Artificial Intelligence- Emerging Trend in Information System
Artificial
intelligence is a means to perform human-like operations through the use of
machines. The machines can learn from experience using this technique.
Computers can be trained to achieve particular tasks by processing and
analyzing lots of data and recognizing patterns in it. AI has the capability to
transform the world. It has led to numerous innovations such as connected
Internet of things, autonomous vehicles and the like. AI can even contribute to
help humans to experience feelings by connecting to the brain through complex
brain interfaces. Commerce, transportation, cybersecurity and healthcare are a
few of the systems revolutionized by AI. Security and explanation of AI systems
can be measured and enhanced by fundamental research. Standards have been
developed to ensure innovation, trust-worthiness and confidence in AI systems.
Description
AI
combines big data with intelligent algorithms and iterative processing to learn
from patterns within the data automatically. AI thrives on data as discussed in
conference proceedings of
- Neural Networks- The interconnected units called neurons process data by relaying information between the units and responding to external inputs. They derive meaningful information from undefined data using multiple passes at the data.
- Natural Language Processing- It allows machines to communicate with humans with natural language used by humans to carry out everyday activities.
- Cognitive Computing- This field focuses on simulating human processes by interpreting speech and images and providing coherent response like a natural human interaction.
- Machine Learning- This field facilitates automated analytical model building using different techniques from physics, statistics and neural networks.
- Deep Learning- Applications like Speech and image recognition use large neural networks having many processing units to learn complex patterns in data. The key units are graphical processing units which provide heavy compute power.
Why is AI required?
The
significant features of AI that make it mandatory in today’s scenario are
- AI
makes the existing applications intelligent. Large amount of data can be
combined with smart machines, robots and other automation platforms to improve
technology at home as well as at office.
- AI
can perform high-volume repetitive tasks with high reliability quotient sans
fatigue. Human supervision is essential to ask the right queries though.
- AI
analyzes data in deep learning through neural networks having several layers.
The deep learning models provide accurate response analysis by analyzing
humungous data directly.
- AI
offers a special technique of back propagation which allows the system to
adjust and learn from more data in case the result obtained is not accurate.
Progressive algorithms of AI are designed to explore structure and regularities
within the data in order to acquire the desired skill like playing carrom or
making product recommendation for future online shopping.
Strengths
As stated in
- Availability:
Unlike humans, machines can provide results irrespective of time, without
needing breaks and can perform long continuous jobs. It can be beneficial in
managing databases, fraud detection, prediction of human query, search and
intentions to substantial extent.
- Daily
Application: Autonomous techniques for learning and perception have become
common. These include smartphones, media utilities of face recognition, etc.
- Repetitive
task management: AI makes machine capable of taking the place of people and
performing tedious and repetitive activities and reduce human effort.
- Medical
assistance: Health care devices with machine intelligence can assess health
related data of patients and outlines risk factors under the supervision of
doctors. For example, artificial surgery simulator.
- Digital
Assistance: AI machines can offer correct program decisions on the basis of
logic. Advanced organizations have implemented AI to reduce human resource
requirement.
- Error
Reduction: AI can accomplish considerably low rate of error in comparison to
human error. Computers with AI can offer remarkable accuracy, speed and
precision.
- Dangerous
Exploration: AI systems can remain unaffected by belligerent environments and
still accomplish perilous tasks such as enduring troubles that may result into
life threatening situations like exploration in space, or hazardous activities
like mining fuels, etc.
Weaknesses
- Self-modifying,
when combined with self-replicating, can lead to dangerous, unexpected results,
such as a new and frequently mutating computer virus.
- Rapid
advances in AI could mean massive structural unemployment AI utilizing
non-transparent learning (i.e. neural networks) is never completely
predictable.
- One
major weakness is that AI incorporates knowledge from data. The accuracy rate
of results will thus depend on the accuracy of data.
- These
machines are programmed to accomplish specific task. They cannot behave like
humans.
