Blog | Dominic Santschi | Website

ChatGPT (or AI) Hushing: The Last Resort to Justify our Employment?

Tue, 09 Dec 2025 00:00:00 +0000

ChatGPT (or AI) Hushing: The Last Resort to Justify our Employment?

“Can it be a crime if everyone does it?” That’s the question that popped into my head when I first started noticing how people were quietly using ChatGPT and other AI tools while pretending they weren’t. It’s like we’re all in on this secret, but nobody wants to admit it out loud.

The AI Washing to Hushing Shift

Remember the early days of AI hype? Companies were slapping “AI-powered” on everything like it was a magic sticker that made investors drool. We’ve all seen it: “AI washing,” as the folks at Corrs call it, where businesses inflate their AI capabilities to snag attention or cash (Corrs: AI washing and cyber washing). But here’s the twist, those overblown claims are starting to fizzle out. People aren’t biting as hard anymore.

What really counts now is actual value and user experience. Does the AI tool actually solve problems without making you want to pull your hair out? For the average person, the tech under the hood is about as interesting as watching paint dry. If a tool gets the job done efficiently, who cares if it’s AI or a team of elves?

But this shift from AI washing to AI hushing creates an interesting paradox. While companies were once exaggerating their AI use to impress, now we’re seeing the opposite: people quietly using AI tools while pretending they aren’t. It’s like we’ve collectively decided that admitting AI use somehow diminishes our human value.

With ChatGPT and AI tools, it feels like we’re jumping straight into the hushing phase. We’re not pretending AI doesn’t exist or that we’re using it when we’re not. Instead, we’re often just… not talking about it. At all.

This phenomenon isn’t new in the business world. In management accounting literature, there’s plenty of research about “performance overreporting” - where managers inflate their achievements to look better. But with AI, we’re seeing the opposite: underreporting of AI use. A recent SSRN paper by Yier Ling, Alex Kale, and Alex Imas explores this exact issue, calling it the “social desirability bias” - our tendency to present ourselves in ways that make us look good to others.

The paper, titled “Underreporting of AI Use: The Role of Social Desirability Bias” (September 2025), argues that we’re actively hiding our AI usage because it threatens our sense of human value. If AI can do the work, what does that say about us? Are we trying to justify our existence at work by pretending we’re still doing everything the “human” way?

I think that’s exactly what’s happening. There’s more at stake for employees than in previous workplace transformations. We need to feel like our contributions matter, like our expertise and creativity still count for something. Admitting we use AI feels like admitting defeat - like we’re not as smart or capable as we want others to believe.

Spotting and Hiding AI Use

Before we dive into the examples, let me be clear: I used AI to write this post and spend two hours customizing it. AI is such a powerful tool that can produce incredible outputs. But creating meaningful outcomes? That’s still very much in our hands. For beginners looking to navigate this space, here are a few things to watch out for. AI isn’t too complicated to spot if you know what to look for, but it’s also not something we should fear.

Examples of AI Hushing in Action

1. The Text Game

Let’s start with the most obvious: ChatGPT’s infamous em-dash usage. You know, those awkward dashes that appear in generated text —— it’s like the AI’s signature move. A Medium post by Brent Csutoras explores this signature quirk in detail.

How to spot it: Look for unnatural phrasing and over-polished language that feels too perfect. Tools like the Fluff-o-Meter can help detect AI-generated text quirks.

How to hide it: Manually edit out hyphens and add personal anecdotes or imperfections to make it feel more human.

But here’s the thing - is this really a problem? Most of us consume content on platforms like LinkedIn for entertainment and networking, not for deeply researched analysis. For that, we turn to other sources. A study published in The International Journal of Press/Politics about AI in news reporting found that while AI can generate content quickly, human oversight is crucial for accuracy and context.

2. Emoji Overload

Emojis have made a comeback thanks to ChatGPT. They’re everywhere in generated text, making everything feel a bit more… visual.

How to spot it: Excessive or awkwardly placed emojis that don’t quite fit the context. AI tends to sprinkle them liberally to add “personality.”

