To start my exploration into AI, I kept it very simple. I went into Google and searched “What is AI?”, and Google’s AI overview provided a basic definition stating that AI is “a set of technologies that allow computers to perform tasks that usually require human intelligence” by using algorithms and data. It also provided an overview of how it works, what it can do, and what some applications are.
This was all information I was already familiar with, so I decided to dig a little deeper. I scrolled away from the Google AI overview and clicked on IBM’s Think piece “What is AI?” written by Cole Stryker and published in August of last year. This article was more technical than I expected. It provided comprehensive explanations of machine learning and deep learning. Machine learning is “creating models by training an algorithm to make predictions or decisions based on data” while deep learning “uses multilayered neural networks… that more closely simulate the complex decision-making power of the human brain.”
From reading about these, I realized that when I thought about how AI worked and what it could do in the in the past, I was thinking about machine learning, so the deep learning aspect of AI is both fascinating and horrifying to me. To think that AI is functioning like a human brain and can create new knowledge in the same way that humans are capable of with far less error makes me think that we are heading toward the future imagined in iRobot, and that scares me a little because it has the ability to make a lot of jobs obsolete, which would put people out of work, and change the landscape of society.
With that fear at the front of my mind, I scrolled down to the benefits, challenges and risks of AI, most of which I had an idea about already. I love the prospect of AI reducing physical risk to humans in dangerous jobs or even with self-driving cars, but I am very concerned about the environmental, ethical and legal risks.
The IBM article covers what some common values associated with AI ethics and responsible AI are. They include explainability and interpretability, fairness and inclusion, robustness and security, accountability and transparency, and privacy and compliance. While I am truly glad that there are values tied to this matter, and I am curious to know how many of the organizations developing AI are upholding them.
Once I finished this article, I moved on to a quick video “What is AI | Learn all about artificial intelligence” for another general overview. It talked about artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial super intelligence (ASI). ANI and AGI seemed to be another way to talk about machine learning or ANI vs. deep learning or AGI, but I could be misunderstanding these terms. This video explained that most AI is ANI but that we are broaching on more AGI applications, and ASI is still just an idea, not a reality, so I suppose we aren’t at iRobot quite yet.
This video also discussed the pros and cons of AI. Again, it mentioned how AI saves time, reduces risk in hazardous jobs, reduces error, and allows for new discoveries. It also talks about AI being expensive, environmentally detrimental, and how it could cause people to lose their jobs. This was also the first source I looked at that mentioned how AI could potentially plagiarize artists work as a con, and as a creative writer, this is something I’m worried about. If AI can write the next big Romantasy book and publishers don’t have to pay them, then what use will we have for creative types? I could be getting ahead of myself here, but it is something that I think about.
That said, this video also made me think about how all big leaps forward in technology have caused certain jobs to become obsolete, so I guess this is nothing new for society as far as impact, but maybe it’s just the first time I’m experiencing something like this as part of the workforce. I’m interested to see what else I discover in this course.
Let me know your thoughts!