A Guide to Issues Related To Artificial Intelligence

The quest of this century to develop software and machines with human-like intelligence is inching closer to reality. Scientists are at the forefront of AI (Artificial Intelligence), trying to develop intelligent machines which can develop knowledge, simulate reasoning and permit computers to set and achieve goals by moving closer to imitating the thought process of humans.

Such intelligent systems enhance the accuracy of prediction, speed up problem-solving and automate administrative tasks, ushering in an era of automation. Some of the areas where artificial intelligence companies are devoting the use of AI are:

• Drugs/ medicine/ surgery
• Robots/ cyborgs/humanoids
• Intelligent personal assistants/ virtual personal assistants
• Business and industry
• Autonomous vehicles
• Defense and military
• Space technology
• Gaming

Comparison to Human Intelligence

Every human being is equipped with the same intellectual mechanism and differences in intelligence are attributed to ‘quantitative physiological and biochemical’ conditions. These include short-term memory, accurate long-term memory, and speed of thought.

But with AI, the case is different. Computer programs function with high memory and speed. However,  their capacities are associated with the intellectual methods which program designers understand well enough to include in such programs. They may feature abilities of teenagers and neglect some abilities of 2-year-olds.

There is more complication because of the fact that cognitive sciences have not gained success in identifying what exactly are human abilities. Most likely, the organization of intellectual mechanisms for AI can differ from that of people. When computers fail in tasks done by humans, this implies that the program designers lack the understanding of intellectual needs for such tasks.

Future of AI

Artificial intelligence in 2020 will have following applications in 2020 as developed by AI companies:

• Cognitive analytics: machines learn from experience and construct associations, help in the development of technological systems which evolve hypothesis, arrive at conclusions and codify experiences and instincts.
• Parallel processing of information: this is helped via chips custom-made for AI and aids in the parallel processing of great amounts of data.
• Re-definition of smart: with progress in the cloud, machine, and sensor learning technology, it pushes the boundary of smarter cars, homes, infrastructure and almost anything.
• Deep learning approach: It permits processing of raw data such as speech, images, and natural language which provide deeper insights.
• Machines for face reading: these understand facial expressions for providing meaningful information on an emotional condition of the user, enhancing computer-human interaction in areas of e-learning.
• Intelligent automation: It mixes automation with AI, which permits knowledge workers from stockbrokers to physicians, to understand the process and use of burgeoning volumes of data and information.

The question of AI Safety

The aim of keeping a beneficial impact of AI on society motivates research in several areas from law and economics to technical issues like control, security, validity, and verification. While you may experience a minor nuisance when your laptop gets hacked, a greater and more crucial issue is when the AI that controls your airplane, your pacemaker, your car or your power grid crashes. Another related issue is the AI controlled arms race in lethal, autonomous weapons.

Also, there is the worry if AI turns back on its human creators armed with an autonomous super-intelligence. Most experts envision that this scenario may not happen in this century but do not rule out the danger in the distant future. Thus incorporating safety issues into AI creations is considered an important issue.