How to hide it: Use emojis sparingly and purposefully, or remove them entirely if they feel forced. However, they can actually enhance readability when used well.

Maybe emojis aren’t the enemy. They help break up text and add personality. In a world of endless scrolling, that visual element might be exactly what keeps people reading.

3. The Vibecoding Revolution

Then there’s the coding world. Tools like Lovable, Bolt, and V0 are revolutionizing web development. Using React and Next.js frameworks, they let anyone create professional-looking websites.

How to spot it: Websites that look remarkably similar in structure and styling, often with generic layouts and components.

How to hide it: Customize the generated code extensively, add unique features, and integrate your project with external services to differentiate your project. I am a vibe coder myself - check out some my projects like reference-analyzer.com that started with AI support but were heavily customized.

But here’s the catch: everything starts looking the same. For venture capitalists, this raises questions. Will startups built with “vibecoding” get discounted compared to those with senior developers? Probably, unless they show real traction. And let’s not forget security and data compliance - areas where many vibe coders have zero expertise.

4. Imagery and Authenticity

Finally, there’s the imagery debate. At what point can a company claim in their CSR report that they used real human photographers instead of AI-generated images?

How to spot it: Images that look too perfect or generic, lacking the authentic imperfections of real photography.

How to hide it: Clearly disclose AI use in reports, or combine AI-generated images with human-created content. A NZZ article explores how AI is changing creative professions in advertising.

For individuals, AI-generated content (often called “AI slop”) serves a purpose too. Its absurdity helps us slow down and appreciate real creativity. This Guardian article and another Guardian article have discussed this in more detail.

Creating a Culture of Clarity

So where does this leave us? AI hushing isn’t just about hiding our tools - it’s about preserving our sense of purpose. We’re in a transitional period where technology is reshaping how we work, and it’s scary. By not talking about AI, we’re trying to maintain the illusion that human creativity and expertise still reign supreme.

But maybe that’s the wrong approach. Instead of hushing, what if we embraced transparency? What if we celebrated how AI amplifies our capabilities rather than replaces them? The real value we bring isn’t in generating outputs - it’s in curating them, contextualizing them, and turning them into meaningful outcomes.

Most importantly, organizations need to create clear cultures around AI use. If AI is prohibited due to confidentiality or data sensitivity concerns, usage should be monitored and sanctioned when rules are broken. However, if your environment has no downside to AI use, it’s crucial to communicate an open AI culture so people can speak freely about their AI usage instead of having to hide it. This transparency reduces the social desirability bias and allows everyone to focus on what really matters: delivering value through human-AI collaboration.

As we navigate this AI-driven world, let’s remember: the tools don’t define us. Our choices do. And choosing to be honest about how we work might just be the most human thing we can do.

What do you think? Are you hushing your AI usage at work, or are you being open about it? I’d love to hear your perspective…

What Enterprise Risk Manager Type Are You?

Sun, 26 Oct 2025 00:00:00 +0000

What Enterprise Risk Manager Type Are You?

Enterprise Risk Management isn’t one-size-fits-all. Based on the ISO 31000 framework’s core principles, we’ve identified four distinct ERM leadership styles. Each type brings unique strengths to risk management and benefits from different development approaches.

The Four ERM Types

🎯 The Strategic Risk Leader

Focus: Integrating risk management into organizational strategy and governance

Strategic Risk Leaders excel at board-level influence and strategic alignment. They thrive in environments where they can shape organizational direction and elevate risk discussions to strategic importance. Their natural ability to connect risk management with business strategy makes them invaluable advisors to C-suite executives.

Key Strengths:

Strong presence in executive and board-level discussions
Ability to translate complex risks into strategic implications
Focus on long-term organizational resilience and competitive positioning
Leadership orientation toward governance and accountability

⚙️ The Process Architect

Focus: Creating structured, systematic approaches to risk management

Process Architects thrive on designing frameworks, implementing standards like ISO 31000, and ensuring consistent risk assessment across the organization. They value methodology, documentation, and proven practices that deliver reliable results.

