Artificial Intelligence: It’s Complicated And Unsettling, But Inevitable

Artificial Intelligence: It’s Complicated And Unsettling, But Inevitable

Artificial Intelligence: It’s Complicated And Unsettling, But Inevitable

If artificial intelligence came to life today and set up a facebook profile, it would have a relationship with all of us, and our relationship status would be “It’s Complicated”. Although we don’t see the motivation or reasoning behind the algorithms we spend so much time with, they are doing great things for us, and so we love them. Unfortunately, we don’t necessarily understand them or how they will change us. By we, I don’t just mean the general public. I mean software developers, their managers, and even machine learning engineers. AI does some things well and some things poorly, but on balance, the benefits exceed the costs of having an algorithm making decisions.

Just like any relationship, it’s about accepting your partner’s flaws just as much as their charms, and understanding how both can shape your future together. Thought leaders are having a pretty public debate about where this technology is going, and where the relationship may sour. In one specific recent example, Jack Ma and Elon Musk recently discussed the future of humanity in a world run on artificial intelligence. The general viewpoint from Ma was upbeat, while Musk urged caution. These two points of view both have merit. AI is delivering a lot of value, and could also cause a lot of problems. On the positive side, automation with AI is already changing the way we work and play. However, on the cautionary side, imperfect AI systems will not only annoy us, they could bring s to question the technology itself. Simplifying artificial intelligence as Musk and Ma have, casting “AI = good” vs “AI = bad” misses the point that “AI = now”. AI is already here and it will keep getting better. Just so you understand, regular non-AI software does what you tell it to do, whereas AI looks at a set of data to figure out what to do based on the data.

AI algorithms have their flaws but so do things we like, such as driving, and we still accept them. As we embrace the bots (AI algorithms), we shouldn’t hide from the flaws in how things work today. Driving cars causes car crashes, but we love driving. It’s worth the risk. There are many problems in the AI field that need work, including the interpretability of AI models, better tools for dataset handling, more automated machine learning, and avoiding bias. And yet the benefits massively outweigh the risks. We use artificial intelligence in many aspects of our lives, from spam filters to movie recommendations.


What are the signs the evolution of artificial intelligence will follow a positive path of widely adopted technology, rather than concentrating within a few large companies? The artificial intelligence community is making a concerted effort to supply tools and education to regular software developers so that more and more business processes can integrate artificial intelligence. For example, there is probably code on GitHub for achieving common artificial intelligence tasks, licensed for free commercial use. I’m suggesting that these models are production ready, but it’s good to have this development out in the open. The major cloud providers such as Amazon, Google, Microsoft, and IBM have made machine learning resources easy to access, and they also support integration partner networks for custom AI development. This is a really good situation, but there is room for improvement.

This article originally appeared on forbes.com To read the full article and see the images, click here.

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