[UX#5]_Prediction Machine Visual notes

                               

Last weekend my book read was on "Prediction Machine" written by a collab of Ajay Agarwal, Joshua Gans and Avi Goldfarb.

As the world has increasingly exposed to AI, I have been reading articles from various sources about its future impact on human society, economies, politics, academia, and nearly every aspect of life that involves human interaction.

 I am myself using AI products to harness its power in UX design as a Designer. 

To expand my knowledge base I got interested in learning more which led me to Blinkist's –Audio book on "Prediction Machines"

I would like to begin sharing of what I learned from the book and lastly will share my own thoughts on the same.

The writer of the book introduces us to the new "teacher" in town—AI. It’s a force that not only outsmarts parents when it comes to helping with school homework, but also powers self-driving cars.

AI is rapidly reshaping every industry, job role, and aspect of our daily lives. With its ability to predict the future, it holds the potential to help humans prevent losses, anticipate risks, and manage crises more effectively. However, as these machines grow increasingly adept at understanding human behavior—our needs, desires, and decisions—they seem to be surpassing human intelligence in some ways. This raises a critical question: could this technology eventually make humans more dependent and less intellectually active in comparison? 

AI advancement definitely brings its own set of trade-offs, and understanding them becomes important—whether you're an entrepreneur or just someone curious about where this whole AI journey is heading. As we already see around us, data is only getting more complex. That’s where machine learning and deep learning have truly shifted gears for AI—helping it deal with such massive datasets and making predictions with remarkable accuracy.

While human judgment still holds value—especially in reading between the lines—AI algorithms shine when it comes to processing huge volumes of information and identifying hidden patterns. The book also highlights how both AI and human intuition are shaping decision-making in areas like healthcare and finance, showing us that while the benefits are huge, we’ll always need to weigh them against the trade-offs. 

For example, a bank may flag a customer's credit card transaction as suspicious, or a medical report might classify a tumor as benign rather than malignant. Prediction involves using what we already know to infer what we don't. In fact, predictive systems influence our daily lives more often than we realize.

The core of AI lies in prediction, not replicating human intelligence. 

AI-driven predictions shape business decisions, impact economies, and influence our futures. Every AI advancement comes with trade-offs; managing these is key for individuals and corporations alike.