The Ethics of Artificial Intelligence: 7 Questions Every User Should Ask
Artificial intelligence is no longer something only scientists and engineers deal with — it’s in your phone, your search engine, your social feeds, your workplace, and even your kid’s homework helper. But as AI becomes more integrated into everyday life, it’s not just a question of what it can do, but what it should do.
AI isn’t neutral. Every system reflects choices made by its designers — choices about whose data to use, whose voices to prioritize, what values to optimize for, and what harms to accept. If we want to live in a world where AI serves people, not just profits, we all need to get a little more curious about the tech we use.
This article explores seven essential questions every AI user — whether a creator, student, worker, or everyday citizen — should be asking about the systems they rely on.
1. 🧭 Who Designed This AI — and Why?
Every AI system is built with goals in mind. Some are obvious, like helping users write faster. Others are less transparent, like maximizing ad engagement or gathering behavioral data.
Why it matters:
Understanding who benefits from an AI system’s design helps you figure out whose interests are being prioritized — and whose might be overlooked.
Ask yourself:
Was this tool made to help me, sell to me, or collect data from me?
Is the company behind it known for responsible tech development?
2. 📊 What Data Was It Trained On?
AI systems learn by processing vast amounts of data. If that data is biased, incomplete, or scraped without consent, the AI will reflect those problems — often in subtle or harmful ways.
Why it matters:
Training data shapes how AI sees the world. If certain communities, cultures, or dialects are underrepresented or misrepresented, the AI’s output will likely be skewed.
Ask yourself:
Where did this AI’s training data come from?
Were people’s rights respected in that process?
Is it likely the AI reflects the diversity of the real world?
3. 🧠 Is This AI Making or Replacing a Human Decision?
AI is increasingly used to make decisions that used to be made by humans: hiring, grading, moderating content, even diagnosing illness. The difference is, AI can do this at scale — and without human nuance.
Why it matters:
When AI replaces human judgment, it can remove empathy, context, and recourse from decision-making. It also makes errors harder to detect and challenge.
Ask yourself:
Is AI assisting or replacing a human?
Would I want a person or a machine making this kind of decision about me?
Is there a way to appeal or correct an AI-driven outcome?
4. 🔍 Can I Understand or Explain How It Works?
Many AI systems — especially deep learning models — are "black boxes." Even their creators can’t always explain why they make certain decisions. While full transparency isn’t always possible, users should still expect a level of clarity.
Why it matters:
When we can’t understand AI, we can’t question or challenge it. That’s dangerous — especially when AI is used in policing, medicine, or public services.
Ask yourself:
Is this AI explainable? Can I see how it got its results?
Does the company provide transparency or documentation?
Would I feel confident explaining this tool to someone else?
5. ⚖️ Who’s Accountable If Something Goes Wrong?
If an AI tool causes harm — gives bad advice, spreads misinformation, or makes a discriminatory decision — who is responsible? The user? The company? The algorithm?
Why it matters:
Without clear accountability, users are left vulnerable. Ethical AI means there’s a system in place for responsibility, redress, and correction.
Ask yourself:
If this AI makes a mistake, is there a way to report it?
Who is responsible for monitoring or fixing harmful outputs?
Has this tool caused controversy or complaints in the past?
6. 🔒 Does This AI Respect My Privacy and Consent?
Many AI systems rely on personal data — your chats, emails, searches, photos — often collected without full awareness. Others might train on publicly available but ethically ambiguous data like online art, code, or writing.
Why it matters:
AI can erode personal boundaries in invisible ways. Ethical AI should be transparent about data use and offer real choices about participation.
Ask yourself:
What information is this AI collecting from me?
Was the data it was trained on gathered with consent?
Can I opt out of sharing my data or being part of training sets?
7. 🌍 Who Could Be Harmed by This AI — and Who Benefits?
Technology often helps some while harming others. For example, automated resume screeners may boost efficiency for employers but disadvantage certain candidates. Facial recognition may offer convenience while threatening marginalized communities.
Why it matters:
Ethical AI considers social impact — not just utility. It centers equity, safety, and dignity for everyone, not just convenience for the majority.
Ask yourself:
Who might be excluded or misrepresented by this AI?
Does it reinforce or challenge social inequalities?
Are the benefits distributed fairly — or concentrated?
🛠️ Bonus: What to Look For in Ethical AI Tools
When choosing or evaluating AI tools, here are some green flags that suggest ethical intention:
Clear documentation or ethics statements
Transparent data practices
Human-in-the-loop systems for oversight
Inclusive design and accessibility features
Open feedback and reporting mechanisms
And some red flags to watch for:
No explanation of how the AI works
Vague or missing data sourcing information
No way to appeal decisions or report harm
Overpromises about accuracy or objectivity
✨ The Power of User Curiosity
You don’t need to be an AI expert to ask thoughtful, important questions. In fact, users who ask questions are one of the strongest forces for making AI more ethical. When we stop accepting technology as inevitable and start demanding that it be responsible, we create pressure for change.
Ethical AI doesn’t start with code. It starts with values — and those values are shaped by people like you who choose to question, engage, and expect better.
References and Resources
The following sources inform the ethical, legal, and technical guidance shared throughout The Daisy-Chain:
U.S. Copyright Office: Policy on AI and Human Authorship
Official guidance on copyright eligibility for AI-generated works.
Global framework for responsible and inclusive use of artificial intelligence.
Research and recommendations on fair, transparent AI development and use.
International standards for trustworthy AI.
Stanford Center for Research on Foundation Models (CRFM)
Research on large-scale models, limitations, and safety concerns.
MIT Technology Review – AI Ethics Coverage
Accessible, well-sourced articles on AI use, bias, and real-world impact.
OpenAI’s Usage Policies and System Card (for ChatGPT & DALL·E)
Policy information for responsible AI use in consumer tools.
