitive discussions so people can speak candidly, free from digital oversight.
Human-AI Collaboration
- Use AI to generate a first draft; let a human note-taker review and inject nuance. This is especially critical for jokes, sarcasm, or side commentary.
- Some companies designate a “human verifier” to glance through the final summary, confirming it doesn’t misquote or inadvertently escalate a minor issue.
Technical Safeguards
- Enable temporary recording pauses when legal or HR topics pop up.
- Use enterprise-grade encryption to prevent leaks. Tools that are SOC 2 certified or boast HIPAA-compliant frameworks (like certain healthcare notetakers) are a good sign.
- Conduct regular accuracy audits to ensure the AI isn’t “hallucinating” or attributing statements to the wrong person.

Case in point: Microsoft implemented AI-powered Intelligent Recap (part of Teams Premium) across its global workforce. Results observed internally include:

35-40% reduction in time spent reviewing meetings for employees catching up on missed sessions
93% of users reported improved efficiency in tracking action items and decisions compared to manual note-taking
50% faster follow-up task allocation due to AI-generated summaries highlighting key next steps

This functionality improves my productivity significantly… I have started recording more meetings because of it.
Tyler Russell, Senior Engineering Architect at Microsoft4.
Tweet

The Human Touch vs. the Digital Data Feed

Remember, the primary reason we gather colleagues in a (virtual) room is to talk, connect, and bounce ideas off each other. That means subtle jokes, tangential remarks, or even half-baked proposals that might spark something brilliant later. If we become too stiff or guarded because an AI might record and store our every breath, we risk turning meetings into purely transactional data feeds.

Margaret Mitchell, chief ethics scientist at Hugging Face, points out that a sarcastic quip could easily end up as an official “action item” in the transcript. If the AI doesn’t understand tone—and let’s be honest, so many of them don’t—your joke might become someone else’s headache.

Balancing Productivity and Openness: A Recap

Let’s summarise the practical tension:

Yes, AI notetakers can reduce friction, cut note-taking time by almost half, and improve accountability.
Yes, we can mitigate some of the privacy nightmares with clear consent processes, robust encryption, and data minimisation (i.e., automatically deleting transcripts after a set period).
But AI notetakers also threaten the very essence of a meeting by inhibiting spontaneity, free speech, and creative risk-taking.
And from a human psychology standpoint, recording drastically alters behaviour—34% more formality, self-censorship in sensitive contexts, and an uptick in anxiety among marginalised groups who have historically faced scrutiny.

Essentially, it’s a question of trade-offs: do you value speed and accountability more, or is open, free collaboration paramount? Ideally, we want both, which means implementing guardrails that ensure an AI notetaker doesn’t overshadow the human heart of the meeting.

What do YOU think?

Are we risking our most innovative, off-the-cuff ideas—and the genuine human connections that meetings are supposed to foster—by handing over every conversation to AI’s unwavering digital memory? Let us know in the comments below! And don’t forget to subscribe for the latest AI happenings in Asia!

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Build Your Own Agentic AI — No Coding Required

Want to build a smart AI agent without coding? Here’s how to use ChatGPT and no-code tools to create your own agentic AI — step by step.

Published

21 hours ago

May 9, 2025

AIinAsia

TL;DR — What You Need to Know About Agentic AI

Anyone can now build a powerful AI agent using ChatGPT — no technical skills needed.
Tools like Custom GPTs and Make.com make it easy to create agents that do more than chat — they take action.
The key is to start with a clear purpose, test it in real-world conditions, and expand as your needs grow.

Anyone Can Build One — And That Includes You

Not too long ago, building a truly capable AI agent felt like something only Silicon Valley engineers could pull off. But the landscape has changed. You don’t need a background in programming or data science anymore — you just need a clear idea of what you want your AI to do, and access to a few easy-to-use tools.

Whether you’re a startup founder looking to automate support, a marketer wanting to build a digital assistant, or simply someone curious about AI, creating your own agent is now well within reach.

What Does ‘Agentic’ Mean, Exactly?

Think of an agentic AI as something far more capable than a standard chatbot. It’s an AI that doesn’t just reply to questions — it can actually do things. That might mean sending emails, pulling information from the web, updating spreadsheets, or interacting with third-party tools and systems.

The difference lies in autonomy. A typical chatbot might respond with a script or FAQ-style answer. An agentic AI, on the other hand, understands the user’s intent, takes appropriate action, and adapts based on ongoing feedback and instructions. It behaves more like a digital team member than a digital toy.

Step 1: Define What You Want It to Do

Before you dive into building anything, it’s important to get crystal clear on what role your agent will play.

Ask yourself:

Who is going to use this agent?
What specific tasks should it be responsible for?
Are there repetitive processes it can take off your plate?

For instance, if you run an online business, you might want an agent that handles frequently asked questions, helps users track their orders, and flags complex queries for human follow-up. If you’re in consulting, your agent could be designed to book meetings, answer basic service questions, or even pre-qualify leads.

Be practical. Focus on solving one or two real problems. You can always expand its capabilities later.