Key Strengths:

Excellence in developing and implementing risk frameworks
Strong analytical and technical risk assessment capabilities
Detail-oriented with focus on documentation and compliance
Ability to create consistency and quality across risk processes

💎 The Value Optimizer

Focus: Creating and protecting organizational value through risk management

Value Optimizers see risk management fundamentally as about demonstrating ROI, linking risk to business performance, and making risk-informed decisions that optimize outcomes. They excel at showing the business case for risk management investments.

Key Strengths:

Strong business and commercial acumen
Ability to quantify risk in financial terms
Focus on performance optimization and value creation
Skill in balancing risk-taking with risk mitigation

🌟 The Culture Champion

Focus: Building risk-aware cultures through engagement and behavior change

Culture Champions understand that effective risk management is fundamentally about people, culture, and behavior. They excel at engaging stakeholders, facilitating collaboration, and transforming how organizations think about risk.

Key Strengths:

Exceptional stakeholder engagement and communication skills
Collaborative and inclusive leadership approach
Natural ability to build consensus across diverse groups
Change management and transformation orientation

Discover Your Type

Take our interactive quiz below to discover your ERM type and get personalized recommendations for your professional development, including which seminar format best suits your learning style and career goals.

Why Understanding Your Type Matters

Knowing your ERM leadership style helps you:

Play to your strengths while addressing development areas
Choose the right seminars and professional development opportunities that match your learning preferences
Build complementary teams with diverse ERM perspectives
Communicate more effectively with stakeholders who have different styles
Accelerate your career by focusing on development that aligns with your natural tendencies

Developing Beyond Your Type

While we all have natural tendencies, the most effective ERM professionals can adapt their approach to different situations:

Strategic Risk Leaders should develop operational implementation skills and detailed process knowledge
Process Architects benefit from enhancing communication skills and strategic business acumen
Value Optimizers should strengthen stakeholder engagement and culture development capabilities
Culture Champions gain from building analytical and structured assessment skills

Our ERM Seminars

Both of our University of St.Gallen ERM seminars cover the full spectrum of risk management, but the format and focus areas differ:

Leading Enterprise Risk Management (On-Site)

3-day intensive program | February 2026 | St.Gallen, Switzerland

Perfect for professionals who want:

Deep immersion with face-to-face learning
Direct access to Prof. Dennis Fehrenbacher and senior executives
Meaningful peer networking and relationship building
Intensive case discussions and strategic dialogue
Transformative learning experiences

Investment: CHF 3,000
Learn more →

Risk Management Online Seminar

5-day online program | September/October 2026

Ideal for professionals who need:

Flexibility to balance learning with work commitments
Structured curriculum with comprehensive materials
Time to digest and apply learnings progressively
Cost-effective path to HSG credentials
Interactive online sessions with peer learning

Investment: CHF 1,900
Learn more →

What You’ll Learn

Both seminars provide comprehensive coverage of:

ISO 31000 Framework: Deep dive into principles, framework, and process
Strategic Risk Management: Connecting risk to organizational strategy and value
Risk Assessment Methods: Quantitative and qualitative techniques
Risk Culture & Behavior: Building risk-aware organizations
Governance & Oversight: Three lines of defense and risk governance
Emerging Risks: Identifying and managing future uncertainties
Practical Application: Real-world case studies and implementation frameworks

Get Personalized Recommendations

Take the quiz above to receive tailored recommendations based on your:

ERM leadership type
Learning preferences (on-site vs. online)
Career development goals
Specific skill development needs

The quiz takes just 5 minutes and provides detailed insights into which seminar format will deliver the most value for your professional development.

Ready to Advance Your ERM Career?

Whether you’re a Strategic Risk Leader seeking board-level influence, a Process Architect wanting to master ISO 31000, a Value Optimizer looking to demonstrate ROI, or a Culture Champion focused on transformation—we have a program designed for your success.

