How artificial intelligence is transforming the world
SUMMARY
Artificial intelligence (AI) is a broad tool that allows people to rethink how they combine data,
analyze it, and use the ensuing insights to make better decisions—and it's already affecting
every aspect of life. Darrell West and John Allen analyze AI's applicability in a range of fields,
address challenges in its development, and make ideas for getting the most out of AI while
maintaining key human values in this paper.
Artificial intelligence is a notion that most people are unfamiliar with (AI). When 1,500 senior
business leaders in the United States were polled in 2017, only 17% stated they were familiar
with artificial intelligence (AI). Several of them had no idea what it was or how it would affect
their businesses. They saw AI had a lot of potential for changing business processes, but they
didn't know how to put it to use in their own companies.
Despite its lack of general familiarity, artificial intelligence (AI) is a technology that is
revolutionizing every aspect of life. It's a versatile tool that allows people to rethink how they
integrate data, evaluate it, and use the insights to make better decisions. Our goal with this
thorough review is to explain AI to policymakers, opinion leaders, and interested observers, as
well as to show how AI is already changing the world and raising major challenges for society,
the economy, and governance.
We look at new applications in finance, national security, health care, criminal justice,
transportation, and smart cities, as well as challenges like data access, algorithmic bias, AI
ethics and transparency, and legal liability for AI choices in this article. We compare and
contrast the regulatory methods taken by the United States and the European Union, and we
conclude with a set of recommendations for getting the most out of AI while maintaining key
human values.
We offer nine measures for moving forward in order to realize AI's benefits:
● Encourage greater data access for researchers without compromising users’
personal privacy.
● Invest more government funding in unclassified AI research.
● Promote new models of digital education and AI workforce development so
employees have the skills needed in the 21st-century economy.
● Create a federal AI advisory committee to make policy recommendations.
● Engage with state and local officials so they enact effective policies.
● Regulate broad AI principles rather than specific algorithms.
● Take bias complaints seriously so AI does not replicate historic injustice,
unfairness, or discrimination in data or algorithms.
● Maintain mechanisms for human oversight and control.
● Penalize malicious AI behavior and promote cybersecurity.
I. QUALITIES OF ARTIFICIAL INTELLIGENCE
Although no universally accepted definition exists, AI is widely
understood to refer to "machines that respond to stimulus in the same
way as people do, given the human ability for deliberation, judgment,
and intention." These software solutions, according to academics
Shubhendu and Vijay, "make decisions that ordinarily require human
level of competence" and assist individuals in anticipating difficulties or
dealing with challenges as they arise. As a result, they act in a
deliberate, intelligent, and adaptive manner.
Intentionality
Artificial intelligence algorithms are created to make judgments based
on data that is often updated in real time. They differ from passive
machines, which are limited to mechanical or preset responses. They
combine data from a number of sources using sensors, digital data, or
remote inputs, evaluate the material in real time, and act on the
insights gained from the data. They are capable of considerable
sophistication in analysis and decision-making thanks to massive
increases in storage systems, computing speeds, and analytic
approaches.
Artificial intelligence is already
altering the world and raising
important questions for society, the
economy, and governance.
Intelligence
Machine learning and data analytics are frequently used in conjunction with AI. Machine
learning examines data for underlying patterns. Software designers can utilise this information
to evaluate specific difficulties if it notices something that is relevant to a practical problem. All
that is required is data that is sufficiently stable for algorithms to recognize valuable patterns.
Digital information, satellite images, visual information, text, and unstructured data are all
examples of data.
Adaptability
As they make decisions, AI systems have the potential to learn and adapt. Semi-autonomous
vehicles, for example, have features that warn drivers and vehicles of approaching traffic
congestion, potholes, highway construction, and other potential traffic barriers. Vehicles can
benefit from the experience of other vehicles on the road without the need for human
intervention, and the entire corpus of their gained "experience" is instantly and completely
transferable to other vehicles with similar configurations. Their powerful algorithms, sensors,
and cameras are based on real-world experience, and they combine dashboards and visual
displays to show information in real time so that human drivers can understand current traffic
and vehicular situations. Furthermore, in the case of fully autonomous vehicles, advanced
technologies can entirely control the vehicle.
II. APPLICATIONS IN DIVERSE SECTORS
AI isn't a far-fetched concept; it's already here, and it's being integrated and implemented across
a wide range of industries. Finance, national security, health care, criminal justice,
transportation, and smart cities are all examples of this. There are countless instances when AI
is already having a substantial impact on the world and complementing human capabilities.