What are the advantages and disadvantages of artificial intelligence?
Artificial neural
networks and deep
learning AI technologies are quickly evolving, primarily because AI can process
large amounts of data much faster and make predictions more accurately than
humanly possible.
While the huge volume of data created on a daily basis would
bury a human researcher, AI applications using machine learning can take that data
and quickly turn it into actionable information. As of this writing, a primary
disadvantage of AI is that it is expensive to process the large amounts of data
AI programming requires. As AI techniques are incorporated into more products
and services, organizations must also be attuned to AI's potential to create
biased and discriminatory systems, intentionally or inadvertently.
Advantages of AI
The
following are some advantages of AI.
·
Good
at detail-oriented jobs. AI
has proven to be as good or better than doctors at diagnosing certain cancers,
including breast cancer and melanoma.
·
Reduced
time for data-heavy tasks. AI
is widely used in data-heavy industries, including banking and securities,
pharma and insurance, to reduce the time it takes to analyze big data sets.
Financial services, for example, routinely use AI to process loan applications
and detect fraud.
·
Saves
labor and increases productivity. An example here is the use of warehouse automation, which grew during the pandemic and is
expected to increase with the integration of AI and machine learning.
·
Delivers
consistent results. The best AI
translation tools deliver high levels of consistency, offering even small
businesses the ability to reach customers in their native language.
·
Can
improve customer satisfaction through personalization. AI can personalize content, messaging, ads,
recommendations and websites to individual customers.
·
AI-powered
virtual agents are always available. AI programs do not need to sleep or take breaks, providing
24/7 service.
Disadvantages of AI
The
following are some disadvantages of AI.
·
Expensive.
·
Requires deep
technical expertise.
·
Limited supply of
qualified workers to build AI tools.
·
Reflects the biases of
its training data, at scale.
·
Lack of ability to
generalize from one task to another.
·
Eliminates human jobs,
increasing unemployment rates.
Strong AI vs. weak AI
AI
can be categorized as weak or strong.
·
Weak
AI, also known as narrow
AI, is designed and trained to complete a specific task. Industrial robots
and virtual personal assistants, such as Apple's Siri, use weak AI.
·
Strong
AI, also known as artificial general
intelligence (AGI),
describes programming that can replicate the cognitive abilities of the human
brain. When presented with an unfamiliar task, a strong AI system can use fuzzy logic to apply knowledge from one domain to
another and find a solution autonomously. In theory, a strong AI program should
be able to pass both a Turing test and the Chinese Room argument.