Questions about which program is right for you?
Feel free to reach out to discuss your development goals and how our ERM seminars can help you achieve them.

Both seminars are offered by the University of St.Gallen Executive School and led by Prof. Dr. Dennis Fehrenbacher, member of the ISO 31000 committee. All participants receive a University of St.Gallen certificate upon completion.

Create your AI-driven Value Proposition Canvas

Fri, 08 Aug 2025 00:00:00 +0000

I forked a public GitHub Repo to generate interview data for sensitive topics. These data could not be gathered from humans, because the questions of interest were too emotionally loaded for the target segment. After generating the data, I coded the insights and illustrated them on a Value Proposition Canvas

In this article, I will share my playbook on how to use LLMs for interview data generation and illustrate insights on a VP Canvas.

Step 1: Generate Interview Data with LLMs

I forked a public GitHub Repo to generate interview data for sensitive topics. The repo is built to run on local LLMs. I used [Ollama] (https://ollama.com/) to run the LLMs locally. The repo contains a script that generates interview data based on a set of questions. You can customize the questions to fit your research needs.

After setting up the repo, I ran the application via Docker in my localhost to generate interview data. To vary the responses, I used different prompts. Here is an example of a prompt I used:

{
 "prompt": "Welcome to our discussion on how we envision a service that supports those who have just lost their partner — by helping them manage the many administrative tasks that follow, from paperwork and account closures to official notifications."
}

Demo Video:

Here’s a demo video of the application in action: Download and watch the video

I exported the interview transcripts as a .docx file, which I then used for further analysis.

Step 2: Analyze Interview Data

I used ATLAS.ti to analyze the interview data. I AI coded the transcripts to identify key insights and themes. The coding process involved reading through the transcripts, highlighting important quotes, and assigning codes to them. This helped me to organize the data and identify patterns.

Once done, I exported the coded data as a .xls file, which I then used to create the Value Proposition Canvas.

Step 3: Classify the Codes into VP Canvas Categories

I used the .xls file to classify the codes into the categories of the Value Proposition Canvas. The categories include:

Customer Jobs: What the customer is trying to achieve.
Pains: The challenges or obstacles the customer faces.
Gains: The benefits or positive outcomes the customer seeks.
Products & Services: The offerings that can help the customer achieve their jobs.
Pain Relievers: How the products and services can alleviate the pains.
Gain Creators: How the products and services can create gains for the customer.

Step 4: Create Wordclouds for the VP Canvas

I used this open-source Wordcloud Generator to copy paste the codes from the .xls file into the wordcloud generator. This helped me visualize the most frequently mentioned words in each category, making it easier to identify key insights.

Et voilà! I had a visual representation of the insights from the interview data on a Value Proposition Canvas.

Blog | Dominic Santschi | Website

ChatGPT (or AI) Hushing: The Last Resort to Justify our Employment?

ChatGPT (or AI) Hushing: The Last Resort to Justify our Employment?

The AI Washing to Hushing Shift

The Social Desirability Bias Factor

Spotting and Hiding AI Use

Examples of AI Hushing in Action

1. The Text Game

2. Emoji Overload

3. The Vibecoding Revolution

4. Imagery and Authenticity

Creating a Culture of Clarity

What Enterprise Risk Manager Type Are You?

What Enterprise Risk Manager Type Are You?

The Four ERM Types

🎯 The Strategic Risk Leader

⚙️ The Process Architect

💎 The Value Optimizer

🌟 The Culture Champion

Discover Your Type

Why Understanding Your Type Matters

Developing Beyond Your Type

Our ERM Seminars

Leading Enterprise Risk Management (On-Site)

Risk Management Online Seminar

What You’ll Learn

Get Personalized Recommendations

Ready to Advance Your ERM Career?

Create your AI-driven Value Proposition Canvas

Step 1: Generate Interview Data with LLMs

Step 2: Analyze Interview Data

Step 3: Classify the Codes into VP Canvas Categories

Step 4: Create Wordclouds for the VP Canvas

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