Learnings & Musings on AI, ML, Data Science & Python

Google Wages War on Gender

Ok, not really. But I can imagine that being a headline of some inflammatory “news” article. πŸ—žοΈ They’re working to remove implicit, societal gender bias from machine translations in Google Translate by changing the underlying architecture of the machine learning model they use. Basically, the model now produces a masculine and feminine version and then determines which is most likely … Read More

When People Do Bad Things With Algorithms 😈

There is a lot of concern surrounding decisions made by algorithms and bias baked into said systems, but that is far from the only concern. These podcast episodes do a tremendous job illustrating what happens when people use neutral data for the wrong things. When the reason for the data becomes perverted. At the end of the day AI systems … Read More

When Unbiased Machines Meet Biased Humans πŸ₯Š

I’m worried about the implications of transferring our biases to machines and then turning up the speed dial to 11. But I hadn’t thought about how we biased mortals might react to truly unbiased decision making. 🀯 So while creating unbiased systems is important, it doesn’t guarantee success in the messy real world once decisions are made. Ultimately debiasing systems … Read More

The Unbias 3000 πŸ€–

Accenture has developed and is rolling out, in beta, a tool to help uncover bias in algorithms. Man, I hope this works. πŸ™ I am really interested to know more about how their Fairness Tool works. My guess is it basically runs another training set through the algorithm that is labeled in such a way that the outputs can be … Read More

The Deciding Tree 🌳

This is a really great description of decision trees with some lovely visuals. It also continues a good overview of overfitting. πŸ‘Œ Decision trees might not seem as sexy as other algorithmic approaches, but it’s hard to argue with the results. It also strikes me how similar this process seems to the way humans approach a lot of experience-based decision … Read More

AI Replacing Animals πŸπŸ€

An algorithm has been developed for testing chemical compound toxicity that has, so far, been as accurate as animal testing. This could be huge for pharma R&D and any other industry that relies on animal testing. It should make the process faster and easier and should make animal rights supporters happy, basically it should be a win all around. πŸ™Œ … Read More

A Cautionary Tale ⚠️

Automation can be a wonderful thing. It can also turn a small human error and snowball it out of control, like this story illustrates. Systems need fail safes and other checks so that humans can intervene if/when needed. Technology is supposed to help us, not control us. πŸš₯ This is one of the reasons why I am in the centaur … Read More

Chatbot Gone Wrong 🚫

I love me some hilarious AI hijinx and the Letting Neural Networks Be Weird blog is a perfect source for it. This post about the less than correct conversations about various images is also a good reminder that AI doesn’t intuit or truly understand things the way we do. These models learn, but in a far different fashion from humans. … Read More

Osonde Osoba on AI πŸŽ™

I find myself agreeing with a lot of what this guy says. Confirmation bias FTW! πŸ™Œ Here are some quotes that represent what really spoke to me. πŸ—£ Artificial intelligence is a way of understanding what it means to be human beings. We need to think about AI in terms of value alignmentβ€”I think that’s a better framework than, say, … Read More

Listen Up πŸ”Š: Digital Evolution

This episode of Software Engineering Daily is a great listen on the topic of digital evolution, or, the process of allowing algorithms to grow and evolve. πŸ¦– This field leads to a lot of funny results but there is an important lesson to that, and is probably my favorite moment of the show. We humans are really bad at stating … Read More