Marvin Minsky and Seymour Papert in their 1969 book Perceptrons, wrote, “One reason why progress has been so slow in [the AI field] is that researchers unfamiliar with its history have continued to make many of the same mistakes that others have made before them.” Minsky and Papert recognized the value of understanding the history of Artificial Intelligence (AI) before trying to make advancements in it. Understanding the foundational aspects of social media AI will ensure that no person or company is left behind in this new age of computing. Here is a brief history of AI that is helpful to understand when thinking about the role and capabilities of AI in current and future social media intelligence programs.
1950: “Turing Test”
Often referred to as the “father of modern computer science,” Alan Turing created the “Turing Test” in 1950 to assess whether a machine is intelligent. The British mathematician focused on formalizing the parameters on what can be computed. The original Turing Test requires a man, a woman, and an interrogator. The interrogator must identify which of the participants is a woman and which is a man. The answers to the interrogator’s questions are to be typed or repeated by a mediator. This way, the interrogator is unable to interpret the respondent’s gender by the sound of their voice.
The Turing Test replaces one of the participants with a machine and the goal of the interrogator switches from identifying the gender of the participants to determining which of them is human and which is a machine. Turing believed that passing as a human in such a test made devices capable of thinking. Despite this progress, the debate on whether devices are capable of thought and feeling has stumped computer scientists for years.
1956: The Term “Artificial Intelligence” is Coined
The term “artificial intelligence” was first coined by John McCarthy in 1956 when he held the first academic conference on the subject at Dartmouth College. The mission statement of the conference as stated by McCarthy was, “To proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.” The conference was the first on record where scientists used the term “artificial intelligence” and debated how to tackle it.
1959: Machine Learning
Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term “Machine Learning” in 1959 while at IBM. In the early days of AI, researchers were interested in having machines learn from data. Machine learning is a division of artificial intelligence where computer algorithms are created to comprehend data automatically. The algorithms do not have to be explicitly programmed but can change and improve on their own. Machine learning capabilities involve the process of using the data provided to the machine to improve algorithms over time and make increasingly accurate predictions. The active use of all the data allows the machine learning algorithm to update continuously. As time went on, machine learning was reorganized as a separate field from artificial intelligence and started to flourish in the 1990s.
1966: ELIZA is Born
ELIZA was the first tangible form of a virtual assistant. MIT professor Joseph Weizenbaum developed it at the MIT Artificial Intelligence Laboratory in 1966. Weizenbaum named it after Eliza Doolittle, a working-class character in George Bernard Shaw’s Pygmalion. The program carried out a conversation via text by following a “script” that directed it on how to respond. Although Natural Language Processing (NLP) programs such as Alexa and Siri are now part of our everyday lives, ELIZA marks a revolutionary turning point in the history of AI.
1972: AI Emerges in the Medical World
In 1972 at Stanford University, work began on MYCIN, an expert computer system that used artificial intelligence to treat blood infections. The name MYCIN came about because many antibiotics have the suffix “-mycin.” MYCIN attempted to diagnose patients using reported symptoms and medical test results. The program also suggested any additional medical tests that the patient might need and recommended a course of treatment. MYCIN was the first step in opening the doors for AI in the medical world. It operated at roughly the same level of competence as human specialists in blood infections, and somewhat better than general practitioners.
1974-1980: AI Winter
From 1974 to 1980, an “AI Winter” occurred. This period happened when government funding and interest in artificial intelligence decreased. Financial cuts during this time resulted in technology limitations. The resulting lack of computing power slowed down the progress of AI research.
1997: IBM’s “Deep Blue” Beats World Chess Champion
In 1997, an IBM computer, named “Deep Blue” beat world chess champion, Gary Kasparov. The computer’s win after the six-game match made headlines across the world. Thus, helping a broad audience better understand the power of AI.
2011: AI Becomes Part of Everyday Life
By 2011, technology advancements in hardware and software allowed AI to enter everyday life. When Apple introduced its virtual assistant, Siri, regular consumers had access to AI right in the palm of their hands. Other smartphone manufacturers also increased in popularity because of the inclusion of virtual assistants, Samsung Bixby for example.
Social Media AI
AI is beginning to play an integral part in the way that marketers make business decisions. It’s becoming increasingly important for marketers to leverage social media AI. It is imperative to analyze massive volumes of social conversations in real-time and convert the data into more profound actionable insights. Social media AI is helping marketers better understand their audience, customers, interests, competitors, and campaigns. This allows brands to better market to their target audience, and sell more relevant products and services to them.
Advances in AI are happening every day. Businesses and marketing departments are already adopting technology with AI capabilities. We live in an exciting time where AI is helping humans make quick, data-backed business decisions. By knowing the history of AI, marketers can make more informed decisions when evaluating social media AI capabilities.
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