Beyond the Code: Ethical Metrics for AI that Truly Matter
By Kraig Kleeman
Measuring AI isn’t just counting beans; it’s like being the referee in a game where the rules are written in binary. Let’s whistle, throw the flags, and make sure our AIs are scoring touchdowns, not just running around the field!” – Erik Severinghaus, Founder and CEO
Introduction
If you ever think about how we keep our AI tools working properly, or why some AI applications do very well while others fail badly, the answer is often in the metrics. Let’s go into the world of AI measurements and find out which ones are truly important.
Why Measuring AI is Like Keeping a Score in Sports
Think AI like sports team. How can you tell if your favorite team is good? You look at results and performance! If they win many games, it means they’re strong. Same for AI: check how accurate it’s predictions are or how well it completes tasks. Also, see what experts say—like coach feedback in sports—you want to know from people who understand the game deeply. Look at consistency too.
A great team performs well not just once but many times over season; a good AI should work reliably across different situations and data sets. Also important to consider teamwork in both cases: In sports, players must work together smoothly; with AI systems, components (data processing, algorithms) need integrate nicely to perform best. Finally fan support matters also—in sport big crowd cheering shows popularity same way positive user reviews show an appreciated useful AI making lives easier!
So by checking all these aspects – wins (results), expert opinion (reviews/feedback), consistency of play/work & general acceptance/popularity – you get clear picture about quality whether looking at sport teams or Artificial Intelligences! You look at their scores, right? It’s the same with AI. If no keeping score, we not know if AI is champion or need go back to training.
Measuring how well our AI works helps us check it does what should do, like following rules and achieving goals important for users.
The MVP of AI Metrics
If I need to choose the MVP (Most Valuable Performance indicator) for AI, it would be “Accuracy of Predictions.” This means how many times our AI correctly guesses or decides things. When our AI predicts something, how many times does it get right? If accuracy is high, that means our AI works very well and makes decisions you can trust.
Why This MVP Stat Tells Us So Much
Accuracy not only a figure—it like the life story of our AI. It tells how good our AI grasp what task it need to perform. It is like a report card which tells us in what subjects our AI is doing very well and where it may need more help studying. This information is very valuable, because it helps us adjust and train our AI to become even better.
Starting Out with AI Metrics
When you begin to monitor AI performance, consider what exactly you wish your AI to accomplish. It is similar to setting personal goals for oneself. Maybe you want your AI to make customer service better or help with fewer mistakes in data entry. Whatever the goal is, pick numbers that show these aims well. Think of it as setting up a fitness tracker for your AI’s health.
Watch Out for These Pitfalls
Here’s where things get hard. Think you only cared about your math grades and forgot everything else in school. Not great, right? The same goes for AI metrics. If we only focus on accuracy, we might not see how the AI works in real-world situations or if it is fair. Also, it’s important to be careful about hidden data biases that can mess up our measurements. It’s all about getting the full picture.
Wrapping Up
To finish, choosing correct metrics not only makes AI more intelligent—it ensures AI is helpful, fair, and enhances our lives. At Bloomfilter, we focus not just on advancing AI but also ensuring these advances benefit everyone in the right way. Thank you for exploring the metrics puzzle with me, and let’s celebrate creating AI that really makes a big impact!
About Erik Severinghaus
Erik Severinghaus is a highly successful entrepreneur, author, and mountaineer. If his accomplishments and aspirations were to draw inspiration from natural icons, he could be described as a fusion of Mark Zuckerberg’s visionary approach to business and Tony Stark’s electrifying approach to saving humanity. He possesses keen business acumen and a flair for captivating customers, investors, and marketing partners.
Erik’s entrepreneurial spirit is boundless, as evidenced by his track record of founding, operating and exiting multiple ventures that have created a combined $600M in value. Erik’s investment skills are striking. He was a founding investor in Hyde Park Angels which recently helped ShipBob achieve unicorn status. He raised $6M startup capital for his newest venture, Bloomfilter, which is growing by triple digits, quarter over quarter.
As an endurance athlete, Erik has conquered some of the world’s tallest peaks, including Mt. Everest in 2018. In his public appearances, Erik is quick to discuss that learning to navigate through the valleys in his business life is what has led him to properly navigate the victories.