My Journey to Explain AI Ethics – And Why It’s Harder Than I Thought

Okay, so here I am in Berlin. Six months now, and I’m finally starting to feel… settled? Not completely comfortable, obviously – there are still days where I fumble over ordering a coffee or completely misunderstand the cashier at the Edeka (that’s a supermarket, you know). But I’m improving, and I’m really trying to use my German every day. My job is as an assistant in a small marketing agency – mostly administrative tasks, but it’s enough to keep me going, and more importantly, it forces me to communicate.

Right now, I’m working on this TELC B1.2 writing exam, and they want us to write about ethical challenges of… well, basically what we all see everywhere – artificial intelligence. It sounds super complicated, right? Honestly, at first, it felt overwhelming. But I’ve realized it’s not actually that different from just talking about something with my colleagues here in Germany – you just need to find the right words and be clear.

The Assignment: “Die ethischen Herausforderungen der KI erklären” (Explain the ethical challenges of AI)

The prompt was pretty specific. I had to explain, in writing, what I thought were some key problems with how artificial intelligence is being developed and used. It felt a bit like trying to explain something simple – maybe over-complicated it at first. My tutor, Frau Schmidt, kept saying, “Konzentriere dich! (Focus!)” which, let’s be honest, was incredibly helpful when I was getting lost in all the different arguments.

First Attempts & Misunderstandings

My first draft was… a mess. It was full of phrases like “artificial intelligence is complex” and “it’s important to consider…” It sounded robotic, and honestly, not very convincing. I even tried using some complicated German vocabulary I’d learned from my textbook – ‘algorithmische Verzerrung’ (algorithmic bias) – but then I realized nobody in the office would understand me!

I was talking to Karl-Heinz, one of the senior marketers, about it and he said, “Ach, du bist zu kompliziert! (Oh, you’re making this too complicated!).” He explained that Germans generally prefer straightforward explanations. He pointed out a small example – when I asked him for help with our company’s social media campaign, I used the phrase ‘die Zielgruppe segmentieren’ – meaning to segment the target audience – which he found unnecessarily formal and confusing. It’s more natural to say just “wir müssen unsere Kunden besser verstehen” (we need to understand our customers better).

Practical Examples & Conversation Starters

So, I started thinking about things I actually saw and discussed. One thing that really bothered me was seeing how some companies use AI-powered chatbots for customer service. They seemed so… impersonal! I had a conversation with my neighbour, Ingrid, who works in customer support for an insurance company. She told me: “Manchmal ist es besser, wenn ein Mensch mit einem Kunden spricht. Die Chatbots sind oft sehr unhöflich und können die Probleme nicht richtig lösen.” (Sometimes it’s better if a person speaks to a customer. The chatbots are often very rude and can’t solve the problems properly.) That gave me an idea for my writing: I could talk about that lack of empathy and how it’s potentially harmful.

Another thing I thought about was data privacy. My friend, David (he’s studying computer science), explained to me in simple terms how companies collect information about people’s behaviour online – “Sie tracken uns! (They track us!)” – and uses that data to target ads. He said it feels a bit… creepy, ‘das ist ein bisschen unangenehm,’ (that’s a little uncomfortable).

Putting It All Together: A More Realistic Approach

I rewrote my piece completely. This time, I started with the simple conversation with Ingrid about the chatbots. Then, I added a paragraph explaining David’s concerns about data privacy, using his own words – ‘Er sagte, dass es ein Problem ist, wenn die Firmen so viele Daten über uns sammeln’ (He said it’s a problem when companies collect so much data about us).

I focused on making it clear and understandable. I avoided overly technical terms and used simple phrases like “Es ist wichtig, darüber nachzudenken” (It’s important to think about it) or “Wir müssen vorsichtig sein” (We need to be careful).

Key Phrases & Vocabulary

Here are some phrases that helped me a lot:

• “Ich finde, dass…” (I think that…) – Great for stating your opinion.
• “Es ist wichtig, … ” (It’s important to…) – Useful for introducing a key point.
• “Das ist ein Problem,” (That’s a problem) – Simple and direct.
• “Ich bin mir nicht sicher…” (I’m not sure…) – Shows you’re acknowledging complexities.

Next Steps

Frau Schmidt marked my piece as ‘gut’ (good). She said I had improved my clarity and used more appropriate vocabulary. It wasn’t perfect, of course – there’s always room for improvement. But it felt like a real step forward. More importantly, I learned that understanding the real challenges, and talking about them in a way people understand, is much better than just reciting textbook definitions.

Now, I need to keep practicing and building my vocabulary. Maybe next time, I’ll tackle something even trickier – like explaining the concept of “Big Data” to my Oma (grandma)! ‘Das wird sicher eine Herausforderung,’ (That will definitely be a challenge!).