AI Should Serve Society - Not Just Industry and Billionaires

Source: Dev.to

Introduction

Build with purpose. Others will follow.

AI is moving fast—faster than our laws, ethics, and often our collective sense of responsibility. The real question isn’t how powerful AI can become; it’s who it actually serves.

Right now, most AI innovation is optimized for three things: scale, profit, and market dominance. That isn’t inherently wrong—businesses need to grow—but it’s incomplete. When AI serves only industry titans and billionaires, we miss its most profound potential: uplifting society at large.

Technology Is Never Neutral

We must stop pretending that algorithms are objective. Every model we train, dataset we curate, and deployment strategy we choose reflects a human choice.

• What problem are we solving?
• Who actually benefits from this solution?
• Who gets left behind?

Designing purely for efficiency or revenue steers technology toward those who already have money and power. Society’s hardest problems—accessibility, safety, healthcare gaps, educational inequality, and the climate crisis—rarely sit at the top of a revenue roadmap. This is why leadership matters.

Using AI for Society Is a Choice

Building AI for social good doesn’t mean abandoning technical excellence. It means redirecting brilliance with intention.

True leadership—whether you’re an engineer, researcher, or founder—isn’t about who builds the biggest model. It’s about:

• Choosing problems that matter, even if they don’t scale immediately.
• Designing systems people can understand and trust, rather than black boxes that alienate them.
• Measuring success by community impact, not just valuation.

How We Actually Do This

Turning an abstract ideal into reality starts by getting out of the bubble:

1. Build from real human pain points, not tech‑first ideas looking for a problem.
2. Collaborate outside the tech echo chamber—sit down with educators, doctors, and community leaders who understand the nuance of the problems.
3. Design for constraints and accessibility, not just for the ideal user with the fastest internet connection.

Sometimes the most revolutionary thing you can do is ship a smaller, focused solution that solves one real problem incredibly well.

Building Where Nothing Existed: A Personal Example

My team and I experienced this firsthand when we built OmniSign.

We identified a massive gap in accessibility for the Deaf community in Lebanon—no real‑time tool to bridge the communication barrier. The market hadn’t deemed a Lebanese Sign Language dataset “profitable enough,” so none existed.

Instead of stopping, we:

• Created the dataset from scratch.
• Developed a model to translate Lebanese Sign Language in real time.

We didn’t wait for permission or big tech; we built because it was necessary.

For more insight, visit the official project website.

The Kind of AI We Should Be Proud Of

The AI worth building isn’t just faster—it’s safer. It doesn’t blindly replace people; it empowers them. It reaches those usually written off as “not the target market.” This isn’t about rejecting industry; it’s about expanding our definition of responsibility.

Final Thought

AI will shape society whether we intend it to or not. The difference between a future of exploitation and one of empowerment is who leads the conversation.

If you are building AI today, you are already shaping that future. The real power move isn’t optimizing for the top 1 %; it’s choosing to build for the rest of us.

Build with purpose. Others will follow.