- AI
machines incur major cost in their construction, rebuilding, storage and
repairing. Any repair will involve human intervention which makes it expensive.
- AI
machines are incapable of offering creativity as well as humans with the
ability of sympathizing and using common sense.
- If
coded incorrectly, the machines can lead to destruction.
How is AI used by Businesses?
AI
algorithms perceive things on the basis of patterns in data. AI can help humans
be better at their jobs in various fields. It can facilitate humans to acquire
better understanding, memory and better vision and lot more. It can enable
industries to use data analytics to improve their overall performance including
time series analysis and computer vision. Some of the industries utilizing AI
capabilities are:
- Retail
Industry: AI systems facilitate personalized recommendations on shopping items.
It can help the industry to organize and enhance stock management.
- Health
Care: Applications of AI provide assistance in daily activities of taking
pills, exercising and can further provide personalized photographic analysis
(X-Ray) and medicine
- Banking:
Techniques can be used in the banking sector to achieve accurate and efficient
credit scoring, to automate data management involved in intensive tasks and to
detect fraudulent transactions.
- Manufacturing:
AI machine uses machine learning and deep learning network to analyze data that
streams from manufacturing equipment, forecasting various manufacturing factors
for better efficiency of the system
Ethical Issues
It
is important to be heedful in making an assumption as documented in
- Although,
specialized AI has a limitation of serving specific purpose, AI in general may
be taken as an autonomous agent capable of taking independent initiative and
making plans.
- AI
may not share the stimulating tendency of people. AI may never resist to serve
the need of humans or desires of a specific human. For example, a machine
programmed to manufacture chairs, will manufacture chairs indefinitely and may
resist attempts to stop or change its goal of manufacturing the item.
- Humans
could not micromanage the behavior of the machines without sacrificing their
ability to function autonomously, thus losing the benefit of allowing them to
replace humans in performing certain tasks.
Conclusion
AI
is a field with lot of potential including sub-fields where it enhances the
performance of intelligent machines. AI is an impactful technology which can
influence almost all aspects of human life. The artificially intellectual
systems facilitate decision making over data by using the ability of the system
of deriving patterns from the data. They have increased the overall nature of
intelligence and understanding of intellectual reasoning.
Ethical
non-threatening machines should be created which can facilitate humans in
various ways and explore survival in a better amicable way. It is important to
boost transparency in algorithms to make the AI technology more reliable and
the inventors should take responsibility of the immense power of AI through
explaining and planning the actions in simple ways. Further, it is recommended
to regulate and improve the use of data. Specific regulations should be
outlined for the use of anonymous data considering the importance of data
privacy and security along with allowing movement of data beyond borders.
References
Bernhard Phringer, Jochen Renz. "AI 2015: Advances in Artificial Intelligence". 28th Australasian
Joint Conference, Australia, Nov 30-Dec 4, 2015 Proceedings
Dagsthul, Susan Leigh Anderson. "Machine Ethics". 2016
https://materials.dagstuhl.de/files/16/16222/16222.SusanLeigh%20Anderson.Preprint.pdf
Very well covered and informative article on AI ma'am 👍🏻✌🏻
ReplyDeleteplease give some information on deep Learning in coming series
Sure Mr. Chabra. Will soon come up on DL. Thanks for your feedback.
DeleteWhat I learnt recently is that there is no "Free Lunch" for all the ML alogorithms and AI concepts and it is critical to decide which concepts need to be used for a specific use-case. However, the best thing about this emerging trend is the infrastructure is now in a better state vs. we had 10 years ago. So comparing various systems has become quite efficient.
ReplyDeleteTo compare which AI method to use for a particular problem, one way could by developing AI prototype. But it is crucial to save oneself from making certain mistakes like not exploring every possible idea before deciding the use case, not considering how to integrate the chosen use case with the current system, availability of valid data in sufficient volume, etc.
ReplyDelete