On March 15, 2016, a computer program named AlphaGo defeated the world’s best player of Go, a highly complex ancient Chinese board game. Last month, Alibaba Group Holding Inc. put its neural net through its paces and successfully outgunned a human being at a Stanford reading test. It is speculated by famous figures such as Stephen Hawking and Elon Musk that we could be creating a nemesis, one that poses dangers far beyond human comprehension.
To increase awareness and reading in the field of AI and machine learning, a reading group was organized by Dr. Laura Brown from the Computer Science Department. The group held its first meeting on Feb. 5, 2016.
Joshua Stomberg is a doctoral student at Michigan Tech. On Feb. 5, he led the discussion for the K-nearest neighbors algorithm.
The meeting commenced with an introductory session. “There can be great but limited success,” he said. “If the number of road accidents per year reduced from 30,000 to 25,000, is that good? Or would self-driving cars make us more anxious?” Unlike many undergraduates with quick opinions about the future, he was skeptical.
“The more you know about the subject, the more you are aware of the unknown unknowns,” Dr. Brown added. “Sci-fi in the media usually represents broad AI. There are always barriers to overcome, and we need to know what questions to ask.” And that is the truth about life and consciousness as well. Is reality a figment of our imagination? Or should we ask deeper and more accurate questions to increase the scope of our consciousness?
Jason Hiebel is a doctoral student in the Department of Computer Science. He is currently investigating the application of online machine learning methods, and performance optimization problems in computer science. On Monday, Feb. 12, Hiebel spoke about the Expectation Maximization algorithm. He was very enthusiastic about the subject and broke down the concepts effectively for simplicity. “Questions about the future of AI are hard to answer!” he says. “Who is responsible for the bad that stems from the actions of intelligent machines?” he asks. This led to a discussion about the laws and ethics of the subject.
The beauty of AI is that it can be applied to various focuses of science and engineering. With its growing popularity in companies and the media, a more comprehensive awareness of AI can provide insight into what computers can do for us in the future. For the reading groups, the coming weeks will witness topics in data mining such as the Naive Bayes algorithm, decision trees, boosting, etc.
Future themes may cover specific application domains or topics such as deep learning, feature selection, etc. But if anyone is interested in a topic in the field that could be of importance to discuss, Dr. Brown is open to suggestions. Students interested in joining the reading group should feel free to contact Dr. Brown at lebrown@mtu.edu.
