Computer scientist John McCarthy was said to have coined the term “Artificial Intelligence” at a conference at Dartmouth College in 1956. The workshop was intended to research ways in which machines could be created to simulate various aspects of intelligence. Since then, the field of AI has made slow but steady progress. The advancement of computer technology, especially since 2000, has made it possible to create all types of intelligent or smart machines and devices that are in use and development today.
Artificial Intelligence before 1999
Artificial intelligence is the science and engineering of making intelligent machines that can reason, learn, perceive, solve problems and understand language. McCarthy and several other people
wanted to know if machines could truly be made to think for themselves, beyond their programming.
The 1956 workshop created a dedicated community of researchers who, under the newly dubbed field of AI, now had an identity. Over the next few decades, their work focused on areas such as simulating intelligence, heuristic search using mathematical theorems, character recognition, natural language processing and mobile robotics.
By the mid-1980s, however, there were still no significant practical successes directly tied to AI. This resulted in what’s called the “AI Winter,” when funding for research dried up due to lack of progress. A resurgence occurred in the 1990s after scientists realized the need to build intelligent systems from the ground up. By this time, computer technology and hardware had become more reliable and cheaper, making it easier to build robots that could use AI to do things. Also, the emergence of the Internet and its ability to house large amounts of data positioned AI for big things in the next century.
The New Millennium
According to a Stanford University report, the promise of artificial intelligence began to pay off at the turn of the millennium. The change was fueled by several factors, most notable was the level of machine learning now capable using information-processing algorithms. This, along with emerging new computer technology, became the foundation for trends in AI research. These trends included robotics, computer vision, natural language processing, large-scale learning, crowdsourcing and computational social choice.
Machine learning allowed artificial intelligence research to spread out over various sectors or domains. Some of those areas include transportation, health care, education, home service/robotics and public safety and security.
AI in Transportation
In the domain of transportation, the move toward intelligent or smarter cars began with the introduction of GPS or in-car navigation in 2001. The arrival of smart phones with GPS systems took another step in this direction. As smart technology improved, so did the capabilities of automobiles.
Cars today have a wide range of sensing capabilities such as blind-spot sensing, collision warning, automatic lights and windshield wipers, automated parallel parking features and more. Here’s a list of some automated capabilities and the dates they began appearing in commercial vehicles:
- 2003 – Intelligent parking assist system
- 2004 – Lane departure system
- 2005 – Adaptive cruise control
- 2007 – Blind spot monitoring
- 2015 – Lane changing
Today, companies such as Google and Tesla have made big strides autonomous vehicles because of the growth of sensing technology over the past two decades.
Another area of growth over since 2000 has been home/service robots. In 2001, the Electrolux Trilobite became the first commercial home robot. This vacuum cleaning machine had a basic control system to avoid obstacles and could navigate. Not long after this, iRobot introduced Roomba, which could do the same thing for one-tenth of the price. Robots in health care settings have also made big strides since 2000.
Education and AI
Artificial intelligence in education has also grown over the past two decades. Today, there are Intelligent tutoring systems, programs that allow teachers to personalize instruction for each student, teaching robots and a wide array of online learning systems. For example, the Carnegie Cognitive Tutor system has been teaching mathematics to American high school students. Intelligent tutoring systems can instruct students on computer literacy, chemistry, geography and other topics.
While this type of AI technology remains available in education, many schools and colleges have not been using them because they don’t have the funds needed to purchase these tools. What’s more, there’s not enough data available that proves the effectiveness of this technology.
Perhaps the biggest growth in education has been in online education at all levels, through what’s called Massive Open Online Courses (MOOCs). The popularity of these learning management systems, even at the graduate-level in college, appeals to those students and adult learners who prefer non-classroom settings that better fit their work schedules and lifestyles.
AI in Entertainment
The evolution of artificial intelligence since 2000 is probably most apparent in entertainment. The rapid growth and acceptance of the Internet have made user-generated content an accepted form of information and entertainment. Social media networks allow people to personalize their information, remain in constant touch with friends and share everything digital, from videos, blogs, photos, memes, tweets and posts.
The Internet has also allowed AI to create online communities such as Second Life and World of Warcraft. These role-playing simulations, set in virtual worlds, could not have been possible without the intelligent machines.
Not to be left behind, traditional sources of entertainment also use artificial intelligence. For example, more and more professional and collegiate sports teams are using quantitative analysis to crunch performance statistics to determine the best lineups for their teams.
Researchers believe one possible step ahead in the evolution of AI in entertainment will occur in people’s living rooms. Smarter hardware and software technology coupled with advances in AI could lead to personalized robotic companions that can talk, touch, move and think just like humans.
The steady growth of Artificial Intelligence, especially since 2000, has brought about broad positive implications for a variety of fields and industries. As with any advancing technology, however, AI carries risks and challenges that policymakers, the private sector, scientists, industries and the public must address. While no one knows how AI will affect us in the coming decades, many involved in this field agree about the need to prepare for it.