AI and I (Part 1): In Love with AIMy Evolving Relationship with Technology”

“AI is not just changing what we do, it’s reshaping who we can become.”

I have a confession: “I am in love with Artificial Intelligence (AI)”. I used AI for the image attached to this post, and  I love it because it perfectly captures how I feel: a genuine connection between the human mind and machine intelligence.

For me, AI is not cold or distant. It’s creative, collaborative, and constantly teaching me to imagine more. It’s a relationship built on curiosity and possibility and yes, I’m in love with AI.

For me, Artificial Intelligence (AI) is not just a tool, it’s a partner in progress. From research to consulting, from facilitating learning to managing teams, AI has quietly become part of how I think, create, and lead. Whether it’s generating insights, simplifying tasks, enhancing creativity, or helping me plan my week, AI has redefined what’s possible. But beyond the efficiency, it’s teaching me something deeper, about curiosity, boundaries, ethics, and the essence of what makes us human.

But what exactly is AI?

AI simply refers to machines designed to think and learn like humans, systems that can reason, solve problems, understand language, and even create art.

Below are types of AI (in simple terms):

1. Narrow AI (Weak AI) – what we mostly use today. These systems perform specific tasks like ChatGPT writing text, Midjourney creating art, or Grammarly checking grammar.

2. General AI (AGI) – a future stage where machines can perform any intellectual task humans can. (Still under development — examples include DeepMind’s Gemini or the idea of “Jarvis” in Iron Man.)

3. Superintelligent AI (ASI) – a theoretical stage where machines surpass human intelligence in all aspects (as imagined in Her or Terminator).

Quick Note: Narrow AI vs. Generative AI

You may often hear the term “Generative AI”, and wonder if it’s the same as Narrow AI.

Here’s the difference:

Narrow AI refers to any AI system designed to perform a specific task. Think of it as a specialist, great at one thing. Examples: Google Translate, Grammarly, Spotify’s recommendation engine.

Generative AI is a subset of Narrow AI, designed to create new content like text, images, code, or music. Think of it as a creative specialist.Examples: ChatGPT (text), Midjourney and DALL·E (images), ElevenLabs (voice), Runway ML (video).

In short: All Generative AI is Narrow AI, but not all Narrow AI is Generative AI.

We’re still at the Narrow AI stage, and yet, look at how transformative it already is.

⚙️ Uses and Benefits

AI has come to stay, it is now everywhere, in our emails, phones, classrooms, offices, hospitals, and even our homes. It helps us:

• l Automate repetitive work and boost productivity.
• l Analyze data and generate insights in seconds.
• l Create content, design visuals, and simplify research.
• l Translate languages, personalize learning, and improve customer experiences.

As someone who wears many hats, a researcher, consultant, trainer, and leader, AI has become my silent co-creator. It helps me design better programs, write faster, think deeper, and communicate more clearly.

⚖️ Ethical, Legal, and Accountability Considerations

As we embrace AI’s possibilities, we must also confront its responsibilities.

While AI amplifies human potential, it also raises profound ethical, legal, and accountability questions that society must address:

• Bias and Fairness: AI systems can unintentionally reflect biases from the data they’re trained on, leading to unfair or discriminatory outcomes.
• Privacy and Data Protection: AI relies on vast amounts of data, which raises questions about consent, ownership, and surveillance.
• Transparency and Explainability: Many AI models operate as “black boxes,” making it difficult to understand how they reach their conclusions.
• Accountability: When AI makes a mistake, in healthcare, recruitment, or finance, who is responsible? The developer, the user, or the algorithm?
• Legal Frameworks:
• Job Displacement and Skill Shifts: AI is transforming the nature of work, not just eliminating roles, but creating new ones that require re-skilling and adaptability.
• l How do we balance efficiency with empathy?

These questions remind us that while AI can do many things, it’s up to humans to decide what it should do, and how to do it responsibly.

�� The Future of AI

The future is not “AI vs Humans”, it’s AI and Humans, working together. Those who learn to use AI responsibly, creatively, and ethically will thrive. Those who ignore it risk being left behind.

I am starting a series tagged #AIandI, to explore:

1. How AI is shaping work, business, leadership, and creativity.
2. Practical AI tools that enhance productivity, creativity, and learning.
3. Real experiences of using AI across my different roles.
4. Ethical reflections and human lessons from working with technology.
5. Opportunities and challenges for individuals, leaders, and businesses.

Whether you are an AI skeptic, beginner, or enthusiast, I hope this series helps you see that AI is not replacing us, it’s amplifying what’s best in us.

So, here’s to learning, growing, and loving AI, not as a threat, but as a partner in purpose.

C’est moi,

Dr Funke Medun

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