Your guide
A key objective of ACHIEv is to enable anyone to understand and use AI.
A passion for human potential
AI enables us to amplify our strengths, unlocking our greatest potential. When designed responsibly and applied thoughtfully, AI systems can enhance human capabilities and empower accomplishments we never thought possible. As we seek to direct these technologies towards progress instead of mere convenience or control, an essential first step is building literacy to guide wise deployment across contexts.
AI Bias
AI systems produce errors or unfair outcomes due to biased training data, incomplete data, or flawed algorithms. AI bias can perpetuate societal prejudices around race, gender, age, etc.
AI Explainability
Ever wonder why AI makes the choices it does? AI explainability sheds light on the “black box,” revealing the reasoning behind its decisions. Like peeking under a car’s hood, this transparency builds trust, identifies biases, and helps us fine-tune AI for a future where machines not only think, but also explain themselves.
Machine Learning
Computer programs that learn patterns from data to make decisions without step-by-step coding. Like how kids learn concepts by examples over time, not rules.
Neural Networks, Reinforcement Learning, Supervised Learning, Unsupervised Learning, Deep Learning
Neural Networks: Layers of math that identify complex patterns. Inspired by animal brains. Can recognize images or speech from discovering underlying relationships.Reinforcement Learning: Trial-and-error method where AIs try actions then receive feedback scores to guide better choices, like conditioning behaviors with rewards versus penalties.Supervised Learning: Supplying labeled datasets so algorithms correlate data traits with the correct conclusions. Similar to a student studying worked examples to understand a concept.Unsupervised Learning: Algorithms find hidden patterns within unlabeled data without direction, like detecting consumer profiles through purchasing data. Deep Learning. A powerful form of machine learning based on artificial neural networks inspired by the human brain. Deep learning excels at finding patterns in unstructured data like images, audio, and text.
Data Privacy
Principles and practices to protect personal information and ensure ethical and secure data handling are especially important when training AI on sensitive individual data.
Generative AI
Generative AI uses machine learning to produce completely new content – whether blog posts, images, videos or more – by studying patterns from large data examples.
Tips
- Just like with humans, breaking down a task into a simple set of instructions is often used to teach someone how to execute a specific task. It’s important to do that for Generative AI to achieve a specific outcome.
- Use Generative AI where: 1) a partially correct solution is valuable or 2) checking if the solution is correct isn’t time-consuming or expensive
Ethical AI
The field examines the moral implications of artificial intelligence systems. It establishes guidelines to ensure AI development and use are aligned with human values like fairness, accountability, privacy, and harm prevention.
Hallucination
Sometimes, AIs generate false information that seems believable – called a “hallucination.” This stems from gaps in reasoning. Leaders should apply judgment when using AI aid. Cross-check details created. Beware of risks behind rising benefits.
For example, if your fundraising AI cites unrealistic donation data, scrutinize output integrity before acting. Blend computational power with human context, filling logic holes. Discerning AI’s strengths versus limitations promises fruitful collaboration.
Yet creativity springs from randomness. With thoughtful design, future “controlled hallucination” may drive innovation – imaginative, human-guided brainstorming rather than unilateral concoction.
About Large Language Models (LLM)
ACHIEv focuses on the adoption of LLM’s.
For nonprofits, LLMs serve as powerful AI co-pilots. They significantly boost team productivity by assisting with communications, writing, analysis, and automation – while augmenting rather than replacing human efforts. Your team stays in control, providing prompts and guidance while the LLM maximizes efficiency.
LLMs stand for large language models. These are a kind of artificial intelligence. They are trained on huge amounts of text that real people have written. This lets them produce very human-sounding language. It also lets them respond to normal prompts in crystal clear ways that make sense.
However, it’s crucial to understand LLMs can make mistakes or have built-in biases. Human oversight is still required to review outputs and protect data privacy/security. When used responsibly, LLMs are transformative tools that amplify your mission’s impact.
“We cannot control the wind, but we can adjust the sails.”