The DJ who's not a DeeJay

Through the years, I’ve had my share of attending conferences, webinars, and talks from experts and professionals in their fields. Just recently, though, I enrolled in a MOOC (Massive Open Online Course) on "Ethics of AI" as part of the Bachelor's Program in Computer Science at the University of Helsinki. It was exciting to be a student again, even if it’s only online.

I’ve been using AI for a few years now and became familiar with the different ways and strategies it can supplement my content creation and creativity. Some of my previous graphic and video creations have led to online discussions on AI, tagging it as AI slop, or basically, lazily low-quality output generated by AI. I wanted to learn more about why AI-assisted or generated content was frowned upon. I researched online to find out why, but a few articles and community threads didn’t quite give a definitive answer.

It was until I discovered this online course on the Ethics of AI, which I figured would help me better understand AI from behind the scenes and at its core. I’m already an end-user but wanted to know how the developers and stakeholders of AI software program their applications.

As I went through this course, I realized that there is much more than just the scientific, technical, and computing aspects of AI. AI is profoundly intertwined with our values, our societies, and our future. Philosophy wasn’t my favorite course in college, but little did I know that philosophical concepts and ideologies would be a part of providing a direction for understanding, programming, and integrating AI into our lives.

For computers, data is king. But the human component and personal identifiers, such as age, race, gender, and religion, could easily cause AI to discriminate if human values aren’t integrated into any AI product. AI should ensure that equality is observed and integrated from the computing and programming side to the end user.

Here are some of the areas that really resonated with me:

• Understanding What AI Really Is (and Isn't): The course provided a crucial foundation, dispelling common myths and giving a realistic picture of current AI capabilities. This grounded understanding is essential before diving into the ethical dilemmas. You can't discuss the ethics of something you don't truly comprehend.
• The Power of Data and the Challenge to Eliminate Bias: A significant portion of the course, as suggested by the module titles, likely delved into how data fuels AI. This is where ethics become incredibly tangible. If the data used to train an AI system is biased, the system itself will perpetuate and even amplify those biases. Such bias can lead to unfair or discriminatory outcomes in areas like hiring, lending, or even criminal justice. It's a solid reminder that "objective" algorithms can still produce highly subjective and harmful results if their foundational data is flawed.
• Transparency, Accountability, and Explainability: As AI systems grow more complex, the "black box" problem becomes a real concern. How do we ensure these systems are making fair decisions if we can't understand how they arrived at them? The course explored the importance of transparency in AI development, the need for clear lines of accountability when things go wrong, and the push for an audit trail, or explainable AI (XAI)—systems that can articulate their reasoning in a human-understandable way.
• Who Decides? The Importance of Ethical Frameworks: Perhaps one of the most crucial lessons is that there are no easy answers. The course undoubtedly presented various ethical frameworks and principles that can guide the development and deployment of AI. This course isn't about prescribing a single "right" way but rather about fostering critical thinking and equipping individuals to participate in the ongoing dialogue about what kind of AI society we want to build. This includes discussions around privacy, security, and human control.
• The Future is Now: Why This Matters to All of Us: The "Ethics of AI" isn't a theoretical exercise for some distant future. It's about the tools we are building and using right now. From self-driving cars to AI in healthcare, the ethical considerations are immediate and impactful. The course effectively communicates that ethical considerations should be tightly woven into the AI development process from the very beginning, not just as an afterthought.

Completing this course has made me realize that ethical AI isn't a niche concern; it's a fundamental pillar of responsible technological advancement. As AI continues to evolve at an astonishing pace, engaging in these conversations and demanding ethical practices from developers and policymakers alike will be crucial for ensuring AI serves humanity for the better.

And after spending a few hours every morning, I finally completed and passed this course. I honestly felt excited and honored, especially when I received the online certificate from an actual university, not to mention a prestigious one in Finland.