Step 2: Pick a No-Code Platform to Build On

Now comes the fun part: choosing the right platform. If you’re new to this, I recommend starting with OpenAI’s Custom GPTs — it’s the most accessible option and designed for non-coders.

Custom GPTs allow you to build your own version of ChatGPT by simply describing what you want it to do. No technical setup required. You’ll need a ChatGPT Plus or Team subscription to access this feature, but once inside, the process is remarkably straightforward.

If you’re aiming for more complex automation — such as integrating your agent with email systems, customer databases, or CRMs — you may want to explore other no-code platforms like Make.com (formerly Integromat), Dialogflow, or Bubble.io. These offer visual builders where you can map out flows, connect apps, and define logic — all without needing to write a single line of code.

Step 3: Use ChatGPT’s Custom GPT Builder

Let’s say you’ve opted for the Custom GPT route — here’s how to get started.

First, log in to your ChatGPT account and select “Explore GPTs” from the sidebar. Click on “Create,” and you’ll be prompted to describe your agent in natural language. That’s it — just describe what the agent should do, how it should behave, and what tone it should take. For example:

“You are a friendly and professional assistant for my online skincare shop. You help customers with questions about product ingredients, delivery options, and how to track their order status.”

Once you’ve set the description, you can go further by uploading reference materials such as product catalogues, FAQs, or policies. These will give your agent deeper knowledge to draw from. You can also choose to enable additional tools like web browsing or code interpretation, depending on your needs.

Then, test it. Interact with your agent just like a customer would. If it stumbles, refine your instructions. Think of it like coaching — the more clearly you guide it, the better the output becomes.

Step 4: Go Further with Visual Builders

If you’re looking to connect your agent to the outside world — such as pulling data from a spreadsheet, triggering a workflow in your CRM, or sending a Slack message — that’s where tools like Make.com come in.

These platforms allow you to visually design workflows by dragging and dropping different actions and services into a flowchart-style builder. You can set up scenarios like:

A user asks the agent, “Where’s my order?”
The agent extracts key info (e.g. email or order number)
It looks up the order via an API or database
It responds with the latest shipping status, all in real time

The experience feels a bit like setting up rules in Zapier, but with more control over logic and branching paths. These platforms open up serious possibilities without requiring a developer on your team.

Step 5: Train It, Test It, Then Launch

Once your agent is built, don’t stop there. Test it with real people — ideally your target users. Watch how they interact with it. Are there questions it can’t answer? Instructions it misinterprets? Fix those, and iterate as you go.

Training doesn’t mean coding — it just means improving the agent’s understanding and behaviour by updating your descriptions, feeding it more examples, or adjusting its structure in the visual builder.

Over time, your agent will become more capable, confident, and useful. Think of it as a digital intern that never sleeps — but needs a bit of initial training to perform well.

Why Build One?

The most obvious reason is time. An AI agent can handle repetitive questions, assist users around the clock, and reduce the strain on your support or operations team.

But there’s also the strategic edge. As more companies move towards automation and AI-led support, offering a smart, responsive agent isn’t just a nice-to-have — it’s quickly becoming an expectation.

And here’s the kicker: you don’t need a big team or budget to get started. You just need clarity, curiosity, and a bit of time to explore.

Where to Begin

If you’ve got a ChatGPT Plus account, start by building a Custom GPT. You’ll get an immediate sense of what’s possible. Then, if you need more, look at integrating Make.com or another builder that fits your workflow.

The world of agentic AI is no longer reserved for the technically gifted. It’s now open to creators, business owners, educators, and anyone else with a problem to solve and a bit of imagination.

What kind of AI agent would you build — and what would you have it do for you first? Let us know in the comments below!

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Or tap here to try this out now at ChatGPT by tapping here.

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Which ChatGPT Model Should You Choose?

Confused about the ChatGPT model options? This guide clarifies how to choose the right model for your tasks.

Published

1 day ago

May 9, 2025

AIinAsia

TL;DR — What You Need to Know:

GPT-4o is ideal for summarising, brainstorming, and real-time data analysis, with multimodal capabilities.
GPT-4.5 is the go-to for creativity, emotional intelligence, and communication-based tasks.
o4-mini is designed for speed and technical queries, while o4-mini-high excels at detailed tasks like advanced coding and scientific explanations.

Navigating the Maze of ChatGPT Models

OpenAI’s ChatGPT has come a long way, but its multitude of models has left many users scratching their heads. If you’re still confused about which version of ChatGPT to use for what task, you’re not alone! Luckily, OpenAI has stepped in with a handy guide that outlines when to choose one model over another. Whether you’re an enterprise user or just getting started, this breakdown will help you make sense of the options at your fingertips.

So, Which ChatGPT Model Makes Sense For You?

Currently, ChatGPT offers five models, each suited to different tasks. They are:

GPT-4o – the “omni model”
GPT-4.5 – the creative powerhouse
o4-mini – the speedster for technical tasks
o4-mini-high – the heavy lifter for detailed work
o3 – the analytical thinker for complex, multi-step problems

Which model should you use?

