We talk a lot about AI being “fair,” “transparent,” or “aligned.” But two of the most important issues in AI get barely any real attention:

**1. Who Actually Controls AI?**

Most powerful AI systems are built by a tiny group of companies that control the compute, the data, and the cloud. They decide:

\- What gets built

\- Who gets access

\- What trade-offs are “worth it”

We almost never hear about how concentrated this power is. AI isn’t just about tech — it’s about who benefits, who gets left out, and who calls the shots.

👾 **Example**: AI systems that shape financial markets, hiring decisions, or policing aren’t just tools. They’re actors in the society, reinforcing existing power structures.

**What we should be asking:**

\- Are we building AI to maximize profit, or to serve society?

\- Who gets to decide how these systems work?

**2. Can You Really Consent to Something You Can’t See?**

Most AI is powered by your data — collected from phones, apps, cameras, smart devices. But:

\- We often don’t know it’s happening

\- We can’t really opt out

\- And “consent” (like cookie popups) is not really that

👾 **Reality**: We can’t meaningfully consent to something if we don’t understand it or have no other choice. AI needs data to work — but should it come at the cost of user agency and autonomy?

**Why These Two Issues Are Connected**

\- The same companies that control the infrastructure are the ones collecting all the data

\- Companies set the rules — and users accept the rules

\- AI ethics talks about AI model fairness, but ignores foundational power dynamics

**So What Do We Do?**

We need to go beyond buzzwords and ask more specific questions:

\- How do we build AI that people can actually say *no* to?

\- What would it mean to *share control* over data and infrastructure?

\- Can we design AI systems that don’t rely on mass *surveillance*?

\- What’s the real missing piece in *AI governance* today?

\- Have you seen AI systems that genuinely respect *consent* or challenge *centralization*?

Two Things We Keep Ignoring in AI Discourse