The AI show — don’t just watch, perform!

The Promise and Pitfalls of AI

AI is omnipresent these days, influencing everything from coding to creating art. But is it living up to its hype? Many of us have used tools like ChatGPT and have seen both their potential and limitations. My coworker once said, “It works, but it’s basically broken up.” She was actually talking about a new feature in the app we were working on, but it fits modern AI perfectly too.

Consider the story of a junior developer, let’s call him Elon. Fresh into his dream job, he eagerly embraced AI tools like ChatGPT for his programming tasks. Copy-pasting code snippets from AI, he appeared efficient and productive. However, during code reviews, Elon struggled to explain the AI-generated logic, leading to self-doubt. His experience highlights the challenges and opportunities AI presents in our jobs. Let’s leave him in this unfortunate situation for a moment, and deep dive into some trends in AI, let’s see what’s happening in IT world, and discuss what we can do to stay relevant in this AI era.

Made with chatGPT 4o

AI’s Impact on the Workforce

AI as the New Developer

AI tools are becoming increasingly adept at coding. Google’s Gemini 1.5 models are a prime example, efficiently writing code and assisting developers. Many developers use tools like ChatGPT or Copilot as coding companions. While AI-generated code is not always perfect, especially for complex projects, it excels at writing boilerplate code, generating test data, and identifying simple bugs. Each iteration brings improvements, making these tools increasingly valuable.

Multimodal AI as the Personal Assistant

AI is also transforming personal assistance by handling multiple types of input simultaneously. Google’s Gemini Nano on Pixel devices can process text, images, sound, and spoken language, making your phone smarter. Imagine your phone summarizing a recorded meeting or transcribing an interview while you focus on other tasks. This capability enhances productivity and simplifies complex workflows. And all of this without the need for an internet connection, as the Nano model lives on the device.

Generative AI as the Content Creator

Generative AI is revolutionizing creativity. It can produce media that rivals human-made content, from photorealistic images to original music and literature. You can even create photorealistic images of dolphins riding a bike! As amazing as this technology is, we also need regulations to protect creators and ensure everything is done ethically. It’s crucial to balance innovation with responsibility to make sure the benefits of generative AI are enjoyed by everyone in a fair and ethical manner.

Keys to Responsible AI

Building Ethical AI

Ethical AI development is paramount. Google’s AI principles emphasize making AI socially beneficial, avoiding unfair bias, ensuring safety, and respecting privacy. These guidelines remind us that just because we can build something doesn’t mean we should — unless it’s exceptionally cool, of course (Nah, just joking…).

Protecting Data Privacy

Data privacy is a significant concern. Despite assurances from companies like OpenAI, skepticism remains due to past practices of training models on unapproved data. Technologies like end-to-end encryption and on-device processing keep your data secure. Differential privacy, which adds random noise to data, ensures individual details remain private while still extracting useful insights.

Ensuring AI Transparency

One of the biggest challenges with AI is that it often operates like a black box, making decisions without any clear explanation. This lack of transparency can be frustrating and concerning. Think about it: when we visit a doctor or a lawyer, we probably want to know their reasoning. So, what can you do about it? When asking AI for something, also ask for the reasoning or step-by-step thinking behind the answer. This way, you can ensure AI’s decisions are clear and accountable. Plus, it’s proven that when AI explains its reasoning, the results are usually better, and hallucinations occur less often.

Strategies to Thrive in the AI Era

Embrace No-Code/Low-Code Tools

No-code and low-code platforms empower anyone to build applications without extensive coding knowledge. Tools like Google AppSheet, Make, and Zapier allow you to automate tasks and enhance productivity. These platforms offer numerous templates to explore and utilize, making it easier to integrate automation into your workflow. After years of promises, programming is now really drag and drop.

Prioritize Lifelong Learning

Continuous learning is essential in the rapidly evolving AI landscape. Experimenting with new tools and staying updated with the latest advancements is crucial. While courses and certifications are beneficial, practical experience and curiosity are key to mastering new technologies. For developers, learning has always been crucial, but now it’s a part of our everyday routine.

Focus on Domain Mastery

Understanding domain-specific problems is invaluable. Such expertise allows you to bridge the gap between technology and business, making you indispensable in your field.

The CEO of NVIDIA, Jensen Huang, once said:

‘The people that understand how to solve a domain problem in digital biology or in education of young people or in manufacturing or in farming, those people who understand domain expertise now can utilize technology that is readily available to you.’

So, as I say it (in a much more straightforward way) — we may not paddle the boat, but we still need to decide where it’s going. As developers, our role is to translate client needs to (AI and non-AI) solutions and ensure we meet ethical standards while doing this. Technology can do amazing things, but it’s up to us to define the ‘what’ and ‘why.’

Conclusion

Let’s go back now to our junior developer, Elon. What can he do to adapt to AI’s evolving landscape and enhance his value? By embracing no-code tools, committing to lifelong learning, and developing domain expertise, individuals like him — and you — can significantly enhance their value. The question now is — do you want to be an observer in the AI revolution or an active participant? Don’t just watch the AI show — perform! The choice is yours.

Please find below some links to the tools and knowledge sources I mentioned in the article:

1. GDG 3City website: https://gdg.community.dev/gdg-3city/
2. ChatGPT: https://chatgpt.com/
3. Gemini 1.5: https://blog.google/technology/ai/google-gemini-next-generation-model-february-2024/#sundar-note
4. Gemini Nano: https://deepmind.google/technologies/gemini/nano/
5. Suno, for creating music with AI: www.suno.com
6. Google AI Principles: https://ai.google/responsibility/principles/
7. Make, to automate your work: https://www.make.com/en
8. Zapier, for some more automation: https://zapier.com/
9. Google Sheets: https://workspace.google.com/products/sheets/
10. IFTTT, pioneer in automation: https://ifttt.com/
11. “Don’t learn to code” video: https://www.youtube.com/watch?v=vEd-LqBCONg