What Is Artificial Intelligence and How Can I Use It?
Artificial intelligence has been surrounded by a fog of mystification — simultaneously oversold as existential threat and undersold as just autocomplete. The truth is more useful than either narrative: AI is a powerful set of tools that can amplify your capabilities as a builder, entrepreneur, and creator right now, at low cost, without requiring advanced mathematics or a computer science degree.
Understanding what AI actually is — and is not — lets you use it intelligently rather than be intimidated by it or exploited by the hype around it.
What AI Actually Is (Plainly)
Modern AI, specifically the large language models (LLMs) like GPT-4, Claude, and Gemini that dominate current technology conversations, are statistical systems trained on enormous amounts of text. They learn patterns — which words follow which other words, in what contexts — at a scale and depth that produces surprisingly capable behavior: coherent writing, code generation, logical reasoning, summarization, translation, and question-answering.
These systems are not conscious. They do not understand language the way humans do. They do not have beliefs or intentions. They are pattern-matching machines operating at extreme scale. Understanding this prevents misuse: do not rely on LLMs for facts without verification (they hallucinate confidently and frequently), do not assume they have current information (most have training cutoffs), and do not share sensitive personal data with them.
What they are genuinely excellent at: drafting, editing, explaining, brainstorming, summarizing, translating, generating code, and performing reasoning on information you provide.
AI Tools You Can Use Today
Writing and content creation
If you write — marketing copy, blog posts, grant proposals, business plans, email campaigns — AI can dramatically accelerate your output. Use Claude, ChatGPT, or Gemini to:
- Draft first versions of documents based on bullet points you provide
- Edit and improve drafts you have already written
- Rewrite content at different reading levels
- Generate social media content in multiple variations
- Summarize long documents into concise briefings
The key practice: always provide specific context and constraints. “Write a 300-word Instagram caption for a Black-owned restaurant in Atlanta, emphasizing the family atmosphere and Sunday brunch special” produces far better results than “write a social media post.”
Coding assistance
AI coding assistants — GitHub Copilot, Cursor, Aider — can generate working code from plain English descriptions, explain what existing code does, suggest bug fixes, and write tests. For developers at every level, these tools accelerate work significantly.
For beginners: AI can explain error messages in plain English, suggest approaches to problems, and write boilerplate code that would otherwise require hours of searching documentation. This substantially lowers the learning curve.
Data analysis
You do not need to know statistics to analyze data with AI. Provide a spreadsheet to an AI tool and ask questions: “What are the top-selling products in this data?”, “Are there any anomalies?”, “What trend do you see in monthly revenue?” The AI reads the data and responds in plain language.
For more structured analysis, Python with pandas and AI-assisted code generation lets you build reproducible data pipelines. The AI writes the pandas code; you run it and interpret the results.
Customer service and chatbots
A small business can now build a customer service chatbot that answers questions from a knowledge base — without writing complex code. Tools like Botpress, Typebot, and Flowise allow no-code chatbot building on top of AI APIs. For developers, building a custom RAG (retrieval-augmented generation) chatbot that answers from your business’s documents costs roughly $20-50/month in API fees.
Image and design
Midjourney, Stable Diffusion, and DALL-E generate images from text descriptions. For small businesses without design budgets, these tools produce usable marketing materials, concept art, and visual content. Stable Diffusion is open source and can be run locally on a capable GPU.
Building With AI, Not Just Using It
Using AI tools is one thing. Building AI-powered products is a larger opportunity for technically inclined builders.
The current entry point for building AI applications is accessible:
- Get an API key from Anthropic (Claude), OpenAI (GPT), or Google (Gemini)
- Install the SDK in Python:
pip install anthropic - Make API calls in your application to generate text, answer questions, or process content
A working AI chatbot backend in Python is approximately 20 lines of code. The complexity comes from the application logic around it — how you retrieve relevant documents, how you format prompts, how you handle conversation history. These are solvable engineering problems, not research problems.
AI and Sovereignty
A critical dimension of AI that Black builders must engage with: these systems are trained primarily on English-language internet text, which skews heavily toward Western, specifically American, perspectives. The history encoded in these models — their assumptions about whose knowledge is authoritative, whose culture is default, whose experiences are centered — reflects the biases of their training data.
This creates two opportunities:
First, as users, bring your own context explicitly. The AI does not know your community’s specific needs unless you tell it. A prompt that includes explicit cultural context produces better, more relevant output.
Second, as builders, the opportunity is to build AI-powered tools that serve communities and knowledge traditions that are underrepresented in current models. An AI assistant trained on African proverbs, oral traditions, and indigenous knowledge systems would serve communities that current LLMs serve poorly.
The tools are here. The question is who builds with them, and for whom.