Welcome to our living dictionary. Technology is filled with jargon, but the ideas behind the words affect all of us. This is a place to find simple, human-centric explanations for the key concepts we explore on this blog. The goal isn’t just to define these terms, but to understand why they matter to us as thinkers, leaders, and human beings.
Key Concepts in Technology & AI
Algorithm
Think of it as a recipe. It’s a set of step-by-step instructions given to a computer to solve a problem or complete a task. In AI, these recipes help machines sort information, make predictions, and learn from data.
Why it Matters: Just as a recipe reflects the chef’s tastes and choices, an algorithm reflects the goals and biases of its human creator. Understanding this is the first step toward demanding more transparency and fairness from our technology.
Artificial Intelligence (AI)
A broad term for the science of making machines that can perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. AI isn’t one single thing; it’s a vast field of tools and techniques.
Why it Matters: It’s less about creating a new conscious life form and more about building powerful tools that can augment our own abilities. The key philosophical question isn’t “Can a machine think?” but “How should we guide its thinking?”
Bias (in AI)
An error or prejudice in an AI system’s judgment. AI systems learn from data, and if that data reflects historical biases (like gender, race, or cultural prejudices in society), the AI will learn and often amplify those same biases.
Why it Matters: This is one of the most critical challenges in AI ethics. A biased algorithm can lead to deeply unfair outcomes in areas like hiring, loan applications, and criminal justice. Creating fairer technology requires us to confront the biases in our society and our data.
Black Box (AI)
A term for an AI system where you can see the input (the data you give it) and the output (the answer it gives you), but you cannot see the process in between. The system’s internal workings are opaque, even to its own creators.
Why it Matters: A “black box” presents a major challenge for trust and accountability. If a doctor uses an AI to diagnose a disease, they need to know why the AI reached its conclusion. Demanding transparency is key to responsible adoption.
Cloud Computing
Instead of storing and running software on your own personal computer or a local server, you access these services over the internet. These “cloud” services are run on massive, powerful data centers located around the world.
Why it Matters: The cloud is the invisible foundation for the entire AI revolution. The enormous computing power needed to train large AI models is only possible because of it.
Cybersecurity
The practice of protecting digital systems, networks, and data from malicious attacks, damage, or unauthorized access. It’s the “immune system” of our digital world.
Why it Matters: As AI becomes more integrated into our lives (our finances, healthcare, infrastructure), securing these systems becomes exponentially more important. A breach in a powerful AI system is a far greater threat than a simple data leak.
Filter Bubble / Echo Chamber
Your own personal, unique universe of information that has been curated for you by algorithms. Based on your past clicks, likes, and views, these systems show you more of what they think you want, effectively “filtering out” opposing viewpoints.
Why it Matters: While comfortable, these bubbles limit our exposure to different ideas and perspectives. They reinforce our existing beliefs, making constructive dialogue with those who think differently increasingly difficult and contributing to societal polarization.
Generative AI
A type of artificial intelligence that doesn’t just analyze data, but creates something new. This can be text (like ChatGPT), images (like Midjourney), music, or code. It learns patterns from vast amounts of data and then uses those patterns to generate new content.
Why it Matters: This technology will profoundly change creativity, work, and communication. It’s a powerful tool, but it raises deep questions about authenticity, art, and the very nature of human creation.
Large Language Model (LLM)
The engine behind systems like ChatGPT. It is a massive neural network trained on a vast quantity of text from the internet, books, and other sources. Its primary skill is predicting the next word in a sequence, which allows it to generate coherent text, answer questions, and summarize information.
Why it Matters: LLMs are the foundation of modern conversational AI. Understanding their predictive nature is key to recognizing both their incredible capabilities and their limitations (for example, they don’t “know” or “understand” things in the human sense).
Neural Network
An AI model inspired by the structure of the human brain. It’s made up of layers of interconnected “nodes” or “neurons” that process information and pass it along to the next layer. By adjusting the strength of these connections during training, the network learns to recognize patterns.
Why it Matters: This is the core architecture behind most of modern AI’s breakthroughs, from image recognition to natural language processing. It’s a beautiful example of taking inspiration from biology to solve complex problems.
Responsible AI
A commitment to designing, building, and using AI in a way that is fair, transparent, accountable, and ultimately beneficial to humanity. It’s about embedding our values—like justice and privacy—into our code and business practices from the very beginning.
Why it Matters: This is the antidote to the “move fast and break things” mentality. It argues that with technology this powerful, we have an ethical obligation to think about the consequences before we deploy it at scale.
Key Concepts in Philosophy
Allegory of the Cave
Plato’s famous story describing prisoners chained in a cave who mistake shadows on a wall for reality. The story illustrates the difficult journey from a state of ignorance (watching the shadows) to one of true understanding (seeing the real world in the sunlight).
Why it Matters: This is a perfect metaphor for our modern digital age. The “filter bubble” acts as our cave, where algorithms show us a comfortable but distorted version of reality. Escaping the cave today means having the courage to seek diverse perspectives beyond our personalized feeds.
Philosopher King
Plato’s ideal ruler. He argued that the best person to lead a society is not one who craves power, but a wise and virtuous philosopher who acts for the good of the whole state.
Why it Matters: In the 21st century, the leaders of major tech companies hold immense power. The concept of the Philosopher King is a powerful call for these leaders to be more than just brilliant engineers; they must also be ethicists and humanists, guiding their powerful creations with wisdom and responsibility.
Theory of Forms
Plato’s belief that the physical world we perceive is not the ‘real’ world, but is instead a collection of imperfect copies of a higher, eternal world of “Forms” or “Ideas.” For example, every dog we see is an imperfect imitation of the perfect “Form” of Dogness.
Why it Matters: This relates directly to how AI models learn. When we train an AI on thousands of pictures of dogs, we are asking it to create its own internal representation—its own “Form”—of what a dog is. It’s a fascinating parallel for how both humans and machines create abstract models to understand a messy reality.
Tripartite Soul
Plato’s theory that the human soul has three parts: Reason (the logical part that seeks truth), Spirit (the emotional part, driving ambition and courage), and Appetite (the part that desires physical things). A just and balanced person is one where Reason guides the other two.
Why it Matters: This provides a powerful framework for designing AI. Should an AI be purely logical? Or should we build systems that can understand and respond to human emotion? The goal of Responsible AI is to ensure that logic and reason—guided by human values—are always in the driver’s seat.
This dictionary is a living document. If there are other terms you’d like to see explained, please let me know!
Techné & Logos 