5 Things I Learned About AI: Part 2
This is a two-part series that discusses what I have learned about AI so far.
1.) It's All About the Data - For AI to work, it relies on data. The availability of data is essential, for without it, AI cannot work. Data can be quantitative, such as numbers, or qualitative, such as words and pictures (Dutceac Segesten). AI must have quality data, as it can be a huge problem if it doesn't. "Garbage in, garbage out" is a phrase that represents whether the AI system was given quality data or not. If you put quality data, you'll get quality results; if you put garbage data, you will get garbage results (Dutceac Segesten).
There are other issues surrounding data, such as data privacy and data collection, that can play a role in data quality.
2.) The oldest facial recognition is humans - Modern facial recognition started in the '60s, with Woodrow Wilson Bledsoe creating the first system that would end up giving ideas to current facial recognition (Lwin). However, facial recognition has always existed, as humans themselves have used it to identify individuals, their thoughts, their feelings, etc (Lwin). Though facial recognition might become more automated, there are still many things that it cannot process like human facial recognition can.
3.) You can create Generative AI content yourself - If you use Generative AI Studio, created by Google Cloud, you can create content such as language, images, and speech. It does this by allowing "users to rapidly prototype and customize generative AI models with no code or low code and to use the generative AI capabilities in their applications" (Google Cloud Training).
4.) We are in a Fourth Industrial Revolution - As a result of rapid technological developments, it can be considered that we are experiencing the Fourth Industrial Revolution. This is a result of cyber-physical systems—a combination of data-generating processes and the physical world (Dutceac Segesten). From 3-D printing to self-driving cars, these advancements and more have pushed us into this new stage, though it will take more time to feel the effects of these technologies.
5.) AI is not going to take our jobs - This argument has come up time and time again, but history has shown that technological advancements have not produced this endgame. On the contrary, it might be giving us more work, but with more advanced technology. This fear that technology will lead to the loss of jobs is called "the fear of technological unemployment" and has existed for at least two centuries (Dutceac Segesten). With the development of AI technology, what this could mean instead is that we do fewer routine tasks and have more where we use our brains more. Also, according to a job replacement theory by Huang and Rust, soft skills such as people skills and empathy will be the last thing that AI will replace (Dutceac Segesten).
Works Cited:
Dutceac Segesten, Anamaria. AI, Business & the Future of Work. Lund University, https://www.coursera.org/learn/ai-business-future-of-work.
Google Cloud Training. Introduction to Generative AI Studio. Google Cloud, https://www.coursera.org/learn/introduction-to-generative-ai-studio.
Lwin, Kelvin. AI, Empathy & Ethics. University of California, Santa Cruz, https://www.coursera.org/learn/ai-empathy-ethics.