User:Kyrsten1128/sandbox/Module 7

How It Began
Contrary to popular belief, A.I. is not a recent breakthrough but was first mentioned in the 1950s. Alan Turing wrote a paper proposing the trailblazing question: “can machines think?” His paper introduced the Turing test to determine whether a machine can display actual intelligence. Then in 1956, at Dartmouth College, researchers united to discuss and delve into their findings of artificial intelligence. Their published research soon gained government funding to encourage their studies of intelligence simulation. However, in their day and age, they presumptuously believed that A.I. was easily achievable, after discovering that was not the case, funding dwindled. From the 1960s to the 1990s, A.I. was sporadically revisited, but the continuous challenge of proper funding prevented progressive results. It wasn’t until 1997, Deep Blue, a chess-playing computer, defeated champion, Kasparov. This victory initiated the spark in A.I. and the development and research have only flourished since then.

Can A.I. read our thoughts?
According to recent studies, scientists have disclosed that A.I. has the ability to read a human’s thoughts through brain activity (Express Computer). Scientists have utilized A.I.’s deep learning algorithms to understand the mechanics of our brains and interpret their signals. Thanks to this discovery, victims of paralysis or speech disorders can benefit by allowing the A.I. to analyze their thoughts and grant more effective communication. Joseph Makin and his fellow colleagues used deep learning algorithms to study the brains of four women who have epilepsy, and then to understand the cause of their seizures, attached electrodes to their brains. While monitoring their brain activity, the researchers requested each woman to read aloud sentences made up of 250 unique words. The process continues as they enter the collected data into an algorithm designed to understand its meaning by training the program to recognize specific patterns associated with speech, i.e., constants. This process is repeated, but with the intention of: “instead of making the algorithm memorize brain activity, the researchers instead worked on getting the neural network algorithm to generalize results by identifying similarities” (Express Computer). The A.I., according to Makin, after using smaller sentences, could then understand word sequences better. This promising research could lead the pathway to help others communicate and encourage the trust for A.I. to be integrated into other sectors.

Project Debater
Members of IBM have constructed a cloud-based A.I. machine named the Project Debater. As we know, typically, debates are reserved for human opponents capable of constructing logical, passion-driven arguments to compel their audience’s support. IBM’s Project Debater, of course, is not human, but she can indeed argue like one. They developed Debater in seven years, using a natural language processing model in combination with deep learning techniques. The “Scientific American” claims: “Its model can cover 4-hundred million newspaper articles and Wikipedia pages in the times it takes a person to finish a cup of coffee”. The Debater is allowed the same 15 minutes as its human counterpart to prepare and research its topics and develop its opening statement and counter-arguments. The machine’s debate preparation includes gathering information based on relevance, ensuring an argumentative tone, and adequate evidence to support the designated stance. Furthermore, yes, the machine can listen and understand humans using the Watson Speech to Text; it even considers their argument in its rebuttal. Finally, the debate’s winner is decided by the audiences’ vote deciding which opponent delivered the most convincing argument. This machine would be helpful to policymakers and businesses and showcases the progress of A.I. understanding the human language.

Artificial Intelligence Knows How You're Feeling!
Finally, artificial intelligence is now capable of clearly identifying and processing human emotions. Affdex, created by Rana el Kaliouby and Rosalind Picard, is a more well-known emotion-based A.I. software. Affdex employs facial coding and emotion recognition software to determine which human emotion is being displayed successfully. This emotion-based A.I. begins by scanning the face, identifying each central portion, and then uses green dots called deformable and non-deformable points that differentiate the facial features that are immobile. Affdex also seeks changes in skin texture in conjunction with the deformable/non-deformable points in figuring the shown emotion. Astonishingly, The New Yorker states: “During the 2012 Presidential election, Kaliouby’s team used Affedex to track more than two hundred people watching clips of the Obama-Romney debates, and concluded that the software was able to predict voting preference with seventy-three-per-cent accuracy”. Not only is this software impressive, but it also could be integrated into the medical field or even interactively teach children how to identify their emotions.

Where Will We Go From Here? It is truly mind-boggling to comprehend just how advanced our technology has advanced within the last hundred years. We have progressed from reading by candlelight to having artificial intelligence be able to read our thoughts. A.I. has enabled technology to engage in argumentative conversations and even identify how we are feeling emotionally. The progressive advancement of A.I. will hopefully help better our hospitals, businesses, education system, and our infrastructure as a society.