Good vs Not So Good AI

The AI landscape is becoming increasingly crowded. Every day brings new tools, models, and promises. But not all AI is created equal. Here's our framework for distinguishing between good AI and not-so-good AI.

Good AI

Good AI amplifies human capabilities:

1. Enhances Creativity: Expands possibilities rather than narrowing them
2. Promotes Understanding: Helps you learn why, not just what
3. Respects Agency: Keeps humans in control of important decisions
4. Builds Capability: Makes you better at what you do
5. Transparent: Clear about its limitations and capabilities

Not So Good AI

Conversely, not-so-good AI tends to:

1. Replace Rather Than Enhance: Removes human agency
2. Black Box Solutions: Provides answers without understanding
3. Creates Dependency: Makes users reliant on the AI
4. Lacks Transparency: Unclear about its limitations
5. Diminishes Skills: Atrophies human capabilities

Examples in Practice

Good AI

• Code assistants that explain their suggestions
• Learning tools that adapt to your understanding
• Creative tools that expand your possibilities

Not So Good AI

• Black box solutions that can't explain their work
• Tools that encourage blind trust
• Systems that replace human judgment entirely

The Path Forward

When building or choosing AI tools, ask:

1. Does this tool make me better at what I do?
2. Am I learning and growing through its use?
3. Do I understand why it makes certain decisions?
4. Does it respect my agency and judgment?

Our Commitment

At Atris, we're committed to building good AI that:

• Amplifies human potential
• Promotes understanding
• Maintains transparency
• Respects agency

The future belongs to those who can effectively collaborate with AI while maintaining their unique human capabilities.