Old School Versus New School

Using AI to Parse Through Tons of Data

Like many people, I wasn't completely shocked to hear the news about an alleged gambling scandal in the NBA.

The NBA has had its fair share of gambling issues (most notably, the Tim Donaghy betting scandal). Compared to other major sports, one player has much more autonomy to create a certain outcome. Combined with this is an environment where gambling is, simply put, in your face.

It's hard to watch an NBA game without seeing DraftKings or FanDuel commercials. It's hard to watch an NBA game without seeing courtside ads for gambling companies. And it's hard to watch an NBA game without seeing players wearing patches for gambling companies on their jerseys.

With all of this in mind, I've been thinking about how AI can help parse through tons of data to find patterns that humans might miss. This is particularly relevant in contexts like sports betting, where there's an overwhelming amount of information to analyze.

The old-school approach would be to manually review game footage, statistics, and betting patterns. But with AI, we can process vast amounts of data in seconds, identifying anomalies and patterns that would take humans weeks or months to discover.

This isn't just about sports betting, of course. The same principles apply to financial markets, business intelligence, and countless other domains where data analysis is critical.

The key is understanding when to use AI for data analysis versus when human intuition and domain expertise are still essential. AI can process information at scale, but humans bring context, judgment, and the ability to ask the right questions.

As we continue to develop these tools, the most successful practitioners will be those who can effectively combine AI's analytical power with human insight and domain knowledge.

Prompt of the Week

I've been trying to expand my reading beyond my typical genres. This prompt helped me discover some interesting books that I might not have found otherwise:

"Based on what you know about me, my career, and my interests. Give me some ideas on some non-traditional books that I can read that can help me perform better at work and reach my career goals. The more off the beaten path or outside of my typical reading diet, the better."