Artificial intelligence
The broad field of systems that perform tasks associated with intelligence, such as recognizing patterns, generating language, and making predictions. Capabilities and reliability depend on the system and task.
THE FIELD GUIDE
Intelligence.
In plain language.
Understand what AI can do today, what remains uncertain, and how to use it thoughtfully.
Three terms. Different meanings.
General intelligence
AGI refers to broadly capable AI across many cognitive tasks. Definitions and evaluation criteria differ. A strong benchmark result alone does not establish general intelligence.
Superintelligence
ASI is a concept for systems that substantially exceed human cognitive capability across many domains. It is not a synonym for every AI tool. Forecasts are uncertain and require careful scrutiny.
Further reading: OpenAI on superintelligence ↗ · Google DeepMind on AGI ↗
PRACTICAL BENEFITS
Useful today.
Possibilities for tomorrow.
These are application examples, not guaranteed outcomes. Test each tool in your own context.
Work & productivity
Draft documents, summarize notes, and explore code. Review for accuracy before using the output.
Learning & education
Practice explanations, compare approaches, and get feedback. Verify references and preserve your own reasoning.
Science & discovery
Assist researchers with patterns, simulations, and hypotheses. Scientific claims still need validation.
Accessibility
Support captions, translation, and text-to-speech. Check performance across languages and user needs.
Industry & operations
Explore forecasting, service support, and document processing. Measure quality, cost, and operational risk.
Creativity & design
Explore concepts, prototypes, and alternative directions. Check rights, attribution, and authenticity.
THE RESPONSIBLE AI CHECKLIST
Keep your judgment in the loop.
01 / Verify before you rely
AI can produce confident but incorrect answers and invented citations. Open the original sources, check dates, and independently verify material claims. Use qualified professionals for high-stakes medical, legal, and financial decisions.
02 / Protect confidential information
Do not paste passwords, bank details, personal records, or employer information into unapproved tools. Review the provider’s retention and training policies, use approved enterprise settings, and minimize the data shared.
03 / Give agents limited authority
Use least-privilege permissions, spending limits, logs, and explicit human approval for consequential actions. Test tools in a sandbox and keep a way to stop or reverse actions.
04 / Check for bias and exclusion
Test outputs across relevant groups and languages. Avoid delegating employment, credit, or other high-impact decisions without appropriate oversight, evidence, and review processes.
05 / Watch for scams and synthetic media
Voice and video can be fabricated. Verify urgent requests through a known separate channel, especially when someone asks for money or credentials. Treat external content as untrusted input.
06 / Measure the real outcome
Start with a bounded use case and a baseline. Check quality and failure rates alongside time saved, cost, and impact on people. Expand only when the results justify it.
Grounded in risk-management themes from NIST’s AI Risk Management Framework ↗. This is educational guidance, not a certification or compliance assessment.