Here’s what OpenAI has to say:

GPT-4o: If you’re looking for a reliable all-rounder, this is your best bet. It’s perfect for tasks like summarising long texts, brainstorming emails, or generating content on the fly. With its multimodal features, it supports text, images, audio, and even advanced data analysis.
GPT-4.5: If creativity is your priority, then GPT-4.5 is your go-to. This version shines with emotional intelligence and excels in communication-based tasks. Whether you’re crafting engaging narratives or brainstorming innovative ideas, GPT-4.5 brings a more human-like touch.
o4-mini: For those in need of speed and precision, o4-mini is the way to go. It handles technical queries like STEM problems and programming tasks swiftly, making it a strong contender for quick problem-solving.
o4-mini-high: If you’re dealing with intricate, detailed tasks like advanced coding or complex mathematical equations, o4-mini-high delivers the extra horsepower you need. It’s designed for accuracy and higher-level technical work.
o3: When the task requires multi-step reasoning or strategic planning, o3 is the model you want. It’s designed for deep analysis, complex coding, and problem-solving across multiple stages.

Which one should you pick?

For $20/month with ChatGPT Plus, you’ll have access to all these models and can easily switch between them depending on your task.

But here’s the big question: Which model are you most likely to use? Could OpenAI’s new model options finally streamline your workflow, or will you still be bouncing between versions? Let me know your thoughts!

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What is ChatGPT Plus?
ChatGPT Plus and Copilot Pro – both powered by OpenAI – which is right for you?
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Neuralink Brain-Computer Interface Helps ALS Patient Edit and Narrate YouTube

Neuralink enabled a paralysed ALS patient to use a brain-computer interface to edit a YouTube video and narrate with AI.

Published

2 days ago

May 8, 2025

AIinAsia

TL;DR — What You Need to Know:

Bradford Smith, diagnosed with ALS, used Neuralink’s brain-computer interface to edit and upload a YouTube video, marking a significant milestone for paralyzed patients.
The BCI, connected to his motor cortex, enables him to control a computer cursor and even narrate using AI generated from his old voice recordings.
Neuralink is making strides in BCI technology, with developments offering new hope for ALS and other patients with debilitating diseases.

Neuralink Breakthrough: Paralyzed Patient Narrates Video with AI

In a stunning development that combines cutting-edge technology and personal resilience, Bradford Smith, a patient with Amyotrophic Lateral Sclerosis (ALS), has made remarkable strides using Neuralink’s brain-computer interface (BCI). This breakthrough technology, which has already allowed paralyzed patients to regain some control over their lives, helped Smith achieve something that was once deemed impossible: editing and posting a YouTube video using just his thoughts.

Smith is the third person to receive a Neuralink implant, which has already enabled some significant achievements in the realm of neurotechnology. ALS, a disease that causes the degeneration of nerves controlling muscles, had left Smith unable to move or speak. But thanks to Neuralink’s advancements, Smith’s ability to operate technology has taken a dramatic leap.

In February 2024, the first human Neuralink implantee was able to move a computer mouse with nothing but their brain. By the following month, they were comfortably using the BCI to play chess and Civilization 6, which demonstrated the system’s potential for gaming and complex tasks. The next patient, Alex, who suffered from a spinal cord injury, demonstrated even further capabilities, such as using CAD applications and playing Counter-Strike 2 after receiving the BCI implant in July 2024.

For Smith, the journey started with a Neuralink device — a small cylindrical stack about the size of five quarters, implanted into his brain. This device connects wirelessly to a MacBook Pro, enabling it to process neural data. Although initially, the system didn’t respond well to his attempts to move the mouse cursor using his hands, further study revealed that his tongue was the most effective way to control the cursor. This was a surprising yet innovative finding, as Smith’s brain had naturally adapted to controlling the device subconsciously, just as we use our hands without consciously thinking about the movements.

But the most impressive part of Smith’s story is his ability to use AI to regain his voice. Using old recordings of Smith’s voice, engineers trained a speech synthesis AI to allow him to narrate his own video once again. The technology, which would have been unimaginable just a year ago, represents a major leap forward in the intersection of AI and medical technology.

Beyond Neuralink, the field of BCI technology is rapidly advancing. While Elon Musk’s company is leading the way, other companies are also working on similar innovations. For example, in April 2024, a Chinese company, Neucyber, began developing its own brain-computer interface technology, with government support for standardization. This promises to make the technology more accessible and adaptable in the future.

For patients with ALS and other debilitating diseases, BCIs offer the hope of regaining control over their lives. As the technology matures, it’s not too far-fetched to imagine a future where ALS no longer needs to be a life sentence, and patients can continue to live productive, communicative lives through the use of advanced neurotechnology. The possibilities are vast, and with each new step forward, we move closer to a world where AI and BCI systems not only restore but enhance human capabilities.

Watch the video here:

Could this breakthrough mark the beginning of a future where paralysed individuals regain control of their lives through AI and brain-computer interfaces?

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