Mitesh is an engineering leader pioneering the use of generative AI to transform data platforms. As a tech lead at Airbnb, he builds cutting-edge data pipelines leveraging big technologies and modern data stacks to power trust and safety products. Previously, at AWS, Mitesh helped Fortune 500 companies migrate their data warehouses to the cloud and engineered highly scalable, resilient systems. An innovator at heart, he combines deep data engineering expertise with a passion for AI to create the next generation of data products. Mitesh is an influential voice shaping the future of data engineering and governance.

My Mentoring Topics

  • Data Engineering
  • Data Analytics
  • Machine Learning

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Thinking, Fast and Slow
Daniel Kahneman

Key Insights from 'Thinking, Fast and Slow' Cognitive Ease: The human brain tends to choose the path of least resistance when processing information. System 1 and System 2: Two distinct systems govern our thought processes. System 1 is fast, intuitive, and emotional, while System 2 is slow, deliberate, and logical. Heuristics and Biases: Our brains use mental shortcuts or 'heuristics' to make quick decisions, which can often lead to biases in our thinking. Prospect Theory: People tend to make decisions based on potential losses and gains, not final outcomes. Anchoring Effect: The first piece of information we receive about a subject heavily influences our perception of subsequent information. Availability Heuristic: We tend to judge the probability of events by how easily examples come to mind. Endowment Effect: We value things more when we own them. Hindsight Bias: Our tendency to see events as more predictable than they really are after they have happened. Framing Effect: The way information is presented can drastically affect how we perceive it and make decisions. The Halo Effect: Our overall impression of a person influences how we feel and think about their character. Deeper Analysis of the Book's Concepts 'Thinking, Fast and Slow', a seminal work by Daniel Kahneman, delves into the two systems that drive the way we think—System 1, which is fast and intuitive, and System 2, slow and deliberate. This dual-process theory of cognition is not new, but Kahneman's exploration of how these systems interact, often leading to cognitive biases, is groundbreaking. System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. It's the part of our brain that responds to a surprising sound in the darkness or decides to swerve to avoid an accident. This system is heavily influenced by our past experiences and emotions, making its responses feel intuitive and automatic. In contrast, System 2 allocates attention to the effortful mental activities that demand it, including complex computations and conscious decision-making. This system is slower and more deliberate, often stepping in to verify and modify the impressions and intuitions from System 1. However, System 2 is lazy and often defaults to the easier, automatic responses of System 1. This is where cognitive biases come in. Heuristics and biases are mental shortcuts that System 1 uses to make quick decisions. While these shortcuts can often be useful, they can also lead to systematic errors in our thinking. For example, the availability heuristic might lead us to overestimate the likelihood of dramatic events (like plane crashes) because they are more memorable and thus more easily available to our minds. Prospect theory, introduced by Kahneman and his colleague Amos Tversky, challenges traditional economic theory, which assumes that humans are rational actors. Instead, prospect theory suggests that people make decisions based on potential gains and losses, not the final outcome. This can lead to seemingly irrational decisions, such as refusing to take a small loss to potentially gain more in the long run. The anchoring effect describes our tendency to rely heavily on the first piece of information we receive (the "anchor") when making decisions. Even when the anchor is arbitrary or irrelevant, it can dramatically influence our judgments and estimates. Similarly, the framing effect reveals that the way information is presented can drastically affect our decisions. For example, people are more likely to opt for a surgical procedure if it’s presented with a 90% survival rate than a 10% mortality rate, even though both statistics convey the same information. In conclusion, 'Thinking, Fast and Slow' highlights how our thought processes—though powerful—are not always as rational, objective, or logical as we might believe. By understanding these biases, we can take steps to mitigate them and make better, more informed decisions.