Gyan from Cassie Kozyrkov
Cassie Kozyrkov, Chief Decision Scientist at Google has the gift of simplifying complex topics and presenting them eloquently in a relatable way through her social media posts.
Here is a compilation of her observations that I found interesting:
AI
- As AI gets better, decision-making is going to become one of the most important skills in the world.
- AI isn't a threat. Bad decision making is.
- Ultimately, AI should serve society's best interests. It must be transparent, understandable, and aligned with human values. We have a shared responsibility to develop AI in a way that benefits everyone, not just a select few.
- Jargon in machine learning usually doesn’t deserve the shock and awe the name inspires.
- AI can be a thoughtlessness enabler. That’s both why it’s awesome and that’s why it’s dangerous. It’s wonderful when it allows a person to get their personal project automated with less thought and effort but it’s dangerous when the project isn’t just personal. When it affects other people. Because if you allow people to be thoughtless at scale with impact on millions of lives, that’s a terrifying thing.
- Making better decisions starts with asking better questions. Whenever you face a choice, take the time to ask yourself the uncomfortable questions that no one else is asking.
- AI systems analyze data, recognize patterns, and turn those patterns into output. They can mimic our behavior and they can blend what we show them into new combinations, tricking you into thinking something fundamentally new has happened, but AI systems can’t truly automate the big four:
* Decision-making
* Design/innovation
* Art
* Genuine social interaction
Data Science
- Data Science is the discipline of making data useful
Decision-making
- Decision making is turning information into hopefully better action.
- In real life, there are no right answers. The best we can do is make decisions in a way that feels reasonable.
- A good decision-maker:
- recognizes the importance of gathering data before rushing to conclusions
- is calm under pressure
- is willing to experiment and learn from mistakes
- isn't afraid to take risks
- is mindful of the consequences of their decisions
- Good decisions come from thoughtful considerations. Great decisions come from anticipating the consequences.
- If you want to make better decisions, focus on the decision-making process, not the result. Questions over answers. Being wrong indicates growth. Sometimes the answer is as simple as saying "I don't know". Take calculated risks.
- Good decisions come from understanding yourself and understanding what you want. For that, you have to gather data, and then draw conclusions. The science of self-knowledge is crucial in understanding what to do and how to move forward.
- Most people think decision-making is an instinct. Truth is, it's a skill. Sharpening your ability to make better decisions will propel your life to the next level.
- Society might not view 'decision-making' as a skill, but it's the most important of them all. Good decisions can get you closer to the people and things you desire. Bad decisions can cost you relationships, opportunities, and ultimately your future.
- The cost of indecision isn't not making a decision—it's having the wrong decision imposed on you.
- I’m a huge fan of taking advice from those who have more expertise and information than I do, but I never let myself confuse their opinions with facts.
Generative AI
- Seeing generative AI as a raw material might be the perspective shift that’ll make everything click.
Learning
- When you need to learn something quickly, read. When you need to clarify something, write. When you need to prove something, build.
- Outcome bias is the single greatest enemy of growth. Don't focus on the results, focus on the processes that propel you to the results.
Machine Learning
- A model is a recipe that a computer uses to turn data into labels. It’s just some code that the machine uses to convert inputs into outputs, and could be handcrafted by a programmer or learned from data by an algorithm.
- Machine learning is a new programming paradigm, a new way of communicating your wishes to a computer.
- Instead of giving explicit instructions, you program with examples and the machine learning algorithm finds patterns in your data and turns them into those instructions you couldn’t write yourself. No more handcrafting of recipes!
- We love to get computers to do stuff for us. But how can we possibly give instructions if the instructions are really hard to think up? If they’re ineffable? AI and machine learning are about automating the ineffable. They’re about explaining yourself using examples instead of instructions. This unlocks a huge class of tasks that we couldn’t get computers to help us with in the past because we couldn’t express the instructions. Now all of these tasks become possible — machine learning represents a fundamental leap in human progress.
- At its core, machine learning is just a thing-labeler, taking your description of something and telling you what label it should get.
Science
- If you read a good scientific article, you’re likely to see reams of caveats… which only make for a riveting read if you’re a fellow scientist. To a Twitter-weaned attention span, those publications can be a prescription-grade sleeping pill.
- It’s a scientist’s job to form opinions reluctantly, which is the best reason for assuming that they’re worth listening to. Too many of the other popular reasons are misplaced reverence.
Solutions
- Don’t hate a data solution for being simple sometimes. Levers are simple too, but they can move the world.
Statistics
- As a statistician, I’m painfully aware of how easy it is to lie with numbers.
- Statistics is the science of changing your mind under uncertainty.
- Statistics offers control, not certainty
Writing
- I learned that once you have the technical stuff down, you have to add your own voice, the spark that makes a reader recognize the artist behind the words.
- I’m a huge fan of taking advice from those who have more expertise and information than I do, but I never let myself confuse their opinions with facts.
- A theory is what a hypothesis becomes when it grows up.
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