One of data science’s primary uses is in companies to help them increase their margins and profits. Data science is also connotated this way – to help companies increase revenue and cut costs. However, data science is also being used for good and to help speed up developments. For example, data science and AI were being used to help aid in the development of the Covid-19 vaccine. That is what the article “How AI and Big Data Contribute to the Search for Vaccines and Drugs” by Stuart Rauch details. The article is linked here.
Summary of Article
The article starts out by emphasizing the popularity of machine learning by showing the amount of businesses that use machine learning(63%). It then goes into the fact that there are a number of companies that are coming up that are centered on AI(221 startups produce AI). AI can “identify patterns in virus data, make appropriate predictions, and potentially uncover the right drugs for testing” along with reducing the time needed for diagnosis from 5 minutes to 20 seconds. AI is also being used to help detect people and places with elevated disease concentrations in China. Google made its play on AI with an AI that can help predict the 3D structure of the virus based on its proteins. The article then gets into how AI works and it says that on the first pass, the algorithm wont get a high accuracy but when they keep learning and learning and keep doing more and more passes that is when the algorithm improves its accuracy. After, the article says that big data is vastly important to vaccine development and the use of AI to go through all of that data is becoming increasingly valuable. The article concludes with the note that vaccine developers will have to employ AI professionals and big data technicians to help expedite vaccine development and they will be in high demand in the years to come.
My Take
Overall I liked this article. Having lived through the Covid-19 pandemic just a couple of years ago it hits really close to home. And it goes to show that AI had a role in all of our lives coming back to normal. The article was structured well with a lot of headings, which broke the article up, making it easier to read. I would have appreciated some pictures and visuals to help show what the article was talking about. This also goes to show the humanistic side of data science with it being used for a good purpose and not solely to line a company’s pockets. The article, with all things considered, was a good one.
Conclusion
All in all, the article was a worthwhile one to read. It was relatively easy to follow and touched on the humanistic side of data science, however, I would have appreciated some more visuals. Overall, it was a great article and you should go read it(link here)!